Дисертації: "Optimal power dispatch"

1

Ali, Habib K. "Mathematical modelling of the optimal power dispatch problem." Thesis, University of Strathclyde, 1990. http://oleg.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=21285.

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This thesis is concerned with the optimum operating conditions in a power system. The various aspects of the problem are modelled and solved as a number of optimization problems applying linear programming techniques. A generalized linear mathematical model has been developed for this purpose. A two-stage formulation is adopted to represent the various problems considered. In each case one power system quantity is chosen as an objective function to be optimized under a number of constraints and operating limits relating to the power system relationships and upper and lower bounds on the variables. These include constraints derived from the power flow equations and transmission network capacity. Limits are also imposed on bus voltage magnitudes and generator outputs. With the appropriate selection of the combination of objective function and constraints, the model can be used to minimize the overall generation cost, the total system losses or the total reactive power generation. The two-stage modelling of the problem also allows optimizing two different objective functions at the same time. Two such combinations are possible. In one case the total system losses can be minimized in the first stage and the generation cost minimized in the second stage. The other combination minimizes the total system reactive power output and the active power generation cost. Using the same model, the problem is then solved using decomposition techniques. These imply breaking up the original problem into a number of smaller problems that can be solved almost independently. The mathematical model has been developed in general terms and the associated computer program is written for a general power system. A sample system of medium size has been used to test the validity of the various aspects of the suggested model and produce numerical results.

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2

Liu, Kai, and 劉愷. "Optimal dispatch and management for smart power grid." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2011. http://hub.hku.hk/bib/B46336680.

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3

Basu, Meheli. "Optimal dispatch in Smart Power Grids with partially known deviation." Thesis, University of Iowa, 2015. https://ir.uiowa.edu/etd/1825.

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Power grid is an interconnected system of supplying electricity from the supplier to the consumer, consisting of electricity generating plant, high voltage transmission lines- to carry electricity from the generating plant to the load center, and distribution lines- to carry electricity from load centers to individual consumers. A lot of research is being pursued to develop technologies for improving the next generation of power grid called the Smart Power Grid. The Smart Power Grid will have sophisticated communication infrastructure to improve the efficiency of electricity generation using renewable energy sources like the sun, water, etc and also to inform consumers of their electricity usage pattern. Also, the electricity market is now divided into three sections- generation, transmission and distribution. Private companies are competing with each other to provide electricity at the most competitive market price. We have developed two algorithms to help generating companies achieve their goal of meeting the hourly electricity need of the consumers and to do so at a minimum total cost.

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4

Cho, Brian Bumseok. "A distributed control approach to optimal economic dispatch of power generators." Thesis, University of Iowa, 2010. https://ir.uiowa.edu/etd/787.

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In this dissertation, we propose a novel distributed approach to the control of generators in the electric grid. Specifically, we consider the problem of the optimal economic dispatch of generator; we present a simple, distributed algorithm, which adjusts the power-frequency set-points of generators to correct for power imbalances arising from generation and load fluctuations. In this algorithm each generator independently adjusts its real-power output based on its estimate of the aggregate power imbalance in the network; such as an estimate can be independently obtained by each generator through local measurements of the frequency deviation on the grid. Eventually, over the course of network operation, the distributed algorithm achieves the equal-marginal-cost power allocation among generators while driving the power imbalance exponentially to zero. In the absence of power losses, we prove the eventual optimality of the distributed algorithm under mild assumptions (strict convexity and positivity of cost functions) and present simulation results to compare its performance with traditional (centralized) dispatch algorithms. Furthermore, we present numerical simulation results that show that the distributed algorithm performs well even in the presence of power losses and other constraints. We argue that distributed control methods are especially attractive for electric grids with smart meters and other advanced capabilities at the end node and grids with high penetration of alternative energy generators and we identify interesting open problems for future work in this area.

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5

Abuella, Mohamed A. "STUDY OF PARTICLE SWARM FOR OPTIMAL POWER FLOW IN IEEE BENCHMARK SYSTEMS INCLUDING WIND POWER GENERATORS." OpenSIUC, 2012. https://opensiuc.lib.siu.edu/theses/991.

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AN ABSTRACT OF THE THESIS OF Mohamed A. Abuella, for the Master of Science degree in Electrical and Computer Engineering, presented on May 10, 2012, at Southern Illinois University Carbondale. TITLE:STUDY OF PARTICLE SWARM FOR OPTIMAL POWER FLOW IN IEEE BENCHMARK SYSTEMS INCLUDING WIND POWER GENERATORS MAJOR PROFESSOR: Dr. C. Hatziadoniu, The aim of this thesis is the optimal economic dispatch of real power in systems that include wind power. The economic dispatch of wind power units is quite different of conventional thermal units. In addition, the consideration should take the intermittency nature of wind speed and operating constraints as well. Therefore, this thesis uses a model that considers the aforementioned considerations in addition to whether the utility owns wind turbines or not. The optimal power flow (OPF) is solved by using one of the modern optimization algorithms: the particle swarm optimization algorithm (PSO). IEEE 30-bus test system has been adapted to study the implementation PSO algorithm in OPF of conventional-thermal generators. A small and simple 6-bus system has been used to study OPF of a system that includes wind-powered generators besides to thermal generators. The analysis of investigations on power systems is presented in tabulated and illustrative methods to lead to clear conclusions.

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6

Yasmeen, Aneela. "A Distributed Algorithm for Optimal Dispatch in Smart Power Grids with Piecewise Linear Cost Functions." Thesis, University of Iowa, 2013. https://ir.uiowa.edu/etd/4930.

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We consider the optimal economic dispatch of power generators in a smart electric grid for allocating power between generators to meet load requirements at minimum total cost. We assume that each generator has a piece-wise linear cost function. We first present a polynomial time algorithm that achieves optimal dispatch. We then present a decentralized algorithm where, each generator independently adjusts its power output using only the aggregate power imbalance in the network, which can be observed by each generator through local measurements of the frequency deviation on the grid. The algorithm we propose exponentially erases the power imbalance, while eventually minimizing the generation cost.

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7

Mohammadi, Javad. "Distributed Computational Methods for Energy Management in Smart Grids." Research Showcase @ CMU, 2016. http://repository.cmu.edu/dissertations/710.

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It is expected that the grid of the future differs from the current system by the increased integration of distributed generation, distributed storage, demand response, power electronics, and communications and sensing technologies. The consequence is that the physical structure of the system becomes significantly more distributed. The existing centralized control structure is not suitable any more to operate such a highly distributed system. This thesis is dedicated to providing a promising solution to a class of energy management problems in power systems with a high penetration of distributed resources. This class includes optimal dispatch problems such as optimal power flow, security constrained optimal dispatch, optimal power flow control and coordinated plug-in electric vehicles charging. Our fully distributed algorithm not only handles the computational complexity of the problem, but also provides a more practical solution for these problems in the emerging smart grid environment. This distributed framework is based on iteratively solving in a distributed fashion the first order optimality conditions associated with the optimization formulations. A multi-agent viewpoint of the power system is adopted, in which at each iteration, every network agent updates a few local variables through simple computations, and exchanges information with neighboring agents. Our proposed distributed solution is based on the consensus+innovations framework, in which the consensus term enforces agreement among agents while the innovations updates ensure that local constraints are satisfied.

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8

Kodsi, Sameh. "Accounting for the Effects of Power System Controllers and Stability on Power Dispatch and Electricity Market Prices." Thesis, University of Waterloo, 2005. http://hdl.handle.net/10012/930.

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Recently, the widespread use of power system controllers, such as PSS and FACTS controllers, has led to the analysis of their effect on the overall stability of power systems. Many studies have been conducted to allocate FACTS controllers so that they achieve optimal power flow conditions in the context of Optimal Power Flow (OPF) analysis. However, these studies usually do not examine the effect of these controllers on the voltage and angle stability of the entire system, considering that the types of these controllers and their control signals, such as reactive power, current, or voltage, have significant effect on the entire system stability.

Due to the recent transition from government controlled to deregulated electricity markets, the relationship between power system controllers and electricity markets has added a new dimension, as the effect of these controllers on the overall power system stability has to be seen from an economic point of view. Studying the effect of adding and tuning these controllers on the pricing of electricity within the context of electricity markets is a significant and novel research area. Specifically, the link among stability, FACTS controllers and electricity pricing should be appropriately studied and modelled.

Consequently, in this thesis, the focus is on proposing and describing of a novel OPF technique which includes a new stability constraint. This technique is compared with respect to existent OPF techniques, demonstrating that it provides an appropriate modelling of system controllers, and thus a better understanding of their effects on system stability and energy pricing. The proposed OPF technique offers a new methodology for pricing the dynamic services provided by the system's controllers. Moreover, the new OPF technique can be used to develop a novel tuning methodology for PSS and FACTS controllers to optimize power dispatch and price levels, as guaranteeing an adequate level of system security. All tests and comparisons are illustrated using 3-bus and 14-bus benchmark systems.

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9

Karimishad, Amir. "Transient stability-constrained load dispatch, ancillary services allocation and transient stability assessment procedures for secure power system operation." University of Western Australia. Energy Systems Centre, 2008. http://theses.library.uwa.edu.au/adt-WU2009.0028.

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[Truncated abstract] The present thesis is devoted to the development of new methods for transient stability-constrained optimal power flow, probabilistic transient stability assessment and security-constrained ancillary services allocation. The key objective of the thesis is to develop novel dispatch and assessment methods for power systems operation in the new environment of electricity markets to ensure power systems security, particularly transient stability. A new method for economic dispatch together with nodal price calculations which includes transient stability constraints and, at the same time, optimises the reference inputs to the Flexible AC Transmission System (FACTS) devices for maintaining power systems transient stability and reducing nodal prices is developed. The method draws on the sensitivity analysis of time-domain transient stability simulation results to derive a set of linearised stability constraints expressed in terms of generator active powers and FACTS devices input references. '...' The low computing time requirement of the two-point estimate method allows online applications, and the use of detailed power systems dynamic model for time-domain simulation which offers high accuracy. The two-point estimate method is integrated in a straightforward manner with the existing transient stability analysis tools. The integrated software facility has potential applications in control rooms to assist the system operator in decision making process based on instability risks. The software system when implemented on a cluster of processors also makes it feasible to re-assess online transient stability for any change in system configuration arising from switching control. The method proposed has been tested on a representative power system and validated using the Monte Carlo simulation. In conjunction with the energy market, by which forecasted load demand is met by generator dispatch, ancillary services are required in relation to control for secure system operation and power quality. The final part of the thesis has a focus on the key aspect of allocating these ancillary services, subject to an important constraint that the dispatch of the ancillary services will not impair the system security achieved in the load dispatch. With this focus and requirement, the thesis develops a new dispatch formulation in which the network security constraints are represented in the optimal determination of generator active power schedule and allocation of ancillary services. Contingencies considered include power demand variations at individual load nodes from the values specified for the current dispatch calculation. The required changes in generator active powers to meet the new load demands are represented by additional control variables in the new dispatch formulation which augment those variables in the traditional OPF dispatch calculation. Based on the Lagrange function which includes the extended set of security constraints, the formulation derives the optimality condition to be satisfied by the dispatch solution, together with the marginal prices for individual ancillary service providers and LMPs. The effects of the security constraints are investigated and discussed. Case studies for representative power systems are presented to verify the new dispatch calculation procedure.

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10

Min, Liang. "Decomposition algorithms for multi-area power system analysis." Texas A&M University, 2003. http://hdl.handle.net/1969.1/5919.

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A power system with multiple interconnected areas needs to be operated coordinately for the purposes of the system reliability and economic operation, although each area has its own ISO under the market environment. In consolidation of different areas under a common grid coordinator, analysis of a power system becomes more computationally demanding. Furthermore, the analysis becomes more challenging because each area cannot obtain the network operating or economic data of other areas. This dissertation investigates decomposition algorithms for multi-area power system transfer capability analysis and economic dispatch analysis. All of the proposed algorithms assume that areas do not share their network operating and economic information among themselves, while they are willing to cooperate via a central coordinator for system wide analyses. The first proposed algorithm is based on power transfer distribution factors (PTDFs). A quadratic approximation, developed for the nonlinear PTDFs, is used to update tie-line power flows calculated by Repeated Power Flow (RPF). These tie-line power flows are then treated as injections in the TTC calculation of each area, as the central entity coordinates these results to determine the final system-wide TTC value. The second proposed algorithm is based on REI-type network equivalents. It uses the Continuation Power Flow (CPF) as the computational tool and, thus, the problem of voltage stability is considered in TTC studies. Each area uses REI equivalents of external areas to compute its TTC via the CPF. The choice and updating procedure for the continuation parameter employed by the CPF is implemented in a distributed but coordinated manner. The third proposed algorithm is based on inexact penalty functions. The traditional OPF is treated as the optimization problems with global variables. Quadratic penalty functions are used to relax the compatible constraints between the global variables and the local variables. The solution is proposed to be implemented by using a two-level computational architecture. All of the proposed algorithms are verified by numerical comparisons between the integrated and proposed decomposition algorithms. The proposed algorithms lead to potential gains in the computational efficiency with limited data exchanges among areas.

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11

Amorim, Elizete de Andrade [UNESP]. "Fluxo de potência ótimo em sistemas multimercados através de um algorítmo evolutivo multiobjetivo." Universidade Estadual Paulista (UNESP), 2006. http://hdl.handle.net/11449/100376.

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Esta pesquisa tem por objetivo o desenvolvimento de uma ferramenta computacional para a solução do problema de Fluxo de Potência Ótimo Multimercado (FPOM). O problema de fluxo de potência ótimo mutimercado é decomposto em vários subproblemas, uma para cada, submercado que compõe o sistema de potência interconectado. O modelo de decomposição utilizado permite resolver o problema de FPO considerando-se os modelos de mercado desverticalizados e centralizados e os desverticalizados e descentralizados. Neste contexto, a pesquisa desenvolvida considera o novo esquema de funcionamento dos mercados de energia elétrica, no qual é vi freqüentemente desejável preservar a autonomia de cada um dos submercados que compõem o sistema de potência multimercado. O problema de FPO proposto é modelado como um problema de otimização não-linear inteiro misto, com variáveis de controle contínuas e discretas e têm ênfase no despacho econômico da geração de potência ativa e nos ajustes dos controles de tensão. Além disso, este modelo de FPO trata os subproblemas ativo e reativo simultaneamente. Para a sua solução é apresentado um algoritmo evolutivo multiobjetivo, baseado no NSGA (Nondominated Sorting Genetic Algorithm), pois características do problema abordado dificultam a sua solução através das técnicas baseadas em programação matemática e justificam a escolha da metaheurística multiobjetivo.
This research is aimed at developing a computational tool for the solution of the Multimarket Optimal Power Flow (MOPF) problem. The multimarket optimal power flow problem is decomposed in various subproblems, one for each submarket that is part of the interconnected power system. The decomposition model used here allows solving the OPF problem considering the deregulated and centralized, and the deregulated and decentralized market models. In this context, the developed research takes into account the new functioning scheme of the electric power markets, viii where it is frequently desirable to preserve the autonomy of each one of those submarkets that compose the multimarket power system. The proposed OPF problem is modeled as a mixed integer non-linear optimization problem with continuous and discrete control variables, emphasizing the economic dispatch of the active power generation and the voltage control adjustments. In addition, this model of OPF deals simultaneously with the active and reactive subproblems. For its solution, a multiobjective evolutionary algorithm based on the NSGA (Nondominated Sorting Genetic Algorithm) is presented. The characteristics of the problem make difficult the utilization of techniques based on mathematical programming, justifying the adoption of a multiobjective metaheuristic.

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12

Alex, Ansu. "Tidal stream energy integration with green hydrogen production : energy management and system optimisation." Thesis, Normandie, 2022. http://www.theses.fr/2022NORMC216.

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L'objectif principal de cette thèse est de concevoir, mettre en œuvre et comparer différentes stratégies de gestion de l'énergie et approches d'optimisation pour un système hybride impliquant l'intégration de l'énergie marémotrice flottante avec la production de l'hydrogène vert. Pour atteindre les objectifs, les composants individuels du système sont d'abord modélisés. Les capacités annuelles de performance du système de la centrale d'énergie marémotrice ont ensuite été obtenues à l'aide des profils quotidiens fréquents au poste d'amarrage de Fall of Warness dans les îles Orcades. Les modes de fonctionnement transitoires des électrolyseurs à membrane échangeuse de protons, lorsqu'elles sont soumises à l'énergie de la centrale hydrolienne, ont été analysés sur la base d'une (RBA) stratégie de gestion de l'énergie basée sur des règles. Plus tard, une évaluation préliminaire du coût de production d'hydrogène est effectuée sur la base de différentes conditions de demande quotidienne d'hydrogène et de profils de marée quotidiens. En outre, une approche d'optimisation dans le but de maximiser le profit d'exploitation du système tout en assurant un fonctionnement optimal et suffisant des deux électrolyseurs sous des contraintes réelles du système, est formulée en donnant la priorité à la production d'hydrogène par l'énergie marémotrice. Le problème d'optimisation est résolu à l'aide d'un algorithme génétique basé sur un problème non linéaire à entiers mixtes. Une analyse coûts-avantages complète basée à la fois sur les coûts fixes-variables et sur les facteurs de coûts actualisés est réalisée pour analyser le fonctionnement technico-environnemento-économique optimal d'un système hybride d'énergie marémotrice-éolienne-hydrogène connecté au réseau. Les résultats ont été comparés aux résultats de l'approche basée sur des règles. Les bénéfices annuels dans l'approche d'optimisation ont été estimés supérieurs de 41,5 % par rapport à ceux de la RBA. De plus, d'un point de vue environnemental, les meilleurs résultats d'optimisation étaient supérieurs d’environ 47 % par rapport aux résultats de la RBA en termes de réduction des émissions de carbone. Un électrolyseur dynamique capable de fonctionner à deux fois sa puissance nominale pendant une durée limitée s'avère particulièrement avantageux lorsqu'il est couplé à l'énergie marémotrice qui est de nature cyclique avec des périodes prévisibles de production d'énergie élevée et faible. Enfin, il est conclu que l'approche d'optimisation des coûts fixes-variables est relativement simple dans l'estimation des coûts. Au contraire, bien que des résultats légèrement meilleurs soient obtenus dans le cas de l'approche par coût actualisé, il est nécessaire d'avoir une meilleure connaissance préalable du fonctionnement du système pour estimer finement les facteurs de coût actualisé. Le modèle proposé peut être utilisé comme un outil générique pour l'analyse de la production d'hydrogène dans différents contextes et il est particulièrement applicable dans les sites à fort potentiel d'énergie verte avec des installations de réseau limitées
The overarching aim of this thesis is to design, implement and compare different energy management strategies and optimisation approaches for a hybrid system involving floating tidal stream energy integration with green hydrogen production. Towards reaching the objectives, the individual system components are modelled initially. The annual system performance capabilities of the tidal stream energy plant are then obtained using frequently occurring daily profiles at the Fall of Warness berth in the Orkney Islands, Scotland. The transitionary operating modes of two polymer electrolyte membrane electrolyser units, when subjected to the energy from the tidal stream plant are analysed based on a rule-based approach energy management strategy. Later, a preliminary evaluation of the hydrogen production cost is assessed based on different daily hydrogen demand and daily tidal profile conditions. Further, an optimisation approach with the objective to maximise the system operating profit ensuring optimal and sufficient operations of both the electrolyser units under real system constraints, is formulated with priority for tidal energy powered hydrogen production. The optimisation problem is solved using a genetic algorithm based on the mixed integer non-linear problem. A comprehensive cost-benefit analysis based on fixed-variable costs and levelised costs factors is performed to analyse the optimal techno-enviro-economic operation of a hybrid grid connected tidal-wind-hydrogen energy system. The outcomes are compared against the rule-based approach results. The annualised profits in the optimisation approach are estimated to be 41.5% higher compared to the rule-based approach. Further, from an environmental view, the best optimisation results are approximately 47% higher than the rule-based approach results in terms of carbon emission reductions. A dynamic electrolyser capable of working at twice of its nominal power rating for limited duration, resulted particularly advantageous when coupled with tidal energy which is cyclic in nature with predictable periods of high and low power generation. Finally, it was determined that the fixed cost (FC) optimisation approach is relatively simple in terms of cost estimation. On the contrary, while the levelised cost (LC) approach yields slightly better results, it necessitates a greater prior knowledge of system operations to reasonably estimate the cost factors. The proposed method can be used as a generic tool for electrolytic hydrogen production analysis under different contexts, with preferable application in high green energy potential sites with constrained grid facilities

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13

Amorim, Elizete de Andrade. "Fluxo de potência ótimo em sistemas multimercados através de um algorítmo evolutivo multiobjetivo /." Ilha Solteira : [s.n.], 2006. http://hdl.handle.net/11449/100376.

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Orientador: José Roberto Sanches Mantovani
Banca: Rubén Augusto Romero Lázaro
Banca: Carlos Roberto Minussi
Banca: Geraldo Roberto Martins da Costa
Banca: Antônio César Baleeiro Alves
Resumo: Esta pesquisa tem por objetivo o desenvolvimento de uma ferramenta computacional para a solução do problema de Fluxo de Potência Ótimo Multimercado (FPOM). O problema de fluxo de potência ótimo mutimercado é decomposto em vários subproblemas, uma para cada, submercado que compõe o sistema de potência interconectado. O modelo de decomposição utilizado permite resolver o problema de FPO considerando-se os modelos de mercado desverticalizados e centralizados e os desverticalizados e descentralizados. Neste contexto, a pesquisa desenvolvida considera o novo esquema de funcionamento dos mercados de energia elétrica, no qual é vi freqüentemente desejável preservar a autonomia de cada um dos submercados que compõem o sistema de potência multimercado. O problema de FPO proposto é modelado como um problema de otimização não-linear inteiro misto, com variáveis de controle contínuas e discretas e têm ênfase no despacho econômico da geração de potência ativa e nos ajustes dos controles de tensão. Além disso, este modelo de FPO trata os subproblemas ativo e reativo simultaneamente. Para a sua solução é apresentado um algoritmo evolutivo multiobjetivo, baseado no NSGA (Nondominated Sorting Genetic Algorithm), pois características do problema abordado dificultam a sua solução através das técnicas baseadas em programação matemática e justificam a escolha da metaheurística multiobjetivo.
Abstract: This research is aimed at developing a computational tool for the solution of the Multimarket Optimal Power Flow (MOPF) problem. The multimarket optimal power flow problem is decomposed in various subproblems, one for each submarket that is part of the interconnected power system. The decomposition model used here allows solving the OPF problem considering the deregulated and centralized, and the deregulated and decentralized market models. In this context, the developed research takes into account the new functioning scheme of the electric power markets, viii where it is frequently desirable to preserve the autonomy of each one of those submarkets that compose the multimarket power system. The proposed OPF problem is modeled as a mixed integer non-linear optimization problem with continuous and discrete control variables, emphasizing the economic dispatch of the active power generation and the voltage control adjustments. In addition, this model of OPF deals simultaneously with the active and reactive subproblems. For its solution, a multiobjective evolutionary algorithm based on the NSGA (Nondominated Sorting Genetic Algorithm) is presented. The characteristics of the problem make difficult the utilization of techniques based on mathematical programming, justifying the adoption of a multiobjective metaheuristic.
Doutor

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14

Modesto, Sonia Angelina Garcia. "Um modelo de despacho e pré-despacho de retaivas através de algoritmos genéticos, fluxo de potência ótimo e busca tabu = A model of reactive dispatch and a model of short-term reactive operation planning through geneti algorithms, optimal power flow and search tabu." [s.n.], 2003. http://repositorio.unicamp.br/jspui/handle/REPOSIP/261159.

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Анотація:

Orientador: Takaaki Ohishi
Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação
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Resumo: Esta tese trata do problema de planejamento da operação de curto prazo (operação diária) de reativos. A Cadeia de Planejamento do Setor Elétrico brasileiro inicia com um Planejamento de Longo Prazo, o qual considera a operação do sistema através de modelos equivalentes em um horizonte de cinco anos. Em seguida o Planejamento de Médio Prazo, utilizando um modelo individualizado para cada usina hidrelétrica e termelétrica, analisa a operação para um horizonte de um ano à frente. A próxima etapa é de Programação da Operação, a qual determina a operação do sistema para o horizonte de alguns dias à frente. Finalmente, a solução da Programação da Operação é utilizada pela operação em tempo real como uma referência operativa. Em todas estas etapas, as modelagens representam apenas a geração e transmissão de potência ativa (Modelo DC). Para a parte reativa não há planejamento. Neste estudo sobre a parte reativa, enfocou-se o aspecto das variáveis discretas, mais precisamente os taps dos transformadores. Supõe-se conhecido um despacho de geração ativa, dado pela Programação da Operação, e um despacho de potência reativa, obtido por exemplo através de um caso base, ou através de um modelo de fluxo de potência ótimo reativo. Inicialmente foi estudado o problema de despacho de reativos, o qual considera o operação em um dado instante de tempo (problema estático). Para este problema, foram desenvolvidos três abordagens. A primeira é uma metodologia híbrida combinando Algoritmos Genéticos (AG) e um modelo de Fluxo de Potência Ótimo (FPO). Nesta abordagem as variáveis discretas são tratadas através dos AG e cada indivíduo é avaliado através de um FPO. A vantagem desta metodologia é que esta determina conjuntamente as variáveis continuas (geração de potência ativa e reativa) e as variáveis discretas; a desvantagem é o elevado tempo computacional. Buscando diminuir o tempo de processamento, foram desenvolvidos duas outras metodologias, uma utilizando um método de Busca Local e a outra baseada em Busca Tabu. Em ambas as metodologias, o FPO foi substituído por um modelo de fluxo de potência não linear. O plano de operação reativa ao longo de um dia, aqui denominado prédespacho de reativos, visa estimar uma solução em termos do posicionamento dos taps para cada intervalo do dia, buscando obter um perfil de tensão mais adequado do ponto de vista operativo. A abordagem para o pré-despacho de reativos utiliza o modelo de despacho de reativos baseado em Busca Tabu, mas considera a solução obtida no intervalo anterior. Todas as metodologias utilizaram o sistema IEEE30 como sistema teste
Abstract: This thesis treats the short-term (daily operation) reactive operation planning. The Brazilian operation planning initially performs a long-term operation study. This planning uses a equivalent model representation and take into account a time horizon of five years. The next step is the mid operation planning, that uses a individual representation and considers one year operation. The last planning determines the short-term operation using a more detailed model, including transmission operation constraints through a linear model. Finally, this short-term planning is used as operational guidelines in the real time operation. The models used in these different planning represent only the active power generation and transmission. For reactive operation there are not planning. This study about reactive operation focused the discrete decision. More specifically, the taps are treated as discrete variables. The methodologies supposes that the active and reactive power generations are given. Initially, the reactive dispatch problem is treated, and three methodologies are developed. The first is a hybrid model, that combines a Genetic Algorithm approach with an Optimal Power Flow model. This methodology has the advantage to determine the active and reactive generations and discrete variables values; the inconvenient is the high computer time processing. Two others methodologies are developed in order to obtain more faster approach. One approach is based on Local Search and the other is based on Tabu Search. In both methodologies, the OPF model is substituted by a non-linear power flow. The proposed daily reactive operation planning aims to determines the taps position for each time interval, looking for a more operationally suitable voltage profile. This planning is based on the Tabu Search Reactive Dispatch model. All methodologies used the IEEE30 as test system
Doutorado
Automação
Doutora em Engenharia Elétrica

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Kasmaei, Mahdi Pourakbari [UNESP]. "Despacho ótimo de potências ativa e reativa de sistema elétricos multi-áreas considerando restrições físicas, econômicas e ambientais =: Envronmentally constrained active-reactive optimal power flow-a compromising strategy for economic-emission dispatch and a multi-area paradigm." Universidade Estadual Paulista (UNESP), 2015. http://hdl.handle.net/11449/126414.

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Nos estudos de planejamento da operação de sistemas de energia elétrica a formulação e solução dos problemas de despacho econômico-ambiental e multi-área são considerados dois problemas de otimização desafiadores. Neste trabalho propõem-se dois novos modelos matemáticos que visam contribuir e contornar algumas desvantagens dos modelos existentes na literatura para os problemas de fluxo de potência ótimo ativo-reativo econômico- ambiental (FPOAREA), e uma formulação integrada para problema multi-área (FPOAREA- MA). No FPOAREA propõe-se uma formulação eficaz para obter um compromisso adequado entre os custos de geração e de emissão, através de um paradigma baseado em normalização inequívoca (PBNI). Ao contrário dos métodos comumente utilizados, que são principalmente aplicáveis a problemas de FPO simples (despacho econômico, despacho econômico com restrições de segurança, etc.), na abordagem PBNI, ao invés de usar um custo do controle da poluição com base na potência máxima (CCPBPM), utiliza-se um custo de controle adaptativo da poluição (CCAP), que representa o custo de controle baseado na topologia atual de operação da rede. A principal contribuição desse paradigma é utiliza a teoria da normalização para o FPO econômico-orientado, o FPO ambiental-orientado, e até mesmo para o fator CCAP. No modelo proposto para o FPOAREA-MA em vez de usar metodologias de decomposição descritas na literatura que têm várias desvantagens e problemas de coordenação, uma formulação integrada que considera as restrições ambientais é proposta. Esta formulação integrada foi desenvolvida com base nos conceitos de modelos centralizados e descentralizados. Este modelo pode ser facilmente resolvido através de solvers comerciais e a sua resposta é precisa, e os resultados obtidos podem ser usados em mercados de eletricidade, planejamento de linhas de interconexões entre sistemas vizinhos, etc. Para mostrar...
In a power system, the economic and emission dispatch and multi-area-based problems are considered as the two most challenging optimization problems. This work presents two novel mathematical models to address some drawbacks of the existing models in the domain of the aforementioned problems, including an economic and emission active- reactive optimal power flow (AROPF), and an integrated formulation for multi-area environmentally-constrained AROPF. In order to obtain an effective formulation to make an appropriate compromise between cost and emission, an unequivocal normalization-based paradigm (UNBP) is presented that solves the dynamic economic and emission AROPF problems. Unlike the commonly used methods, which are mostly applicable to simple OPF problems (economic dispatch, security-constrained economic dispatch, etc.), in the UNBP approach, rather than using a maximum output-based pollution control cost (MOPCC), an adaptive pollution control cost (APCC) is employed, which is a topology-based control cost is used. The main contribution of this paradigm is to make use of the normalization theory for the economic- oriented OPF, the environment-oriented OPF, and even for the APCC factor. In addition, in this work a multi-area active-reactive optimal power flow (MA- AROPF) is proposed. In the MA-AROPF model, instead of using decomposition methodologies that have several disadvantages and shortcomings, an integrated formulation that considers the environmental constraints is proposed. This integrated formulation has been created based on the concepts of centralized and decentralized models. This model can be easily solved via commercial solvers and because of its precise answer, it can be used in electricity markets, tie line planning, etc. In order to show the easy implementable characteristic of the MA-AROPF, it is applied on a tie line planning problem. In this work, in order to obtain optimal tie lines, the planning is performed under ...

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Kasmaei, Mahdi Pourakbari. "Despacho ótimo de potências ativa e reativa de sistema elétricos multi-áreas considerando restrições físicas, econômicas e ambientais = Envronmentally constrained active-reactive optimal power flow-a compromising strategy for economic-emission dispatch and a multi-area paradigm /." Ilha Solteira, 2015. http://hdl.handle.net/11449/126414.

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Orientador: José Roberto Sanches Mantovani
Banca: Ruben Augusto Romero Lazaro
Banca: Antonio Padilha Feltrin
Banca: Elizete de Andrade Amorim
Banca: Roberto Chouhy Leborgne
Resumo: Nos estudos de planejamento da operação de sistemas de energia elétrica a formulação e solução dos problemas de despacho econômico-ambiental e multi-área são considerados dois problemas de otimização desafiadores. Neste trabalho propõem-se dois novos modelos matemáticos que visam contribuir e contornar algumas desvantagens dos modelos existentes na literatura para os problemas de fluxo de potência ótimo ativo-reativo econômico- ambiental (FPOAREA), e uma formulação integrada para problema multi-área (FPOAREA- MA). No FPOAREA propõe-se uma formulação eficaz para obter um compromisso adequado entre os custos de geração e de emissão, através de um paradigma baseado em normalização inequívoca (PBNI). Ao contrário dos métodos comumente utilizados, que são principalmente aplicáveis a problemas de FPO simples (despacho econômico, despacho econômico com restrições de segurança, etc.), na abordagem PBNI, ao invés de usar um custo do controle da poluição com base na potência máxima (CCPBPM), utiliza-se um custo de controle adaptativo da poluição (CCAP), que representa o custo de controle baseado na topologia atual de operação da rede. A principal contribuição desse paradigma é utiliza a teoria da normalização para o FPO econômico-orientado, o FPO ambiental-orientado, e até mesmo para o fator CCAP. No modelo proposto para o FPOAREA-MA em vez de usar metodologias de decomposição descritas na literatura que têm várias desvantagens e problemas de coordenação, uma formulação integrada que considera as restrições ambientais é proposta. Esta formulação integrada foi desenvolvida com base nos conceitos de modelos centralizados e descentralizados. Este modelo pode ser facilmente resolvido através de solvers comerciais e a sua resposta é precisa, e os resultados obtidos podem ser usados em mercados de eletricidade, planejamento de linhas de interconexões entre sistemas vizinhos, etc. Para mostrar...
Abstract: In a power system, the economic and emission dispatch and multi-area-based problems are considered as the two most challenging optimization problems. This work presents two novel mathematical models to address some drawbacks of the existing models in the domain of the aforementioned problems, including an economic and emission active- reactive optimal power flow (AROPF), and an integrated formulation for multi-area environmentally-constrained AROPF. In order to obtain an effective formulation to make an appropriate compromise between cost and emission, an unequivocal normalization-based paradigm (UNBP) is presented that solves the dynamic economic and emission AROPF problems. Unlike the commonly used methods, which are mostly applicable to simple OPF problems (economic dispatch, security-constrained economic dispatch, etc.), in the UNBP approach, rather than using a maximum output-based pollution control cost (MOPCC), an adaptive pollution control cost (APCC) is employed, which is a topology-based control cost is used. The main contribution of this paradigm is to make use of the normalization theory for the economic- oriented OPF, the environment-oriented OPF, and even for the APCC factor. In addition, in this work a multi-area active-reactive optimal power flow (MA- AROPF) is proposed. In the MA-AROPF model, instead of using decomposition methodologies that have several disadvantages and shortcomings, an integrated formulation that considers the environmental constraints is proposed. This integrated formulation has been created based on the concepts of centralized and decentralized models. This model can be easily solved via commercial solvers and because of its precise answer, it can be used in electricity markets, tie line planning, etc. In order to show the easy implementable characteristic of the MA-AROPF, it is applied on a tie line planning problem. In this work, in order to obtain optimal tie lines, the planning is performed under ...
Doutor

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17

Altimari, Márcia Marcondes Rezende Simões. "Uma estratégia ótima para o despacho de potência ativa AC com restrição na transmissão." Universidade de São Paulo, 1999. http://www.teses.usp.br/teses/disponiveis/18/18133/tde-16112017-123038/.

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Neste trabalho realizamos um estudo do Despacho de Potência Ativa AC, o qual é uma estratégia de alocação da geração de potência entre as usinas de um sistema. Para isto, obtivemos dados teóricos, a partir de levantamento bibliográfico, que explicitaram os conceitos de Despacho Ativo. Fundamentamos, metodologicamente, nossa pesquisa no Método da Função Lagrangeana Aumentada. O sistema de equações resultantes das condições de otimalidade foram resolvidos pelo Método de Newton Modificado. Apresentamos os resultados de estudos de casos acadêmicos para a validação e verificação da eficiência da abordagem proposta. Os resultados indicaram uma coerência com as perspectivas reais de contribuição na resolução do Despacho Ótimo de Potência Ativa AC.
In this work we accomplished a study of the AC Active Power Dispatch, which is a strategy of distribution of the power generation among the plants of a system. For this, we obtained theoretical data, starting from bibliographical investigation, that elucidated the concepts of Active Dispatch. We based our research in the Method of the Augmented Lagrangian Function. The equation system originated of the optimal conditions was solved for Modified Newton\'s Method. We presented the results of studies of academic cases for the validation and verification of the efficiency of the proposal approach. The results indicated a coherence with the real perspectives of contribution in the resolution of the AC Active Optimal Power Dispatch.

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Baroche, Thomas. "Marchés pair-à-pair de l’électricité dans les réseaux électriques." Thesis, Rennes, École normale supérieure, 2020. http://www.theses.fr/2020ENSR0022.

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Le déploiement de ressources énergétiques distribuées, combiné à une gestion plus pro-active de la demande et à l'intégration de systèmes de gestion d'énergie, fait entrer l'exploitation des systèmes électriques et des marchés de l'électricité dans un nouveau paradigme. En partie liés à leur structure décentralisée, les marchés dits pair-à-pair ont gagné un intérêt considérable. Les marchés pair-à-pair reposent sur des négociations bilatérales entre les agents pour faire correspondre l'offre et la demande. De plus, ils peuvent cartographier l’ensemble des échanges possibles, ce qui permet de repenser ces interactions avec le réseau.Ces travaux de thèse traitent de trois défis majeurs dont la résolution est essentielle avant d'envisager le passage à des applications réelles : (i) le passage à l'échelle pour gérer un nombre croissant d'acteurs et de ressources distribués, (ii) le respect des contraintes du réseau électrique, et (iii) la résilience du marché à la présence d'agents stochastiques. Une analyse de complexité a permis de montrer que le passage à l’échelle des marchés pair-à-pair et le mécanisme de résolution peut être renforcé par trois améliorations réduisant les complexités algorithmiques et structurelles. Pour le respect des contraintes réseau, le manuscrit propose d’introduire des redevances qui seraient liées à l’utilisation du réseau électrique. Deux approches sont considérées pour déterminer ces redevances réseau. La première, exogène, exige que le gestionnaire de réseau les fournisse a priori avant le début des négociations. Dans la seconde, le gestionnaire de réseau actualise les redevances réseau de manière endogène à chaque itération pour mieux tenir compte de l'état actuel du réseau. Enfin, les prévisions de production et de consommation des agents stochastiques sont mieux prises en compte par la création d’un marché pair-à-pair de l'énergie et des capacités de réserve, pour corriger un éventuel déséquilibre de puissance due à des erreurs de prévision
The deployment of distributed energy resources, combined with a more proactive demand side management and energy management systems, is inducing a new paradigm in power system operation and electricity markets. Within a consumercentric market framework, peer-to-peer approaches have gained substantial interest. Peer-to-peer markets rely on multi-bilateral negotiation among all agents to match supply and demand. These markets can yield a complete mapping of exchanges onto the grid, hence allowing to rethink market–grid interactions.This thesis treats three main challenges which needs to be overcome before considering real world implementations: (i) scalability to host a growing number of distributed users and resources, (ii) compatibility with grid constraints, and (iii) resilience to stochastic power injections. After a complexity analysis, scalability of peer-topeer markets and the proposed negotiation mechanism to solve them is enhanced by three improvements reducing algorithmic and structural complexities. Feasibility of the peer-to-peer electricity market is eventually obtained with the use of network charges. Two approaches are proposed to handle these network charges. The first, exogenous, requires the system operator to provide them a priori before negotiations start. In the second, the system operator updates network charges endogenously at each iteration to better account for the current grid status. Finally, power forecasts of stochastic agents are taken in a more comprehensive way by the developpement of peer-to-peer market on both energy and capacities, used to restore power balance in case of misdipatch due to forecast errors

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Chung, Tak Shing. "An integrated approach incorporating dynamic and static security limits in optimum power dispatch." Thesis, University of Strathclyde, 1993. http://oleg.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=20375.

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Optimum power dispatch is performed in a power system to determine the most economic power dispatch condition for a certain system loading. In this thesis the main focus is on the investigation of this problem and its improved application by including both dynamic security and static security limits in its solution. The aim is to develop an efficient and practical on-line method of optimum power dispatch with due regard to the necessary security requirements. A critical review of the current practices of security and optimization in power system operation shows that they are essential elements in Energy Management System computer softwares. Since optimality and security present conflicting requirements on system operation, it is both logical and beneficial to develop an integrated approach to satisfy all the security limits in optimum dispatch. The classical approach to consider only the static security limits in optimum dispatch calculation is found to be insufficient in providi ng the essential informations on the dynamic security performance. This problem is causing increasing concern with the recent trend to load power systems more closer to their stability limits in order to achieve maximum economy. A new formulation of the security constrained optimum dispatch problem with an integrated approach to consider both dynamic and static security limits is thus proposed in this thesis. The Optimum Power Flow ( OPF ) formulation uses a Recursive Quadratic Programming algorithm applied in the compact modelling of the system. This formulation consists of a decoupling process of the active and reactive power optimizations. The investigation into on-line security control shows that insufficient attention on dynamic security in present practice could endanger the system integrity in the contingency state. This leads to the development of a new scheme to integrate both dynamic and static security assessments. Direct application of classical transient stability assessment methods using numerical integration of swing equations is found to be too slow and a new method based on reduced dynamic equivalent is investigated. The method is based on an efficient dynamic security assessment scheme which assesses the on-line operating state of the system. A dynamic security margin is defined to measure the robustness of the system when it is subjected to a selected scenario of dynamic contingency. The method also identifies the critical machine or cluster of machines that would cause transient instability, and proposes preventive control strategies to improve the dynamic security performance. This is integrated in the approach as a preventive control module. The module aims to prevent the system from reaching probable system collapse due to contingency that could cause cascading tripouts in the system. Extensive simulation tests are performed using the approach in several example networks together with validation case studies compared to full load flow and transient stability tests. The results demonstrate that the approach is fast and reliable with good potential for on-line application in stability limited power systems.

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Freire, Rene Cruz. "Otimização natural multiobjetivo como ferramenta para desvio mínimo de pontos de operação considerando restrições de segurança." Niterói, 2017. https://app.uff.br/riuff/handle/1/3927.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
Um dos temas de alta relevância para a sociedade atual é a qualidade do suprimento de energia elétrica, que deve ser ininterrupto, seguro e econômico. Para tal, é primordial que o sistema de potência esteja preparado para um possível defeito de algum equipamento da rede, mantendo a operação dentro dos patamares seguros, evitando os blecautes e todas as suas consequências para a sociedade. Isso pode ser feito através do redespacho das unidades geradoras, de modo a encontrar um ponto de operação que concilie segurança e economicidade, dois objetivos conflitantes, enquanto busca se afastar o mínimo possível do ponto de operação previamente estabelecido, via planejamento eletroenergético, para o sistema de potência em questão. Trata-se de uma abordagem multiobjetiva do Fluxo de Potência Ótimo com Restrições de Segurança (FPORS) que pode ser solucionada com uma abordagem de Computação Evolucionária (CE) com viés multiobjetivo. Neste trabalho, foram implementadas e comparadas duas meta-heurísticas evolutivas multiobjetivo: Nondominated Sorting Genetic Algorithm II (NSGA-II) e o Multi-objective Evolutionary Particle Swarm Optimization (MOEPSO). Os resultados dessas heurísticas também foram comparados com a abordagem mono-objetivo do mesmo problema. Os algoritmos foram implementados no MATLAB® e testados em um sistema-teste que simula as condições do Sistema Interligado Nacional (SIN). As heurísticas multiobjetivo foram comparadas através da metodologia de análise da Fronteira de Pareto (FP), onde é analisado qual método concilia melhor os objetivos de economia e segurança. Na primeira análise o NSGA-II saiu-se melhor, entretanto após a implementação de melhorias no algoritmo, o MOEPSO mostrou desempenho superior na segunda análise. Nas duas análises, o viés multiobjetivo mostrou-se superior ao mono-objetivo, na comparação através do critério de agregação de objetivos. Em relação ao tempo de simulação de cada método, o MOEPSO foi superior na primeira análise, já na segunda análise foi implementado um refinamento baseado no Fluxo de Potência Linearizado no FPORS, que baixou o tempo de simulação das duas heurísticas multiobjetivas em comparação com a primeira análise, e o MOEPSO teve o menor tempo de simulação. Na comparação com o viés mono-objetivo, apenas o NSGA-II teve tempo médio de simulação maior que o método mono-objetivo na primeira análise. Na segunda análise, todas as heurísticas multiobjetivo possuíam tempo de simulação menores que o método mono-objetivo.
One of the topics of high relevance to the today’s society is the quality of electric power supply, which must be uninterrupted, safe and economical. To this end, it is essential that the power system be prepared for a possible defect of some equipment from the network while maintaining operation within safe levels, avoiding blackouts and all its consequences for society. This can be done by redispatch of generating units, in order to find an operation point which conciliate security and economy, two conflicting objectives, while seeking to depart as little as possible of the operation point previously established in the energy planning for the power system in question. This is a multi-objective approach to Security Constrained Optimal Power Flow (SCOPF) that can be solved with an approach of Evolutionary Computation with multi-objective bias. In this work we were implemented and compared two multi-objective evolutionary meta-heuristics: Nondominated Sorting Genetic Algorithm II (NSGA-II) and Multi-objective Evolutionary Particle Swarm Optimization (MOEPSO). The results of these heuristics were also compared with mono-objective approach to the same problem. The algorithms were implemented in MATLAB® and tested in a test-case that simulates the conditions of the Brazilian Sistema Interligado Nacional (National Interconnected System). The multi-objective heuristics were compared using the analysis methodology of the Pareto Frontier, where is analyzed which method is better to conciliate the economy and security objectives. In the first analysis the NSGA-II fared better, but after the implementation of improvements in the algorithm, the MOEPSO showed superior performance in the second analisys. In both analyzes, the multi-objective bias was superior to the mono-objective bias, in the comparison through objectives aggregation criteria. Concerning the simulation time of each method, the MOEPSO was superior in the first analysis, but in the second analysis was implemented a refinement based on DC Load Flow, which lowered the simulation time of the two multi-objective heuristics compared with the first analysis, and the MOEPSO had the shortest time simulation. Compared to the mono-objective bias, only the NSGA-II had an average time simulation greater than the mono-objective method in the first analysis. In the second analysis, all multi-objectives heuristics had simulation time smaller than the mono-objective method.

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Leuthold, Florian U. "Economic Engineering Modeling of Liberalized Electricity Markets: Approaches, Algorithms, and Applications in a European Context." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2010. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-26135.

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This dissertation focuses on selected issues in regard to the mathematical modeling of electricity markets. In a first step the interrelations of electric power market modeling are highlighted a crossroad between operations research, applied economics, and engineering. In a second step the development of a large-scale continental European economic engineering model named ELMOD is described and the model is applied to the issue of wind integration. It is concluded that enabling the integration of low-carbon technologies appears feasible for wind energy. In a third step algorithmic work is carried out regarding a game theoretic model. Two approaches in order to solve a discretely-constrained mathematical program with equilibrium constraints using disjunctive constraints are presented. The first one reformulates the problem as a mixed-integer linear program and the second one applies the Benders decomposition technique. Selected numerical results are reported.

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22

Liu, ChingYi, and 劉清億. "The Research of Optimal Power Dispatch." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/34918277382316755881.

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碩士
元智大學
資訊管理研究所
93
In a power distribution system, all substations have their own equipment capacity to offer their power-supply area enough power. But sometimes the peak loads in their power-supply area are over than their equipment capacity. Therefore, the other substations in the same power-supply area have to offer their power aid to the one who needs the power. However, it’s hard to determine which is the best substation to be the transferred to and power transmission path that leads the minimal power loss. We apply genetic algorithm for searching optimal power transfer order in this research. The substation can transfer electricity to each other under the condition that electricity-deficient substation can be minimized, so the goal in problem formulation is to minimize total deficient electricity in the power supply area to use electric resource fully and reach load balance. On the other hand, in order to improve the searching ability of genetic algorithm, we implement the power transfer programs by constraint-based genetic algorithm to resolve the power transfer problem in our research. Finally, we implement some experiments to compare the result of constraint-based genetic algorithm with that of genetic algorithm to show the advantages of constraint-based genetic algorithm in searching time and quality. Finally, we hope we can consider more factors in the future research.

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23

Lee, Kai-Xiang, and 李凱翔. "Optimal Reactive Power Dispatch of Transmission Systems." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/8r3s96.

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Анотація:

碩士
國立臺北科技大學
電機工程系所
94
Reactive power dispatch is one of the major research topics in power system operation and planning. Optimal reactive power dispatch is one kind of multi-objective optimization problems. The goals of this thesis include voltage magnitude of load buses within reasonable region, reducing real power loss of transmission line, and good performance of voltage stability. They can avoid the risk of voltage collapse owing to load demand change or contingencies, get good voltage security and cost reduction. This thesis proposed two methods of particle swarm optimization and genetic algorithm to optimal reactive power dispatch of transmission systems, respectively. The advantage of these methods is to achieve near optimal solution for discrete nonlinear optimization problem. So this thesis simulates the proposed method for IEEE 30-bus power system and a practical Taipower system. The test results have proved that the proposed method can obtain the good performance. We wish that can help dispatchers to do more correct, economic, and secure dispatch.

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24

Lu, Shao-An, and 呂紹安. "Optimal Power Dispatch Planning under CO2 Emission Consideration." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/02474523137024796016.

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Анотація:

碩士
國立臺灣科技大學
電機工程系
98
In this thesis, the optimal power dispatch planning considering the emission of carbon dioxide (CO2) is presented. First, different CO2 equivalent models for fossil fuel generating units are derived. Secondly, two index, the Cost-CO2 emission Tradeoff Curve (CCTC) and Incremental Cost for CO2 Reduction (ICCR) curve, are introduced to assess the impact of the carbon dioxide emission on the generation cost. Incorporating with the aforementioned index, the single-objective and bi-objective programming methods are employed to establish the power dispatching strategy. The salient feature of the dispatching strategy lies that the decision-maker can consider the environmental and economic factors at the same time. Since the power dispatching belongs to large-scale non-linear planning problem, this study employs a particle swarm approach with novel coding scheme for power dispatch solution, which can fast find an optimal solution with higher probability. Finally, taking the 27-unit system of the Tai-power as an example, simulation result of the study reveals that the proposed dispatching strategy can indeed consider the carbon dioxide reduction impact on cost in off-peak, half-peak and peak load conditions to achieve environmental protection and economic purpose.

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25

CHIANG, YU-CHUAN, and 江昱銓. "Optimal Reactive Power Dispatch Using Ordinal Optimization Algorithm." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/98yp44.

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Анотація:

碩士
高苑科技大學
電子工程研究所
105
In this paper, we propose an Ordinal Optimization (OO) algorithm for the solution of the Optimal Reactive Power Dispatch (ORPD) problem. The main objective of QRPD is to minimize active power loss and improve the voltage profile of power systems. Our algorithm consists of three stages. This work first constructed a crude but efficient model from a sample space. Then, a scheme with enhanced accuracy based on sensitivity theory was applied to identify the top samples to form the selected subset. Finally, we obtain a good enough solution with smallest objective value. The proposed algorithm is tested on IEEE 118-bus system and results are compared with those of tabu research method and genetic algorithms. Test results demonstrate the efficiency of proposed algorithm in finding the good enough solution within a shortest computing time.

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26

Kuan-ChihTung and 董冠志. "Optimal Scheduling of Electric Energy for Microgrid Power Dispatch." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/cpau37.

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27

Husan, Yu-Chen, and 宣宇晨. "Study on Microgrid Power Dispatch by Optimal Load Shifting." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/6mj797.

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Анотація:

碩士
國立臺灣科技大學
電機工程系
106
This thesis applies optimal load shifting to microgrid power dispatch. First of all, a commercial software Solar Pro is used to create a solar PV system model and to simulate their power generation. The Weibull probability density distribution is used to create a wind speed model and calculate its power generation. Then, this paper uses the fmincon, the built-in function of Matlab® for optimal load shifting of users. Users change their electricity consumption habit according to different time-of-use and dynamic electricity pricing to achieve the goal of stabilizing load curve. After that, in the case of meeting various operational restrictions and making full use of renewable energy, the microgrid integrates the optimized load and joins the battery energy storage system, and applies the particle swarm optimization (PSO) algorithm to microgrid power dispatch. Simulation results show that the proposed method can reduce the cost and may provide a valuable reference for real-time control and dispatch of a microgrid system.

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28

Jung, Tay Ho. "Optimal reactive power dispatch based on a multiobjective optimization technique." 1988. http://catalog.hathitrust.org/api/volumes/oclc/18826554.html.

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Анотація:

Thesis (Ph. D.)--University of Wisconsin--Madison, 1988.
Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 148-160).

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29

GUAN-CHIH, PU, and 蒲冠志. "Short Term Real/Reactive Power Load Forecasting and Dynamic Optimal Dispatch." Thesis, 1998. http://ndltd.ncl.edu.tw/handle/12766221334530619211.

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Анотація:

博士
國立臺灣科技大學
電機工程技術研究所
86
The optimal dispatch of real/reactive power in a deregulated power system over a short period of time is investigated in this dissertation. The generation plants, transmission system and distribution systems will be separately owned under this condition. The consideration of profits of power producers, system- wide benefits and system security to determine the optimal dispatch pattern then becomes a significant task of the independent system operator (ISO). In this dissertation, the sensitivity factors are used to solve the optimal dispatch of real/reactive power over a short period of time. The traditional optimal power flow shows high accuracy, but it takes much computation time. Therefore, it cannot be applied to real-time operation, not to mention dynamically over the whole day scheduling period. In this dissertation, the artificial neural network is used for load forecasting and a two-step dynamic real power dispatch method considering inconforming load changes is developed to solve real power dispatch, and then, the sensitivity factors are used to solve reactive power dispatch with constraints. Finally, the dynamic programming technique is used to minimize control actions and to ensure bus voltagemagnitudes within the secure range over the scheduling time period. For wheeling, if there is any line flow beyond the secure range in the vested generation contracts, generation shifting factors are employed to move the excess line flow to other transmission lines to relieve the transmission congestion. Then, the reactive power/voltage sensitivity factors and dynamic programming technique are used to solve the reactive power dispatch with constraints. The proposed approach is applied to Taipower system. The results show that this methodology can minimize thecontrol actions in the whole day. It is simple and canenhance the operators'' planning greatly and can save a lot of switching cost.

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30

Lu, Nai-Yen, and 盧乃彥. "Optimal Active-Reactive Power Dispatch Using a Hybrid Taguchi-Genetic Algorithm." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/2rsy4s.

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Анотація:

碩士
國立臺北科技大學
電機工程系研究所
100
This paper presents a new approach to solve optimal active-reactive power dispatch problem in power systems by using a hybrid Taguchi-genetic algorithm. In the past researches, the active power dispatch and the reactive power dispatch are discussed separately. As a result, an intelligent control method is proposed to integrate theses two dispatch into one optimal power dispatch simultaneously in order to obtain a more complete optimization. The objective function combine with minimizing the fuel cost, which is associated with the economic dispatch, and reducing the real power loss in the transmission line, which is associated with the reactive power dispatch, by using weight values. In this paper, it is too difficult to obtain an optimal solution because of considering lots of variables at the same time. Therefore, a hybrid Taguchi-genetic algorithm is proposed to solve the problem by using the orthogonal array and the SNR(sinal-to-noise ratio). The proposed approach has been verified on IEEE 30-bus 6-generator system. The results are also compared with other approaches and it shows that the solution to active-reactive dispatch problem is better.

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31

Kao, Pei-Chun, and 高培鈞. "Artificial Bee Colony Algorithm for Multiple Objectives Optimal Power Dispatch Study." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/88w57z.

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Анотація:

碩士
國立臺北科技大學
電機工程系所
105
The traditional economic dispatch method has considered a single object function which is to minimize the generation cost. In fact, there are more than one object with related constraints to consider meeting the power demand requirements. In practical system, the problems have more than one object function to be optimized. These objectives normally conflict each others. In recent years, due to the rise of environmental awareness. For example, we optimized the generation cost as main objective, it might cause other cost increasing if we neglect line loss and pollution emission. The more difficult part of the multi-objective optimization problem is conflicting between various objectives. It is hardly to assess its quality. Thus, this thesis has proposed using “double model algorithm” for optimal power flow in order to solve this problem. The artificial bee colony algorithm’s searching and sorting mechanism can handle this mutual non-dominated information capability and find out the most representative of the mutual non-dominated solution set. To sort the most optimal solution without setting weight situation by using data envelopment analysis method for this solution set with the efficiency concept. As a result, the validity of this thesis has been demonstrated through IEEE 30-Bus system simulation of the proposed algorithm.

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32

Tsai, Yeong-Sheng, and 蔡永勝. "Ant Colony System for Optimal Reactive Power Dispatch of Transmission Systems." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/4t8tw3.

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Анотація:

碩士
國立臺北科技大學
電機工程系研究所
95
Reactive power dispatch is one of the major research topics in power system operation and planning. Reactive loads in a power system can cause phase differences for voltages and currents, leading to voltages drop and power loss in power lines. Optimal reactive power dispatch is accordingly adopted to solve the problems. This thesis proposes to apply Ant Colony System(ACS) to facilitate the multi-objective optimal reactive power dispatch for transmission systems. The proposed application aims at achieving three major purposes: regulating voltage magnitude of load buses within a reasonable region, reducing real power loss of transmission line, and ensuring good performance in terms of voltage stability. The proposed application can therefore be expected to avoid the risk of voltage collapse caused by changes in load demand or related contingencies. ACS is a heuristic algorithm adopting stochastic search to solve problems about large-size clustering effectively and to avoid early convergence that may provide at its best only local optimal. The route chosen by a substantial number of ants is very likely to attract more ants with a greater density of accumulated pheromones. This mechanism can be expected to help us identify solutions in an effective and efficient manner. The thesis simulates the proposed method on an IEEE 30-bus power system and an actual Taipower system. The dispatch solutions are then compared to their counterparts obtained by Ant System (AS), Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) respectively. Results show that the proposed method works best in reducing real power loss and securing voltage stability. The proposed method can therefore be expected to render dispatch safer, faster, and cheaper.

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33

Hsia, Cho-Yen, and 夏倬彥. "An Immune Algorithm for Optimal Reactive Power Dispatch of Transmission Systems." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/623y62.

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Анотація:

碩士
國立臺北科技大學
電機工程系研究所
96
For raising power system quality, efficiency and safety, reactive power dispatch is an important cause and accordingly adopted to solve problems. This thesis proposes to apply Immune Algorithm to facilitate the multi-objective optimal reactive power dispatch for transmission systems. The aims are achieving three major purposes: regulating voltage magnitude of load buses within a reasonable region, reducing real power loss of transmission line, and avoid the risk of voltage collapse owing to load demand change or contingencies. Immune Algorithm developed from the adaptive immune response in human body, the objective function and constraints are expressed as antigen and all feasible solutions are expressed as antibody. Use the memory cell function in immune system to keep the superior antibodies to next generation also avoid destroyed by crossover and mutation, equally use the suppressor cell function to restrain the high affinity antibodies that can increase diversity of antibodies to not falling into the local optimal solution. The thesis simulates the proposed method on IEEE 30-bus power system and simple Taipower system. The dispatch solutions are then compared to their counterparts obtained by Genetic Algorithm, Ant Colony System and Ant System respectively. Results show that the proposed method works best in reducing real power loss and securing voltage stability. The proposed method can therefore be expected to render dispatch safer, faster, and cheaper.

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34

Chiu, Hao-Jung, and 邱浩榮. "A Study on an Optimal Bid-Commitment-Dispatch Problem under Deregulated Power Environments." Thesis, 2001. http://ndltd.ncl.edu.tw/handle/11206164388647332619.

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Анотація:

碩士
義守大學
電機工程學系
89
Utilities around the world are confronted with the impact of a deregulation trend in the electric power industry. To make our country more grandly competitive, the government is aggressively working toward the liberalization of electric power industry, such as privatizing the power generation plants, encouraging the investment of co-generation plants, and revising the related regulation rules and laws for the new competitive power marketplace. The main object of this thesis is to investigate the optimal bid-commitment-dispatch problem under the framework of Independent System Operator (ISO), Power Exchange (PX), and Scheduling Coordinators (SCs) for a new competitive power market. The research provides the related lawmakers with important information from the electric power technical views so as to avoid possible conflicts. In the thesis, we first propose an optimal bid commitment problem that maximizes the overall power market’s benefit and considering its constraints. Secondly, under a bidding/offering system, we propose a new optimal dispatch problem that minimizes the total generation cost or variation and considering its constraints. In addition, we combine the two preceding problems into a new optimal bid-commitment-dispatch problem. The problem is subject to the objective function and the constraints considered in both problems. The motivation comes from the fact that the present real-power line flows are approaching their transmission limitation for many transmission lines. There is a very high chance to have a congested condition when the transmission capacities are not considered during the bid commitment process. It thus may need a re-allocation of the deal amounts via a congestion management procedure. In the thesis, the IEEE 14-bus system is used to investigate the feasibility of combined optimal bid-commitment-dispatch, compare the differences between approximate and realistic transmission line models, investigate the impacts for limiting the upper bound of bidding/offering generation amounts, study the impacts of different objective functions, and discuss the possibility of allowing power providers to buy and sell power at the same trading period.

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35

Agbugba, Emmanuel Emenike. "Hybridization of particle Swarm Optimization with Bat Algorithm for optimal reactive power dispatch." Diss., 2017. http://hdl.handle.net/10500/23630.

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This research presents a Hybrid Particle Swarm Optimization with Bat Algorithm (HPSOBA) based approach to solve Optimal Reactive Power Dispatch (ORPD) problem. The primary objective of this project is minimization of the active power transmission losses by optimally setting the control variables within their limits and at the same time making sure that the equality and inequality constraints are not violated. Particle Swarm Optimization (PSO) and Bat Algorithm (BA) algorithms which are nature-inspired algorithms have become potential options to solving very difficult optimization problems like ORPD. Although PSO requires high computational time, it converges quickly; while BA requires less computational time and has the ability of switching automatically from exploration to exploitation when the optimality is imminent. This research integrated the respective advantages of PSO and BA algorithms to form a hybrid tool denoted as HPSOBA algorithm. HPSOBA combines the fast convergence ability of PSO with the less computation time ability of BA algorithm to get a better optimal solution by incorporating the BA’s frequency into the PSO velocity equation in order to control the pace. The HPSOBA, PSO and BA algorithms were implemented using MATLAB programming language and tested on three (3) benchmark test functions (Griewank, Rastrigin and Schwefel) and on IEEE 30- and 118-bus test systems to solve for ORPD without DG unit. A modified IEEE 30-bus test system was further used to validate the proposed hybrid algorithm to solve for optimal placement of DG unit for active power transmission line loss minimization. By comparison, HPSOBA algorithm results proved to be superior to those of the PSO and BA methods. In order to check if there will be a further improvement on the performance of the HPSOBA, the HPSOBA was further modified by embedding three new modifications to form a modified Hybrid approach denoted as MHPSOBA. This MHPSOBA was validated using IEEE 30-bus test system to solve ORPD problem and the results show that the HPSOBA algorithm outperforms the modified version (MHPSOBA).
Electrical and Mining Engineering
M. Tech. (Electrical Engineering)

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36

Kung, Hsi-chia, and 龔錫家. "Study on Optimal Demand Dispatch Platform Based on a Power Supervisory Control System." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/223dpe.

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Анотація:

碩士
國立臺灣科技大學
電機工程系
95
Due to the rapid increasing of energy price, the importance of electricity supervisory control and demand side management will get more and more attention. For the university campus, traditional electricity management systems only takes the whole campus as a single user. The individual department doesn’t have incentives to encourage its self energy reduction. Besides, the electricity bill sharing mechanism usually doesn’t take the over-demand charge into consideration. In this thesis, an optimal power demand dispatch method based on the market-oriented programming technique is developed. And its application platform based on a campus power supervisory control system is also presented. The research consists of establishing an integrated electricity power supervisory control system, modeling of power usage pattern for campus departments, and development of the optimal demand dispatch method. Through this research, the feasibility of switching campus power management system from central control to distributed control is also investigated. In the future, when the utility company deploys the demand response management, the optimal demand dispatch method can also be applied to multi-user demand dispatch applications.

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37

Lin, Yi-Hsiang, and 林意祥. "Application of Quantum Genetic Algorithm for Optimal Reactive Power Dispatch of Transmission Systems." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/przvsg.

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Анотація:

碩士
國立臺北科技大學
電機工程系研究所
101
Reactive loads in a power system can cause phase shifts for voltages and currents, leading to voltages drop and power loss in power system. Therefore, reactive power dispatch for power system operation and planning purposes is a very important issue. This thesis proposes a new method which applies Quantum Genetic Algorithm (QGA), and uses power flow to reactive power optimization dispatch for the transmission system. Keeping each of the power system load bus voltage in a reasonable range, and minimizing loss of effective power transmission line are the major tasks for the power system stability. The Quantum Genetic Algorithm is a new optimization technique which uses the coding method of quantum probability vector, and also uses the quantum bit and quantum superposition at the same time. The superposition can let it express more states. The probability expression characteristic can express the solution state by certain probability. It can enforce the ability of reaching optimal solution. This thesis simulates the proposed method on IEEE 30-bus system and IEEE 57-bus system. The dispatch solutions are then compared with their counterparts obtained by Genetic Algorithm (GA). Results show that the proposed method obtains the best solution in reducing real power loss and securing voltage stability. The proposed method can therefore be expected to render the dispatch under a safer, faster, and cheaper environment.

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38

Yu, Chao-Tung, and 余兆東. "Optimal Active-Reactive Power Dispatch Using a Non-dominated Sorting Genetic Algorithm II." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/rdnqdg.

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Анотація:

碩士
國立臺北科技大學
電機工程系研究所
102
The thesis using the multi-objective optimization algorithm to solve the optimal active-reactive power dispatch problem in power system. There are many research about reactive power dispatch and economic dispatch with different evolution algorithm had been discussed individually. The thesis integrates both of them by multi-objective optimization algorithm. The object is to obtain less transmission loss and minimum cost by non-dominated solutions at same time. The hardest part of the multi-objective function is to evaluate the value of the fitness. Therefore, has been developed in the thesis method which is able to process non-dominated set to solve the problem by non-dominated sorting genetic algorithm II (NSGA-II). The method also can obtain the optimal solution in all of object functions, and be validated by the IEEE 30-bus system.

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39

Lee, Hang-Sheng, and 李亨聲. "Optimal Reactive Power Dispatch of Transmission Systems UsingGenetic Algorithm and Artificial Neural Networks." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/b62732.

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Анотація:

碩士
國立臺北科技大學
電機工程系所
93
This thesis aims to do the optimal reactive power dispatch of transmission systems. The purpose is to assist dispatch persons to do more correct, economic, and secure dispatch. The dispatch of reactive power is important and difficult to do. Nowadays, the dispatches are almost from operators'' experiences. The compensators of over-voltage or under-voltage are used. However, the large amount of underground cables are built to power systems, the dynamic and steady-state stability is different from those before the Sixth transmission systems. The assistant from optimal reactive power dispatch is an important thing. The assistant from optimal reactive power dispatch is an important thing. This paper is proposed genetic algorithm to do an optimal shunt capacity dispatch of a transmission system. To modify the bus voltage to reasonable margin, avoid the risk of a voltage collapse. For the dispatch, the artificial neural network is applied to learn the dispatches from optimal methods by GA, a data-reduction skill was used by principal component analysis. It can decrease the number of input and increase the speed of the artificial neural network. Simulation results show that the proposed algorithm obtains the good performances on the transmission system.

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40

Kuo, Tzu-Hsiang, and 郭子祥. "Study of the Optimal Reactive Power Dispatch for Wind Power Systems by using Charged System Search Algorithm." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/wrn977.

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Анотація:

碩士
國立臺北科技大學
電機工程系所
102
Problems on reactive power and voltage control are significant for power systems. Suitable adjustment can not only reduce active power loss, but improve voltage stability so as to maintain a stable operation. Traditional reactive power dispatch methods use the adjustment of generator terminal voltage, load taps of transformers in substations, and reactive power compensation devices to control voltage and enhance the supply quality. Traditional systems only considered the effect of load variations on the system voltage and reactive power, and associated technologies and theories are mature. However, in modern power systems, reactive power and voltage control problems would suffer from new challenge owing to the introduction of smart grids and renewable energy. Renewable energy posses high uncertainty, so the variation of its power output is high, leading to more complicated solutions for the voltage control. Additionally, the control of power converters in renewable energy would have an effect on its output characteristics. This study will describe the uncertainty of renewable energy by random variables, and analyze the voltage control problems in renewable energy systems by using probability load flows and optimal algorithms. This project uses the Charged System Search (CSS), one of the optimal algorithms, to solve the reactive power dispatch. It is a multi-agent-based method, which regards the agent as the charged particle (CP). Each CP affects other CPs based on the fitness values and distance, search for the optimal solutions by calculating the attractive force to adjust locations, and verifying its efficiency on basic functions and industry problems. The objective function of this study is to minimize the transmission loss with satisfying all of the system constraints, and sets the terminal voltage of generators, tap setting of transformers, and capacitors as control variables to adjust the system voltage. The initial study has proved the feasibility of the proposed method by using the IEEE 30- bus simulation. Next, this study will consider the high wind power penetration system in Penghu. This study will discuss the optimal reactive power dispatch taking renewable energy uncertainty and probability load flow into account.

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41

Jr, Melanio Pech, and 米蘭諾. "Optimal Dispatch with Minimal Power Transmission Loss Using a Novel Neighbor-Influenced Particle Swarm." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/73936340876016011109.

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Анотація:

碩士
國立清華大學
資訊系統與應用研究所
100
As a swarm intelligent technique, particle swam optimization (PSO) is inherently an evolutionary algorithm that simulates the animal collective behaviors. Since each individual has a different experience based on its position, each particle produces its own movement based on these experiences. The original PSO lacks deeper interaction between individuals at a local level. This implementation of PSO will explore the influence that individuals in its neighborhood have on its search and how it can improve on the capabilities of PSO. Therefore, in this study, a variation will be added to the current PSO technique and applied to Economic Dispatch (ED) problem. ED is an integral component in planning and operation of power systems, because it results in the most cost-efficient method of power delivery while serving the demand. In solving ED there are also other considerations such as power loss that play a large role in cost. More recently, evolutionary algorithms have replaced conventional methods of solving these power system problems. They require less computation and are also very useful in large non-linear problems.

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42

Wang, Jia-ching, and 王嘉慶. "Multi-Objective Optimal Active/Reactive Power Dispatch with Considering Load and Wind Generation Uncertainties." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/50319574254348538928.

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Анотація:

碩士
國立雲林科技大學
電機工程系碩士班
102
There are two parts of problem discussed in this thesis. The first part is multi-objective optimal reactive power dispatch problem. In this problem, the optimal solution is found under the condition which the active power of power generators of PV buses are assumed to be known and fixed. By controlling the load tap changer of transformers, reactive power output of capacitors, and voltage of slack bus and PV buses, the loss of transmission lines and the voltage deviation of load buses can be reduced. To make less cost of power generation, the second part that includes optimal active power dispatch and wind energy system. This problem also considers uncertainties which exist in practical load demands and wind speed. In optimal active power dispatch problem, the loss coefficients of transmission lines and control variables which are dispatched by multi-objective optimal reactive power dispatch are fixed. The B-coefficients based on economic dispatch are used to obtain active power of power generators for active power dispatch solution in order to make less cost of power generation. This thesis presents enhanced firefly algorithm with local random search to multi-objective optimal active and reactive power dispatch with considering load and wind generation uncertainties problem. This algorithm is based on firefly algorithm which the update formula and parameters are modified and the mutation strategy and local random search are utilized to enhance the capabilities of exploring and searching. So the proposed algorithm can converge fast and the solution can avoid trapping in local minimum. Furthermore, in order to deal with the multi-objective problem and the linguistic expression such as “as little as possible”, the fuzzy theory is employed to establish the fuzzy membership functions. To demonstrate the effectiveness of the proposed method for solving multi-objective optimal reactive power dispatch problem and multi-objective optimal active and reactive power dispatch with considering load and wind generation uncertainties problem, the test systems have been applied and the results of the proposed method are compared with those of other algorithms. The results show that the proposed method can get better solution.

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43

Wu, Hung-chen, and 吳鴻辰. "Optimal Power Dispatch and CCHP Assessment of Microgrid System Using Improved Bee Swarm Optimization." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/56261925753739047305.

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Анотація:

碩士
國立中山大學
電機工程學系研究所
103
Under the guidance of international energy event occurred and international agreements, so Energy Saving and Carbon Reduction have already become an important issue in every county. However, the advances in green power not only provided alternative programs, but also reduced environmental pollution when using traditional way to produce energy. As increasing those unstable supply of green power. It must do some impact on traditional power grid. Such as power quality, system reliability, cost of power, etc. Therefore a microgrid which can quick react and dispatch the power demand is taken seriously gradually. How to build a microgrid with quick reaction and enhance power efficiency is an important issue currently. This thesis combined microturbines, wind power, solar power, power storage system, and combined cooling, heating and power(CCHP) to form a microgrid system. Then applying this design into Penghu power system, and reach the function of demand response by power storage system. For minimum cost of generating power this objective. Using combine fuzzy rule into Bee Swarm Optimization (BSO) to solve the problem of generation unit commitment (UC) and economic dispatch(ED). The UC and ED problem must satisfy the constraints of load demand, generating limits, ramp rate limits, and also the minimum up/down time of generators, and capacity of power storage system, etc. For avoid the local optimality problem, this thesis proposed the utilization of combined Probability Selection Fuzzy Rule into Self-Adaption Enhanced Bee Swarm Optimization (SAEBSO) method, which can quickly reach the optimal solution with better performance and accuracy.

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44

LIN, CHIH-CHIANG, and 林志強. "Optimal of Natural Gas Power Plant Dispatch Model - Considering Both Environmental and Economic Factors." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/r82dbk.

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碩士
國立中央大學
環境工程研究所在職專班
103
Due to the concerns of climate change and the rise of environmental protection consciousness, operation of electricity-generation system should take economics and environmental protection into account to achieve better overall competitiveness and sustainable management. This thesis proposes an optimal dispatch model by considering fuel consumption and environmental factors including CO2 and NOx emissions from a natural gas power plant. At first, a mathematical model considering the cost of fuel, CO2 and NOx emission was constructed by compiling the information collected during efficiency testing. The output pf this model is a continuous polynomial function. Next, it uses Lagrange Multiplier Method and Particle Swarm Optimization with less parameters and higher convergence speed to optimize the mathematical mode by obtaining the minimum fuel cost or minimum pollutant emissions. The single objective dispatch mode is then further developd to take economics and environmental protection into account and works as a dual-objective compromise method. The results indicate that analysis of pollutants emitted from each unit can be regarded as a strategic decision parameter of gas turbine combustion tuning. In addition to fixed load analysis, the concept of minimizing fuel cost and pollutant emissions can be adopted for power dispatching by considing actual load demand. The results indicate that optimization of fuel cost as the dispatching objective can reduce the daily fuel cost by seven hundred ninety thousand NT dollars (equivalent to rise up 0.51% of efficiency), CO2 emission is reduced by 1018.3 ton (3.88%), and NOx emission is reduced by 171.4 kg (1.42%). On the other hand, optimization with NOx emission as the daily dispatching objective can reduce daily NOx emission by 536.7 kg (4.44%) and decrease fuel cost by five hundred and six thousand NT dollars (equivalent to 0.37% of efficiency increase) and reduce CO2 emission by 888.8 ton (3.39%). Furthermore, optimization with CO2 emission as the dispatching objective would reduce the daily CO2 emission by 1538.9 ton (5.86%), but fuel cost is increased by two hundred eighty-five thousand NT dollars (equivalent to 0.21% of efficiency reduction) and NOx emission is increased by 1738 kg (14.37%). Therefore, the decision maker can take these results and draw up the operation dispatching strategy by considering actual load demand to achieve the best power dispatch mode by considering both economic and environmental factors.

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45

Soroush, Milad. "Accuracies of Optimal Transmission Switching Heuristics Based on Exact and Approximate Power Flow Equations." Thesis, 2013. http://hdl.handle.net/10012/7584.

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Optimal transmission switching (OTS) enables us to remove selected transmission lines from service as a cost reduction method. A mixed integer programming (MIP) model has been proposed to solve the OTS problem based on the direct current optimal power flow (DCOPF) approximation. Previous studies indicated computational issues regarding the OTS problem and the need for a more accurate model. In order to resolve computational issues, especially in large real systems, the MIP model has been followed by some heuristics to find good, near optimal, solutions in a reasonable time. The line removal recommendations based on DCOPF approximations may result in poor choices to remove from service. We assess the quality of line removal recommendations that rely on DCOPF-based heuristics, by estimating actual cost reduction with the exact alternating current optimal power flow (ACOPF) model, using the IEEE 118-bus test system. We also define an ACOPF-based line-ranking procedure and compare the quality of its recommendations to those of a previously published DCOPF-based procedure. For the 118-bus system, the DCOPF-based line ranking produces poor quality results, especially when demand and congestion are very high, while the ACOPF-based heuristic produces very good quality recommendations for line removals, at the expense of much longer computation times. There is a need for approximations to the ACOPF that are accurate enough to produce good results for OTS heuristics, but fast enough for practical use for OTS decisions.

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46

Li, Xiaoguang. "Estimating Wind Forecast Errors and Quantifying Its Impact on System Operations Subject to Optimal Dispatch." Thesis, 2011. http://hdl.handle.net/1807/31312.

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Wind power is being added to the supply mix of numerous jurisdictions, and an increasing level of uncertainties will be the new reality for many system operators. Accurately estimating these uncertainties and properly analyzing their effects will be very important to the reliable operation of the grid. A method is proposed to use historical wind speed, power, and forecast data to estimate the potential future forecast errors. The method uses the weather conditions and ramp events to improve the accuracy of the estimation. A bilevel programming technique is proposed to quantify the effects of the estimated uncertainties. It improves upon existing methods by modeling the transmission network and the re-dispatch of the generators by operators. The technique is tested with multiple systems to illustrate the feasibility of using this technique to alert system operators to potential problems during operation.

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47

Caballero, Renzo. "Stochastic Optimal Control of Renewable Energy." Thesis, 2019. http://hdl.handle.net/10754/655846.

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Uruguay is a pioneer in the use of renewable sources of energy and can usually satisfy its total demand from renewable sources. Control and optimization of the system is complicated by half of the installed power - wind and solar sources - be- ing non-controllable with high uncertainty and variability. In this work we present a novel optimization technique for efficient use of the production facilities. The dy- namical system is stochastic, and we deal with its non-Markovian dynamics through a Lagrangian relaxation. Continuous-time optimal control and value function are found from the solution to a sequence of Hamilton-Jacobi-Bellman partial differential equations associated with the system. We introduce a monotone scheme to avoid spurious oscillations in the numerical solution and apply the technique to a number of examples taken from the Uruguayan grid. We use parallelization and change of variables to reduce the computational times. Finally, we study the usefulness of extra system storage capacity offered by batteries.

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48

Farhat, Ibrahim A. "Economic and Economic-Emission Operation of All-Thermal and Hydro-Thermal Power Generation Systems Using Bacterial Foraging Optimization." 2012. http://hdl.handle.net/10222/14865.

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Electric power is a basic requirement for present day life and its various economic sectors. To satisfy the ever-increasing needs for electricity, the number of generating units, transmission lines and distribution systems is rising steadily. In addition, electric power systems are among the most complex industrial systems of the modern age. Beside complexity, the generation of electric power is a main source of gaseous emissions and pollutants. The planning and operation of electric power systems must be done in a way that the load demand is met reliably, cost-effectively and in an environmentally responsible manner. Practitioners strive to achieve these goals for successful planning and operations utilizing various optimization tools. It is clear that the objectives to be satisfied are mostly conflicting. In particular, minimizing the fuel cost and the gaseous emissions are two conflicting and non-commensurate objectives. Therefore, multi-objective optimization techniques are employed to obtain trade-off relationships between these incompatible objective functions in order to help decision makers take proper decisions. In this thesis, two main power system operation problems are addressed. These are the economic load dispatch (ED) and the short-term hydro-thermal generation scheduling (STHTS). They are treated first as single-objective optimization problems then they are tackled as multi-objective ones considering the environmental aspects. These problems, single and multi-objective, are nonlinear non-convex constrained optimization problems with high-dimensional search spaces. This makes them a real challenge for any optimization technique. To obtain the optimal or close to optimal solutions, a modified bacterial foraging algorithm is proposed, developed and successfully applied. The bacterial foraging algorithm is a metaheuristic non-calculus-based optimization technique. The proposed algorithm is validated using diverse benchmark optimization examples before implementing it to solve the problems of this thesis. Various practical constraints are considered in the different cases of each problem. These include transmission losses, valve-point effects for both the ED and the STHTS problems and water availability and reservoir configurations for the STHTS problem. In all cases the optimal or near-optimal solution is obtained. For the multi-objective optimization cases, the Pareto optimal solution set that shows the trade-off relationship between the conflicting objectives is successfully captured.

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49

(10653461), Veronica R. Bosquezfoti. "Distributed Optimization Algorithms for Inter-regional Coordination of Electricity Markets." Thesis, 2021.

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In the US, seven regional transmission organizations (RTOs) operate wholesale electricity markets within three largely independent transmission systems, the largest of which includes five RTO regions and many vertically integrated utilities.

RTOs operate a day-ahead and a real-time market. In the day-ahead market, generation and demand-side resources are optimally scheduled based on bids and offers for the next day. Those schedules are adjusted according to actual operating conditions in the real-time market. Both markets involve a unit commitment calculation, a mixed integer program that determines which generators will be online, and an economic dispatch calculation, an optimization determines the output of each online generator for every interval and calculates locational marginal prices (LMPs).

The use of LMPs for the management of congestion in RTO transmission systems has brought efficiency and transparency to the operation of electric power systems and provides price signals that highlight the need for investment in transmission and generation. Through this work, we aim to extend these efficiency and transparency gains to the coordination across RTOs. Existing market-based inter-regional coordination schemes are limited to incremental changes in real-time markets.

We propose a multi-regional unit-commitment that enables coordination in the day-ahead timeframe by applying a distributed approach to approximate a system-wide optimal commitment and dispatch while allowing each region to largely maintain their own rules, model only internal transmission up to the boundary, and keep sensitive financial information confidential. A heuristic algorithm based on an extension of the alternating directions method of multipliers (ADMM) for the mixed integer program is applied to the unit commitment.

The proposed coordinated solution was simulated and compared to the ideal single-market scenario and to a representation of the current uncoordinated solution, achieving at least 58% of the maximum potential savings, which, in terms of the annual cost of electric generation in the US, could add up to nearly $7 billion per year. In addition to the coordinated day-ahead solution, we develop a distributed solution for financial transmission rights (FTR) auctions with minimal information sharing across RTOs that constitutes the first known work to provide a viable option for market participants to seamlessly hedge price variability exposure on cross-border transactions.

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50

Powell, Kody Merlin. "Dynamic optimization of energy systems with thermal energy storage." 2013. http://hdl.handle.net/2152/21590.

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Thermal energy storage (TES), the storage of heat or cooling, is a cost-effective energy storage technology that can greatly enhance the performance of the energy systems with which it interacts. TES acts as a buffer between transient supply and demand of energy. In solar thermal systems, TES enables the power output of the plant to be effectively regulated, despite fluctuating solar irradiance. In district energy systems, TES can be used to shift loads, allowing the system to avoid or take advantage of peak energy prices. The benefit of TES, however, can be significantly enhanced by dynamically optimizing the complete energy system. The ability of TES to shift loads gives the system newfound degrees of freedom which can be exploited to yield optimal performance. In the hybrid solar thermal/fossil fuel system explored in this work, the use of TES enables the system to extract nearly 50% more solar energy when the system is optimized. This requires relaxing some constraints, such as fixed temperature and power control, and dynamically optimizing the over a one-day time horizon. In a district cooling system, TES can help equipment to run more efficiently, by shifting cooling loads, not only between chillers, but temporally, allowing the system to take advantage of the most efficient times for running this equipment. This work also highlights the use of TES in a district energy system, where heat, cooling and electrical power are generated from central locations. Shifting the cooling load frees up electrical generation capacity, which is used to sell power to the grid at peak prices. The combination of optimization, TES, and participation in the electricity market yields a 16% cost savings. The problems encountered in this work require modeling a diverse range of systems including the TES, the solar power plant, boilers, gas and steam turbines, heat recovery equipment, chillers, and pumps. These problems also require novel solution methods that are efficient and effective at obtaining workable solutions. A simultaneous solution method is used for optimizing the solar power plant, while a static/dynamic decoupling method is used for the district energy system.
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