Дисертації з теми "LOAD DISPATCH"

Direct Load Control (DLC) -- the direct control of customer loads by an electric utility for the economic and reliable operation of the power system, is an important and active element of Load Management (LM). Currently attention has focussed on the integration of DLC into system operations. However, as yet, DLC is regarded as a discretionary resource to be used by the system operator based on informed judgment. The integration process has therefore, concentrated on improving the informational inputs to the operator. This dissertation extends the integration from that of a discretionary resource to a dispatchable system resource. The concept of the dynamic dispatch of DLC is formulated and defined to be an online evaluation and utilization of DLC for optimum benefit to the utility, as system conditions change. The concept envisages the use of DLC in an automated mode and coordinated with other system resources for optimum benefit. An important and integral part of the research effort is the development of a cost characterization of DLC. A closed form solution, using a dynamic programming framework, has been developed to estimate the costs of DLC dispatch. The derivation takes into account all operational constraints on the utilization of DLC -- payback characteristics, maximum on-times and minimum recovery times. The cost, defined as the difference in the fuel costs with and without DLC dispatch, were found to be dependent on the cost characteristics of the online generators and the load shape impacts of DLC dispatch. The dynamic dispatch concept is concretized by a power system operations model which incorporates DLC dispatch for fuel cost minimization and peak load shaving. The two modes are toggled by the dispatch algorithm as system conditions change. Results from the model are presented for several combinations of system conditions and DLC system parameters.
Ph. D.

There are different methods to implement demand management. In this thesis, a Demand Side Frequency Droop is proposed to calculate the require power reduction. Moreover, Demand Dispatch (DD) can provide ancillary service to the grid and maintains the power system frequency. Besides, to improve the operation of DD, the renewable resources and the storage devices are integrated to the DD. The proposed methods in this thesis have been validated through PSCAD software simulation and MATLAB.

The Economic Load Dispatch (ELD) problem is an optimisation task concerned with how electricity generating stations can meet their customers’ demands while minimising under/over-generation, and minimising the operational costs of running the generating units. In the conventional or Static Economic Load Dispatch (SELD), an optimal solution is sought in terms of how much power to produce from each of the individual generating units at the power station, while meeting (predicted) customers’ load demands. With the inclusion of a more realistic dynamic view of demand over time and associated constraints, the Dynamic Economic Load Dispatch (DELD) problem is an extension of the SELD, and aims at determining the optimal power generation schedule on a regular basis, revising the power system configuration (subject to constraints) at intervals during the day as demand patterns change. Both the SELD and DELD have been investigated in the recent literature with modern heuristic optimisation approaches providing excellent results in comparison with classical techniques. However, these problems are defined under the assumption of a regulated electricity market, where utilities tend to share their generating resources so as to minimise the total cost of supplying the demanded load. Currently, the electricity distribution scene is progressing towards a restructured, liberalised and competitive market. In this market the utility companies are privatised, and naturally compete with each other to increase their profits, while they also engage in bidding transactions with their customers. This formulation is referred to as: Bid-Based Dynamic Economic Load Dispatch (BBDELD). This thesis proposes a Smart Evolutionary Algorithm (SEA), which combines a standard evolutionary algorithm with a “smart mutation” approach. The so-called ‘smart’ mutation operator focuses mutation on genes contributing most to costs and penalty violations, while obeying operational constraints. We develop specialised versions of SEA for each of the SELD, DELD and BBDELD problems, and show that this approach is superior to previously published approaches in each case. The thesis also applies the approach to a new case study relevant to Nigerian electricity deregulation. Results on this case study indicate that our SEA is able to deal with larger scale energy optimisation tasks.

This thesis investigates the performances of a class of intelligent system algorithms in solving the volt/VAr/THD control problem for large distribution systems. For this purpose, optimal dispatch of Load Tap Changers (LTCs) and Switched Shunt Capacitors in distribution networks with high penetration of nonlinear loads is studied. The optimization problem consists of determination of LTC positions, switched shunt capacitors statuses and proper coordination of these switched elements such that power loss is minimized, voltage profile is improved and total harmonic voltage distortion (THDv) is acceptable while network and operational constraints are satisfied. The Decoupled Harmonic Power Flow (DHPF) is employed for solving the optimization problem. In the next step, an Ant Colony algorithm (ACA) is developed and implemented as an effective and new technique to capture the near global solution of the dispatch problem. Simulation results based on ACA, Genetic Algorithm (GA) and Fuzzy-GA are presented and compared to show the accuracy of the proposed approach.Finally, the application of the developed dispatch ACA in smart grids with Plug-In Electric Vehicle (PEV) charging activities in the residential networks is considered. ACA is first applied on the distribution part of the smart grid to minimize losses, improve voltage profile and mitigate harmonic distortions. Then, a smart load management (SLM) algorithm is proposed and tested for the coordination of PEVs on the residential feeders. The developed algorithm is tested on smart grid configuration with 449 buses consisting of the IEEE 31-bus distribution system connected to a number of low voltage residential feeders populated with PEVs. Simulation results are presented and compared for uncoordinated (random) and SLM coordinated PEV charging considering consumer designated priorities and charging zones.

[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.

The purpose of this research is to identify the need of Smart Grid Technologies in communication between industrial plants with co-generation capability and the electric utilities in providing the most optimum scheme for buying and selling of electricity in such a way that the fuel consumption is minimized, reliability is increased, and time to restore the system is reduced. A typical industrial plant load profile based on statistical mean and variance of industrial plants' load requirement is developed, and used in determining the minimum cost of producing the next megawatt-hours by a typical electric utility. The 24-hour load profile and optimal power flow program are used to simulate the IEEE 39 Bus Test System. The methodology for the use of smart grid technology in fuel saving is documented in the thesis. The results obtained from this research shall be extended to include several industrial plants served by electric utilities in future work by the UNO research team.

Distributed power system is the basic architecture of current power systems and demands close cooperation among the generation, transmission and distribution systems. Excessive greenhouse gas emissions over the last decade have driven a move to a more sustainable energy system. This has involved integrating renewable energy sources like wind and solar power into the distributed generation system. Renewable sources offer more opportunities for end users to participate in the power delivery system and to make this distribution system even more efficient, the novel "Smart Grid" concept has emerged. A Smart Grid: offers a two-way communication between the source and the load; integrates renewable sources into the generation system; and provides reliability and sustainability in the entire power system from generation through to ultimate power consumption. Unreliability in continuous production poses challenges for deploying renewable sources in a real-time power delivery system. Different storage options could address this unreliability issue, but they consume electrical energy and create signifcant costs and carbon emissions. An alternative is using electric vehicles and plug-in electric vehicles, with two-way power transfer capability (Grid-to-Vehicle and Vehicle-to-Grid), as temporary distributed energy storage devices. A perfect fit can be charging the vehicle batteries from the renewable sources and discharging the batteries when the grid needs them the most. This will substantially reduce carbon emissions from both the energy and the transportation sector while enhancing the reliability of using renewables. However, participation of these vehicles into the grid discharge program is understandably limited by the concerns of vehicle owners over the battery lifetime and revenue outcomes. A major challenge is to find ways to make vehicle integration more effective and economic for both the vehicle owners and the utility grid. This research addresses problems such as how to increase the average lifetime of vehicles while discharging to the grid; how to make this two-way power transfer economically viable; how to increase the vehicle participation rate; and how to make the whole system more reliable and sustainable. Different methods and techniques are investigated to successfully integrate the electric vehicles into the power system. This research also investigates the economic benefits of using the vehicle batteries in their second life as energy storage units thus reducing storage energy costs for the grid operators, and creating revenue for the vehicle owners.

In this thesis, we propose novel optimization and spatial queueing models that expand the currently existing methods by allowing multiple servers to be located at the same station and multiple servers to be dispatched to a single call. In particular, a mixed integer linear programming (MILP) model is introduced that determines how to locate and dispatch ambulances such that the coverage level is maximized. The model allows multiple servers to be located at the same station and balances the workload among them while maintaining contiguous first priority response districts. We also propose an extension to the approximate Hypercube queueing model by allowing multi-server dispatches. Computational results suggest that both models are effective in optimizing and analyzing the emergency systems. We also introduce the M[G]/M/s/s queueing model as an extension to the M/M/s/s model which allows for multiple servers to be assigned to a single customer.

Orientador: Edmea Cassia Baptista
Resumo: O problema de Despacho Econômico com Ponto de Válvula é um importante problema relacionado aos Sistemas Elétricos de Potência, que pode ser formulado como um problema de otimização não linear, não convexo e não diferenciável, o que dificulta sua resolução através de métodos exatos. Pode-se observar na literatura que diversos métodos heurísticos são propostos para a resolução do mesmo, os quais são eficientes e com um baixo custo computacional. Uma das desvantagens desses métodos é o tamanho do espaço de busca para realizer tais testes. Pesquisas realizadas apontam que, na grande maioria das vezes, os pontos ótimos para o problema de Despacho Econômico com Ponto de Válvula se encontram em pontos nos quais a função modular, presente na formulação do problema, possui valor nulo, ou estão na região destes e tais pontos são denominados de Pontos Singulares. Neste trabalho, com o bjetivo de propor um método heurístico com espaço de busca reduzido, é proposto um método de Busca Tabu direcionada a Pontos Singulares, o qual utiliza o método de Busta Tabu para percorrer os pontos nos quais a função modular se anula. O método se mostra eficiente para problemas de DEPV de 3, 13 e 40 geradores, com valores próximos aos valores ótimos obtidos por métodos determinísticos e com baixo custo computacional.
Abstract: The problem of Economic Load Dispatch with Valve Point (EDVP) is an important problem related to Electric Power Systems, that can be formulated as a non-linear, non-convex and non-differentiable optimization problem, that difficults resolution through deterministic methods. We can observe in the literature that many heuristic methods are proposed for the resolution of the same, being efficient with a low computational cost. One of the advantages of this methods is the size of the search space necessary to perform the tests. Researches points out that, in most cases, the optimal points for the Economic Load Dispatch with Valve Point problem are at points where the modular function present in the problem formulation has zero value, or in the region thereof, these points are called Singular Points. In this work is proposed, with the objective to propose a heuristic method with the search space reducted, a Tabu Search Directed to Singular Point Search, which uses he tatbu search method to the points in which the modular function cancels out. The method is efficient for resolution of Economic Load Dispatch with Valve Point problems of 3, 13 and 40 generators unities, with values close to optimal obtained by deterministic methods values and low computational cost.
Mestre

The study carried out in this master thesis is part of a larger project led by Energynautics GmbH focusing on renewable energy development in the Caribbean. One of the Caribbean states, consisting of multiple islands, has set a target of 30 % of renewable energy in the power sector by 2030. The first objective of the thesis is to develop optimal generation capacity expansion plans for two different islands of this country, utilizing solar PV generation, which is the only available renewable energy resource. To achieve this objective, three main tasks are identified. The first is the development of an optimal generation capacity expansion plan for the next three years using the optimization tool HOMER Energy. At the beginning only diesel generation is present on the islands. For each study case year, the installed capacity of PV and BESS is optimized and enabling technologies such as curtailment (controllability of PV) and grid-forming inverters are deployed. The second task focuses on the development of a new dispatch strategy, improving on the black box dispatch algorithms built into HOMER. The dispatch strategy minimises the cost of electricity generation and is based on a rolling 48 hours forecasts of the load and PV. It is implemented in MATLAB and linked to HOMER via the built-in MATLAB interface. As HOMER is focused on generation expansion and dispatch and inherently neglects the grid, a grid study is required to assess the stability of the network. This study is the last task of the thesis and is limited to determined steady-state voltage and the asset loading on one of the studied islands through load flow simulations in DIgSILENT PowerFactory. It is shown that there are no major issues even at high PV shares, however, grid performance can be improved if the PV unit is equipped with reactive power capability to control the voltage. A study on the impact of the Q(U)- control and the PQ-capability of the PV and BESS inverters is performed.
Studien som genomförts i detta examensarbete är en del av ett större projekt vilket leds av Energynautics GmbH med fokus på utveckling av förnybar energi i Karibien. En av de Karibiska staterna, bestående av flera öar, har ett mål på 30 % förnybar energi i elkraftssektorn innan 2030. Första syftet med examensarbetet är att utveckla optimala utbyggnadsplaner för produktionskapaciteten för två olika öar i detta land, med användning av solcellsproduktion, vilket är den enda tillgängliga förnybara energikällan. Den första uppgiften är utvecklingen av en optimal utbyggnadsplan för produktionskapaciteten för de kommande tre åren med optimeringsverktyget HOMER Energy. Från början fanns det bara dieselgeneratorer på öarna. För varje studerat år optimeras den installerade kapaciteten av PV och BESS samt aktivering av möjliggörande teknologier som begränsning av PV-produktion och grid-forming växelriktare. Den andra uppgiften fokuserar på utvecklingen av en ny driftsstrategi, förbättring av den basala driftsalgoritm som är inbyggd i HOMER. Driftsstrategin minimerar kostnaden av elproduktionen och är baserad på en 48 timmars prognos av laster och PV. Den är implementerad i MATLAB och kopplad till HOMER via det inbyggda MATLABgränssnittet. Eftersom HOMER fokuserar på produktionsutbyggnad och drift och i praktiken försummar elnätet, krävs en studie av elnätet för att utvärdera stabiliteten av elnätet. Studien av denna sista uppgift i examensarbetet är begränsad till att bestämma spänningen vid jämnviktsläge och den utvärderade lasten på en av de studerade öarna genom belastningsfördelningsberäkning i DIgSILENT PowerFactory. Det visade sig att det inte fanns några stora problem även med stora andelar PV, men elnätets prestanda kan förbättras om PV-omriktarna är utrustade med reaktiv effektstyrning som kontrollerar spänningen. En studie avinverkan från Q(U)-styrning och PQ-kapacitet av PV- och BESS-växelriktare har utförts.

The power system in modern world has grown in complexity of interconnection and power demands. The focus has now shifted to enhancing performance, increasing customer focus, lowering cost, reliability and clean power. In this changed modern word where we face scarcity of energy, with an ever increasing cost of power generation, environmental concerns necessitate some sort of optimum economic dispatch. Particle Swarm Optimization (PSO) is used to allot active power among the generating stations which satisfy the system constraints and thereby minimizes the cost of power generated. The feasibility of this method is analysed for its accuracy and its rate of convergence. The economic load dispatch problem is carried for three and six unit systems using PSO and conventional lagrange method for both cases i.e. neglecting and including transmission line losses. The results of PSO method was compared with that of conventional method and was found to be superior. The convergence characteristics in PSO method were also found both for loss included and loss neglected case. The conventional optimization methods are unable to solve many complex problems due to convergence of local optimum solution. Particle Swarm Optimization (PSO) since its initiation during the last 15 years, has been a great solution to the practical constrained economic load dispatch (ELD) problems. The optimization technique is evolving constantly to provide better and fast results.

碩士
元智大學
資訊管理研究所
91
Optimal planning distribution of power load network reconfiguration has been proposed here. Distribution systems normally need reconfiguration to adapt different load pattern. The proposed methodology mainly focuses on non auto switched distribution system. For the long term planning, a new algorithm has been proposed by using system simulation to overcome the uncertainty of the power need next year. Once the future load has been identified in distribution system, the power dispatch in substation level can be optimized. The result of proposed approach is applied to support on the planning of distribution network in Taiwan.

The modern power system around the world has grown in complexity of interconnection and power demand. The focus has shifted towards enhanced performance, increased customer focus, low cost, reliable and clean power. In this changed perspective, scarcity of energy resources, increasing power generation cost, environmental concern necessitates optimal economic dispatch. In reality power stations neither are at equal distances from load nor have similar fuel cost functions. Hence for providing cheaper power, load has to be distributed among various power stations in a way which results in lowest cost for generation. Practical economic dispatch (ED) problems have highly non-linear objective function with rigid equality and inequality constraints. Particle swarm optimization (PSO) is applied to allot the active power among the generating stations satisfying the system constraints and minimizing the cost of power generated. The viability of the method is analyzed for its accuracy and rate of convergence. The economic load dispatch problem is solved for three and six unit system using PSO and conventional method for both cases of neglecting and including transmission losses. The results of PSO method were compared with conventional method and were found to be superior. The conventional optimization methods are unable to solve such problems due to local optimum solution convergence. Particle Swarm Optimization (PSO) since its initiation in the last 15 years has been a potential solution to the practical constrained economic load dispatch (ELD) problem. The optimization technique is constantly evolving to provide better and faster results.

In this project, an Improved PSO algorithm has been developed to solve economic load dispatch problem. In the Proposed PSO algorithm, Retardation factor has been introduced to damp out the oscillations as the particle reaches near the global optimum point. This results in faster convergence as well as lesser cost of generation. The proposed algorithm has been implemented on unconstrained mathematical test functions to check the accuracy and convergence of the algorithm. The Proposed PSO algorithm is implemented on IEEE three and six generator thermal power plants. In the case of mathematical test functions, the comparison is done in terms of the number of iterations performed and the number of function evaluations. In case of an economic load dispatch problem, the comparison is done in terms of fuel cost of generation also. After comparing results in both cases, it is found that the proposed PSO algorithm gives more accurate results in less number of iterations. Number of iterations, number of function evaluations, and time consumed have been measured for different values of retardation factors. Best retardation is the one for which function gets optimized in minimum number of iterations. MATLAB simulation is done to solve the economic load dispatch problem and mathematical test function using Proposed algorithm and Basic particle swarm optimization algorithm.

M.TECH
In general, a large scale power system possesses multiple objectives to be achieved. The ideal power system operation is achieved when various objectives like cost of generation, system transmission loss, environmental pollution, security etc. are simultaneously attained with minimum values. Since these objectives are conflicting in nature, it is impossible to achieve the ideal power system operation. In this thesis work, three objectives of Multiobjective Economic Load Dispatch (MOELD) problem-cost of generation, system transmission loss and environmental pollution- are considered. The MOELD problem is formulated as a multiobjective optimization problem using weighting method and a number of noninferior solutions are generated in 3D space. The optimal power system operation is attained by Ideal Distance Minimization method. This method employs the concept of an ‘Ideal Point’ (IP) to scalarize the problems having multiple objectives and it minimizes the Euclidean distance between IP and the set of noninferior solutions. This method has been applied to IEEE 30 bus system.

The power flow in a highly interconnected grid is an ancient problem for an electrical engineer. With the advent of time of course, this issue has been tackled with greater accuracy and efficiency. Now the load flow and subsequent concerns are taken care by simulations in a minute. The next big obstacle is that of Economic Load Dispatch. In ELD, the unit commitment of each generator is taken into consideration to have adequate margin for reserve at any time. The second issue with ELD is with allocating the total generation to the individual generators in such a way that the total cost of generation at any time is at a minimum. In this project, the optimum cost of generation problem has been looked into with a distributed slack bus algorithm. In ordinary line flow analysis, the slack bus is asked to carry the entire residual burden of the system. In the proposed method, the burden on slack bus shall be eliminated and still maintain the equal incremental cost criteria. A new concept called Participation factor shall be used to achieve the same as the total loss of the system at the end of iteration shall get divided among all the generator buses. Two distinct bus networks were used as case studies and the results are compared and analysed to verify the usefulness of the proposed technique.

The economic load dispatch is an integral part of power system. The leading purpose is to minimize the fuel cost of power plant without violating any system constraints. Many conventional methods are applied to elucidate economic load dispatch through mathematical programming and optimization technique. The popular traditional method is the lambda-iteration method. Many heuristic approaches applied to the ELD problems such as dynamic programming, evolutionary programming, genetic algorithm, artificial intelligence, particle swarm optimization etc. In this study, two cases are taken named as three unit system and six unit system. The fuel cost for both systems compared using conventional lambda-iteration method and PSO method. These calculations are done for without transmission losses as well as with transmission losses. In the end, the fuel cost for both methods compared to analyse the better one from them. All the analyses are executed in MATLAB environment.

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.

The economic load dispatch plays an important role in the operation of power system, and several models by using different techniques have been used to solve these problems. Several traditional approaches, like lambda-iteration and gradient method are utilized to find out the optimal solution of non-linear problem. More recently, the soft computing techniques have received more attention and were used in a number of successful and practical applications. The purpose of this work is to find out the advantages of application of the evolutionary computing technique and Particle Swarm Optimization (PSO) in particular to the economic load dispatch problem. Here, an attempt has been made to find out the minimum cost by using PSO using the data of three and six generating units. In this work, data has been taken from the published work in which loss coefficients are also given with the max-min power limit and cost function. All the techniques are implemented in MATLAB environment. PSO is applied to find out the minimum cost for different power demand which is finally compared with both lambda- iteration method and GA technique. When the results are compared with the traditional technique and GA, PSO seems to give a better result with better convergence characteristic.

The power flow analysis in a highly interconnected grid is a big problem for an electrical engineer. The next big obstacle is that of Economic Dispatch at the load side. The issue with Economic Load Dispatch (ELD) is with allocating the total generation to the individual generators in such a way that the total cost of generation at any time is at a minimum. In this project, the optimal cost of generation has been analyzed with a distributed slack bus model. In ordinary load flow method, the slack bus is bound to carry the entire extra burden of the system. In the proposed technique, the burden on slack bus shall be reduced and still maintain the equal incremental cost criteria. A new term called Participation factor shall be utilized to achieve the same as the total loss of the system at the end of iteration shall get distributed among all the generating units. Finally practical bus network problems shall be taken as case study and results shall be analyzed and compared with the existing ELD scheme to verify the usefulness of the proposed technique.

The Economic power dispatch problem is one of the most important problems to be solved in the operations of power system. It is basically a non-linear optimization problem having linear and non-linear equality and inequality constraints. This is a real time problem for properly allocating the real power output among the committed generators such that fuel cost is minimized while the demand requirement is met and the constraints imposed are satisfied. The main objective of this thesis is to study the performance of Selection Based Particle Swarm Optimization (SBPSO) technique to solve economic load dispatch problems. SBPSO performance is compared with the Basic Particle Swarm Optimization (BPSO). In this thesis, selection procedure of size of particles in BPSO is changed to new selection criteria. This selection is based on the function value of the particles. The size of particles is decreased in each iteration by some decrement factor. In the 1st iteration the size of particle is same as initial size and in subsequent iteration the size of particles decreases by some decrement factor for the remaining evolution. This decrement of particles in each iteration is being done in a way that particle for which the value of function is less will be selected and the particles with higher function values will get discarded. In this thesis, the particle size goes on decreasing in each iteration which will become very less than the minimum number of particles required to optimize a function. Therefore, the minimum number of particles required to optimize a function has been fixed and for subsequent iteration the size of particles will be the minimum value for the optimization. A MATLAB program has been developed for SELECTION BASED PARTICLE SWARM OPTIMIZATION to Economic Load Dispatch problem. Program is tested on IEEE 5, 14 and 30 bus system and the results are compared with Basic PSO technique.

碩士
逢甲大學
電機工程所
93
The load of distribution system is grouped into nine categories and composed of three client users (housing users, commercial users, and manufacturing users), and the distribution system is formed of client users, transformer (users of high voltage), switching, feeder, main transformers .As a result, it is the client users that influence the capacity of the distribution system, and the properties of client users’ consuming electricity are the principal part of this thesis. In this thesis, the daily operation data of feeders'' and group the client users'' data，into three categories to estimate and build the standardized model of all types of client users. Using the model to analyze the load of feeder, we can deploy workers more efficiently.

博士
國立高雄應用科技大學
電機工程系
99
The aim of this research is to study the load management (LM) and economic dispatch decision for the Taiwanese industries through Cat Swarm Optimization (CSO) algorithm. CSO algorithm can be proposed to select optimal demand contract and drop the basic electricity cost. Results indicated that the CSO is superior to Particle Swarm Optimization (PSO) in the fast convergence and better performance to find the global best solution, considering the same iteration time. Also the CSO algorithm is highly helpful to Taiwanese industries on the optimal LM decision. From the view point of demand side management, this research is to apply SCADA system and a feasible LM options for the Taiwanese industries to reduce the power cost. Also this study refers to provide decision-makers with useful LM strategies as reference. Finally, it is suggested that future research might explore in nonlinear optimization problem through CSO algorithm, as well as in engineering and power system.

This project presents an efficient and reliable Particle Swarm Optimization (PSO) method for the Economic load dispatch (ELD) problems which is considered as one of the complex problems to be tackled. The PSO techniques have drawn much attention from the power system community and been successfully applied in many complex optimization problems in power systems. The PSO method was developed through the simulation of a simplified social system and has been found to be robust in solving continuous nonlinear optimization problems in terms of accuracy of the solution and computation time and it can out perform other algorithms. In this project, the proposed algorithm is applied for the ELD of three unit thermal plant systems.

ELD or economic load dispatch is a crucial aspect in any practical power network. Economic load dispatch is the technique whereby the active power outputs are allocated to generator units in the most cost-effective way in compliance with all constraints of the network. The traditional methods for solving ELD include Lambda-Iterative Technique, Newton-Raphson Method, Gradient method, etc. All these traditional algorithms need the incremental fuel cost curves of the generators to be increasing monotonically or piece-wise linear. But in practice the input-output characteristics of a generator are highly non-linear leading to a challenging non-convex optimisation problem. Methods like artificial intelligence, DP (dynamic programming), GA (genetic algorithms), and PSO (particle swarm optimisation) solve non-convex optimisation problems in an efficient manner and obtain a fast and near global and optimum solution. In this project ELD problem has been solved using Lambda-Iterative technique, GA (Genetic Algorithms) and PSO (Particle Swarm Optimisation) and the results have been compared. All the analyses have been made in MATLAB environment.

An electric power system consists of several generating stations which cater to the load demands of various regions. The prime function of any generating utility is to optimally schedule the real power output of its generating units to meet any specified real power demand subject to various constraints on the operation of the units and the system. The optimal scheduling of individual generators at the least possible cost is referred to as the economic dispatch or economic load dispatch (ELD) problem. The ELD studies play a vital role in the day­to­day operation of the power system and in formulating economic operating strategies, besides ensuring the stability and security of the system. This thesis work makes an effort to probe deeper into some aspects of the economic load dispatch problem and the underlying mathematical formulations and attempts to come up with generalized algorithms that can effectively handle different types of systems under different operating conditions and, to a certain extent, to try and resolve some aspects hitherto unresolved. The primary focus is on developing efficient computational techniques to solve some Specific types of ELD problems in a simple and systematic manner. In the course of this investigation, we highlight some imperfect assumptions involved in the solutions proposed for the ELD problems for systems with complicated constraints like prohibited operating zones (POZ). We also set forth new concepts and strategies and develop new techniques in this investigation to help resolve some of these incorrect propositions and ambiguities. The first chapter introduces the ELD problem in general and proceeds to discuss the effects of the transmission losses and the presence of POZs on both the scheduling of the generators and the complexity of the ELD analysis. It also provides a brief review of some relevant aspects of the state-of-the-art solution techniques and clearly spells out the motivation for the present work. The second chapter presents a generalized algorithm for solving the ELD problem efficiently. The algorithm is effectively applicable to any system comprising power generating units with any type of well-defined, smooth and monotonic cost functions, besides quadratic cost functions usually considered in conventional algorithms. The proposed method first identifies the units that are forced to operate at their generating limits for any given value of the system demand. Subsequently, it limits the ELD problem to calculating The system's incremental cost of received power and the power output of only those units operating within their normal feasible range. The specific improvement introduced here is the development of an efficient computational scheme for calculating the value of the system incremental cost accurately. In addition to quadratic and higher order polynomial cost functions, the proposed algorithm can easily be generalized to include units with smooth, monotonic, non­ polynomial cost functions. The major advantages of the proposed ELD scheme are its inherent simplicity, scalability, rapid convergence and high computational efficiency. These characteristics are particularly important for real-time online implementation. The results obtained for test cases from the literature and some new ones as well are presented to illustrate the effectiveness of the proposed scheme. The third chapter proposes an algorithm for solving the ELD problem considering power losses in the transmission network. The losses are computed using the transmission loss­ formula A coefficients method suggested by Nanda and Bijwe as an alternative to the conventional B­loss coefficients approach popularized by Kirchmayer. The proposed ELD­with­ Losses scheme builds upon the ELD scheme developed in the second chapter for the lossless case. The specific contribution of the third chapter is the computational approximation suggested for the iterative procedure involving The Newton­Raphson (NR) method with the losses considered, while still retaining the elegant solution scheme developed in the earlier chapter. The results obtained using test cases from the literature are presented to demonstrate the precision and effectiveness of the proposed technique. The fourth chapter presents a novel algorithm for efficiently solving the ELD problem for systems having generators with prohibited operating zones. The proposed ELD­ POZ scheme partitions the no convex solution space into simpler convex intervals in which the ELD scheme developed in the second chapter can be applied directly. The improvisation lies in the optimal ordering­cum­sorting strategy adopted to systematically determine the output levels of the units constrained by POZs and to adjust the output power of the remaining units appropriately. The proposed scheme also recognizes and exactly computes the multiple, equivalent optimal solutions wherever applicable–– another significant contribution of this thesis work. It also seeks to clarify and set right some unintentionally imperfect propositions and assumptions currently prevalent in the literature regarding the formulation and analysis of the ELD problem considering POZs. The results generated for a number of systems using test cases from the literature along with some new ones are presented to clearly illustrate the validity as well as the Simplicity and superiority of the proposed scheme for different types of systems. The final chapter briefly recounts the work done in this thesis work. It also presents a summary of the significant results obtained using the schemes proposed in the earlier chapters, along with the conclusions drawn in support of the validity and superiority of the proposed algorithms. More areas for further investigation and some possible avenues for future applications of the proposed techniques are also indicated.

An electric power system consists of several generating stations which cater to the load demands of various regions. The prime function of any generating utility is to optimally schedule the real power output of its generating units to meet any specified real power demand subject to various constraints on the operation of the units and the system. The optimal scheduling of individual generators at the least possible cost is referred to as the economic dispatch or economic load dispatch (ELD) problem. The ELD studies play a vital role in the day­to­day operation of the power system and in formulating economic operating strategies, besides ensuring the stability and security of the system. This thesis work makes an effort to probe deeper into some aspects of the economic load dispatch problem and the underlying mathematical formulations and attempts to come up with generalized algorithms that can effectively handle different types of systems under different operating conditions and, to a certain extent, to try and resolve some aspects hitherto unresolved. The primary focus is on developing efficient computational techniques to solve some Specific types of ELD problems in a simple and systematic manner. In the course of this investigation, we highlight some imperfect assumptions involved in the solutions proposed for the ELD problems for systems with complicated constraints like prohibited operating zones (POZ). We also set forth new concepts and strategies and develop new techniques in this investigation to help resolve some of these incorrect propositions and ambiguities. The first chapter introduces the ELD problem in general and proceeds to discuss the effects of the transmission losses and the presence of POZs on both the scheduling of the generators and the complexity of the ELD analysis. It also provides a brief review of some relevant aspects of the state-of-the-art solution techniques and clearly spells out the motivation for the present work. The second chapter presents a generalized algorithm for solving the ELD problem efficiently. The algorithm is effectively applicable to any system comprising power generating units with any type of well-defined, smooth and monotonic cost functions, besides quadratic cost functions usually considered in conventional algorithms. The proposed method first identifies the units that are forced to operate at their generating limits for any given value of the system demand. Subsequently, it limits the ELD problem to calculating The system's incremental cost of received power and the power output of only those units operating within their normal feasible range. The specific improvement introduced here is the development of an efficient computational scheme for calculating the value of the system incremental cost accurately. In addition to quadratic and higher order polynomial cost functions, the proposed algorithm can easily be generalized to include units with smooth, monotonic, non­ polynomial cost functions. The major advantages of the proposed ELD scheme are its inherent simplicity, scalability, rapid convergence and high computational efficiency. These characteristics are particularly important for real-time online implementation. The results obtained for test cases from the literature and some new ones as well are presented to illustrate the effectiveness of the proposed scheme. The third chapter proposes an algorithm for solving the ELD problem considering power losses in the transmission network. The losses are computed using the transmission loss­ formula A coefficients method suggested by Nanda and Bijwe as an alternative to the conventional B­loss coefficients approach popularized by Kirchmayer. The proposed ELD­with­ Losses scheme builds upon the ELD scheme developed in the second chapter for the lossless case. The specific contribution of the third chapter is the computational approximation suggested for the iterative procedure involving The Newton­Raphson (NR) method with the losses considered, while still retaining the elegant solution scheme developed in the earlier chapter. The results obtained using test cases from the literature are presented to demonstrate the precision and effectiveness of the proposed technique. The fourth chapter presents a novel algorithm for efficiently solving the ELD problem for systems having generators with prohibited operating zones. The proposed ELD­ POZ scheme partitions the no convex solution space into simpler convex intervals in which the ELD scheme developed in the second chapter can be applied directly. The improvisation lies in the optimal ordering­cum­sorting strategy adopted to systematically determine the output levels of the units constrained by POZs and to adjust the output power of the remaining units appropriately. The proposed scheme also recognizes and exactly computes the multiple, equivalent optimal solutions wherever applicable–– another significant contribution of this thesis work. It also seeks to clarify and set right some unintentionally imperfect propositions and assumptions currently prevalent in the literature regarding the formulation and analysis of the ELD problem considering POZs. The results generated for a number of systems using test cases from the literature along with some new ones are presented to clearly illustrate the validity as well as the Simplicity and superiority of the proposed scheme for different types of systems. The final chapter briefly recounts the work done in this thesis work. It also presents a summary of the significant results obtained using the schemes proposed in the earlier chapters, along with the conclusions drawn in support of the validity and superiority of the proposed algorithms. More areas for further investigation and some possible avenues for future applications of the proposed techniques are also indicated.

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.

In this thesis, two objectives of power systems – cost of generation and system transmission losses has been considered for simultaneous minimization. The Multi-objective Economic Load Dispatch (MELD) problem considering the two objectives has been formulated using weighting method. The non-inferior set has been generated by varying the relative weights of the objectives in a systematic manner and solving the MELD problem as a combinatorial optimization problem by Ant System which is the first Ant colony Optimization technique. Explicit trade-off analysis has been carried out by Maximization of minimum Relative (MMR) Attainments method. The target point of the power system is obtained when the sum of minimum relative attainments are maximum. The proposed method has been implemented on IEEE 5, 14 and 30 bus systems. A MATLAB program has been developed to solve Travelling Salesman Problem of four cities using Evolutionary Computation such as Ant Colony Optimization (ACO). Multi-objective economic load dispatch problem considering cost of generation and system transmission losses has been solved using ACO.
Prof. N.K. Jain & Prof. Uma Nangia

Power system security plays a very vital role along with the transmission capability. The power system security is mostly influenced by several contingencies. The mean of contingency is any outage of transmission line, outage of transformer, outage of generator etc. from the system. Under contingency the system might get into insecure. Determination of system state that is whether the system is working under secure condition or not that can be deal by security analysis. Insecure of the system means all the components in the system are operating out of the specified limits. If the present operating condition is found that system is not in secure condition then the remedy must be taken to protect the system from the violation of specified limits of particular components under contingency. During the contingency the transmission line power flows will get affected and it might cross the maximum power flow limit. So we have to control the power flows in the transmission lines during the contingency. The power flows in the transmission line can be control by rescheduling of the generators in the system. In this work the particle swarm optimization technique has been utilised to reschedule the generators for getting optimum cost. While rescheduling the generators under contingency the power flows in the transmission line will get control and they will come within the specified limits and security will get enhance under contingency.

碩士
國防管理學院
國防資訊研究所
94
Generally speaking, an enterprise network operation cost could be reduced and its performance would be enhanced with a link load balance device. However, there are many algorithms can be used by a link load balance device to handle traffic loading over multiple internet links within an enterprise network. Each algorithm can apply different measurement distances and traffic dispatching schemes to process traffic load balance with different measurement and dispatching cost. Which are the best combinations of measurement distance and traffic dispatching schemes for link load balance algorithms to receive better performance with lower cost? It is an issue needs discuss further. This study tries to discuss which combination of measurement distance and traffic dispatching schemes is more efficient for link load balance algorithms to receive better performance. First, this study tries to understand the operation of a link load balance algorithm with different measurement distances and traffic dispatching schemes. According to the operations of measurement distances and traffic dispatching schemes, a cost analysis of measurement distances and traffic dispatching schemes is discussed in this study. In this study, link load balance emulation environment is implemented to emulate link load balance processes which are handled by different algorithms with different traffic measurement and dispatching schemes. Several most used link load balance algorithms, round robin (RR) and Weighted Least Traffic First (WLTF), with different traffic measurement and dispatching schemes are emulated. By examining the emulated data, an interested summary can be found: the RR and WLTF algorithms can receive better link load balance performance with the lowest measurement and dispatching cost.

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.

碩士
國立高雄科技大學
電子工程系
107
According to the Paris Agreement promulgated by United Nations (UN) in 2015, the targets of reducing greenhouse gas emissions have been set by 120 countries including the United States, and the development of renewable energy has attracted much attention from public. European Union (EU) has also claimed to increase the proportion of various renewable energy sources such as wind power and solar power from 27% to 32% in 2030. However, the deployment of renewable energy is often accompanied by some problems, so that the utilization of renewable energy often fails to meet expectations as well as causes the waste of energy. Moreover, the variation of renewable energy has brought great challenges to the original grid systems. The common methods of generating renewable energy are solar energy, wind power, hydropower, geothermal, etc. Among them, solar power and wind power are the most popular internationally. However, renewable energy has great instability, and it is subject to change the power generation with weather, environment and other factors, which will affect the safety of the power grid. Thus, renewable energy cannot be the base load power. If the load of power grids could be predictable, the time of power dispatching operation can be extended to make the deployment of renewable energy more feasible. The deployment of renewable energy requires “a trustworthy power forecasting and dispatching platform" to manage different types and large number of power generation/storage/electrical devices, and a transport framework to quickly integrate the status information of legacy and modern power plants is needed. In this paper, we propose a Machine-Learning Approach to Predictive Power Load Dispatch for IEC61850-Connected Heterogenous Power Plants, to solve the dispatching problem of next-generation grids based on machine learning. The proposed framework selects reliable features to predict electricity consumption. The IEC61850 protocol published by TC57 is used in this paper to enable a power management and decision-making platform with high reliability, predictive ability, automatic scheduling and scalability, and is more compatible with the transmission network framework of heterogeneous power grid. The power generation and load data sets in northern Taiwan are used as the experimental field. The numeric results show that the power consumption can be predicted accurately, reduce the average error to 2.61%. The information link of the energy storage/electrical device and the automated power dispatching, explore the relationship between the energy storage station and the renewable energy in the power grid, and the power shortage caused by the stable power demand of the energy storage station. This research contributes to the design and the deployment of heterogenous power grids in future.

碩士
國立臺灣科技大學
電機工程系
107
This research proposed a new hybrid algorithm of grey wolf optimization (GWO) integrated with robust learning mechanism to solve the large scale economic load dispatch (ELD) problem. The robust learning grey wolf optimization (RLGWO) algorithm imitate the hunting behavior and social hierarchy of grey wolves in nature and reinforced by robust tolerant based adjust searching direction and opposite based learning. This technique could effectively prevent search agents trapping into local optimum but also generate potential candidate to obtain feasible solutions. Several constraints of power generators such as generation limits, local demand, and valve point loading effect and transmission losses are all considered for practical operations. Five test systems have been used to evaluate the effectiveness and robustness of the proposed algorithm in solving ELD problem. The simulation results distinctly reveal the superiority and feasibility of RLGWO to find the better solution in term of fuel cost and computational efficiency when comparing with previous literatures.

碩士
中原大學
電機工程研究所
107
In recent years, due to the awakening of the sustainable development, our government promotes the allocation and construction of renewable energy. The increasing penetration of the renewable capacity results in the popularity of researching in various studies in power system. Economic dispatch (ED) is one of the important topics. This thesis presents a method based on Consensus Alogorithm for solving economic dispatch in Taipower system considering uncertain loads and renewables. Firstly, establish the consensus algorithm in Taipower system by using Breadth-First Search (BFS) to find agents suitable being leader-agent. Uncertain loads and renewables can be then calculated by using Affine Arithmetic models. The multi-area economic dispatch by using three-layer consensus is solved. In this thesis, the result of solving multi-area economic dispatch in Taipower system by using three-layer consensus is similar to the result of using Lagrange multiplier, but it took much longer time to solve this ED problem because of the decentralized control. There was a comparison of three uncertainty models of loads and renewables which were studied by Affine Arithmetic and Monte Carlo.

碩士
國立交通大學
電信工程系
89
The Internet traffic increases rapidly, especially the World Wide Web traffic. For a Application Service Provider(ASP), there are many users connect with it at the same time. Because the ability of server is limited, it cannot deal with all users' requests at the same time. Then the congestion is happened. The best solution to solve this problem is to increase the number of servers to deal with the users' requests and to duplicate the contents of the server. Because of the cost, the ASP cannot increase the number of servers unlimitedly. Under the condition of limited number of servers, it should dispatch new sessions of users to the server according to load balance of servers to maximize the system capacity and then avoid congestion. In recent years, The intelligent techniques such as fuzzy logic, neural network, ANFIS architecture, have been widely applied to deal with traffic control. Most research results show that the intelligent techniques can have better performance than conventional schemes. Now we have an idea to slove this problem by using fuzzy system. When we know all information of the current state, we may predict the load in the next state in some way. But it is not accuracy. In this thesis, we analyse the system deeply and propose the fuzzy algorithm. The dispatcher depends on the information which is sent periodically by the servers in the server farm to make decisions. This algorithm considers the short term and long term server characteristics to make decisions. This can have better performance than all other conventional algorithms in both request packet loss probability and overall system utilization. Based on the same model, we also propose an ANFIS technique to find the optimum fuzzy solution. The ANFIS technique can derive the best fuzzy rule and membership functions dynamically. And the performance of fuzzy algorithm in request packet loss probability can be further improved.

The objective of an Energy Control Center (ECC) is to ensure secure and economic operation of power system. The challenge to optimize power system operation, while maintaining system security and quality of power supply to customers, is increasing. Growing demand without matching expansion of generation and transmission facilities and more tightly interconnected power systems contribute to the increased complexity of system operation. Rising costs due to inflation and increased environmental concerns has made transmission, as well as generation systems to be operated closure to design limits, with smaller safety margins and hence greater exposure to unsatisfactory operating conditions following a disturbance. Investigations of recent blackouts indicate that the root cause of most of these major power system disturbances is voltage collapse. Information gathered and preliminary analysis, from the most recent blackout incident in North America on 14th August 2003, is pointing the finger on voltage instability due to some unexpected contingency. In this incident, reports indicate that approximately 50 million people were affected interruption from continuous supply for more than 15 hours. Most of the incidents are related to heavily stressed system where large amounts of real and reactive power are transported over long transmission lines while appropriate real and reactive power resources are not available to maintain normal system conditions. Hence, the problem of voltage stability and voltage collapse has become a major concern in power system planning and operation. Reliable operation of large scale electric power networks requires that system voltages and currents stay within design limits. Operation beyond those limits can lead to equipment failures and blackouts. In the last few decades, the problem of reactive power control for improving economy and security of power system operation has received much attention. Generally, the load bus voltages can be maintained within their permissible limits by reallocating reactive power generations in the system. This can be achieved by adjusting transformer taps, generator voltages, and switchable Ar sources. In addition, the system losses can be minimized via redistribution of reactive power in the system. Therefore, the problem of the reactive power dispatch can be optimized to improve the voltage profile and minimize the system losses as well. The Instability in power system could be relieved or at least minimized with the help of most recent developed devices called Flexible AC Transmission System (FACTS) controllers. The use of Flexible AC Transmission System (FACTS) controllers in power transmission system have led to many applications of these controllers not only to improve the stability of the existing power network resources but also provide operating flexibility to the power system. In the past, transmission systems were owned by regulated, vertically integrated utility companies. They have been designed and operated so that conditions in close proximity to security boundaries are not frequently encountered. However, in the new open access environment, operating conditions tend to be much closer to security boundaries, as transmission use is increasing in sudden and unpredictable directions. Transmission unbundling, coupled with other regulatory requirements, has made new transmission facility construction more difficult. In fact, there are numerous technical challenges emerging from the new market structure. There is an acute need for research work in the new market structure, especially in the areas of voltage security, reactive power support and congestion management. In the last few decades more attention was paid to optimal reactive power dispatch. Since the problem of reactive power optimization is non-linear in nature, nonlinear programming methods have been used to solve it. These methods work quite well for small power systems but may develop convergence problems as system size increases. Linear programming techniques with iterative schemes are certainly the most promising tools for solving these types of problems. The thesis presents efficient algorithms with different objectives for reactive power optimization. The approach adopted is an iterative scheme with successive power-flow analysis using decoupled technique, formulation and solution of the linear-programmingproblem with only upper-bound limits on the state variables. Further the thesispresents critical analysis of the three following objectives, Viz., •Minimization of the sum of the squares of the voltage deviations (Vdesired) •Minimization of sum of the squares of the voltage stability L indices (Vstability) •Minimization of real power losses (Ploss) Voltage stability problems normally occur in heavily stressed systems. While the disturbance leading to voltage collapse may be initiated by a variety of causes, the underlying problem is an inherent weakness in the power system. The factors contributing to voltage collapse are the generator reactive power /voltage control limits, load characteristics, characteristics of reactive compensation devices, and the action of the voltage control devices such as transformer On Load Tap Changers (OLTCs). Power system experiences abnormal operating conditions following a disturbance, and subsequently a reduction in the EHV level voltages at load centers will be reflected on the distribution system. The OLTCs of distribution transformers would restore distribution voltages. With each tap change operation, the MW and MVAR loading on the EHV lines would increase, thereby causing great voltage drops in EHV levels and increasing the losses. As a result, with each tap changing operation, the reactive output of generators throughout the system would increase gradually and the generators may hit their reactive power capability limits, causing voltage instability problems. Thus, the operation of certain OLTCs has a significant influence on voltage instability under some operating conditions. These transformers can be made manual to avoid possible voltage instability due to their operation during heavy load conditions. Tap blocking, based on local measurement of high voltage side of load tap changers, is a common practice of power utilities to prevent voltage collapse. The great advantage of this method is that it can be easily implemented, but does not guarantee voltage stability. So a proper approach for identification of critical OLTC s based on voltage stability criteria is essential to guide the operator in ECC, which has been proposed in this thesis. It discusses the effect of OLTCs with different objectives of reactive power dispatch and proposes a technique to identify critical OLTCs based on voltage stability criteria. The fast development of power electronics based on new and powerful semiconductor devices has led to innovative technologies, such as High Voltage DC transmission (HVDC) and Flexible AC Transmission System (FACTS), which can be applied in transmission and distribution systems. The technical and economicalBenefits of these technologies represent an alternative to the application in AC systems. Deregulation in the power industry and opening of the market for delivery of cheaper energy to the customers is creating additional requirements for the operation of power systems. HVDC and FACTS offer major advantages in meeting these requirements. .A method for co-ordinated optimum allocation of reactive power in AC/DC power systems by including FACTS controller UPFC, with an objective of minimization of the sum of the squares of the voltage deviations of all the load buses has been proposed in this thesis. The study results show that under contingency conditions, the presence of FACTS controllers has considerable impact on over all system voltage stability and also on power loss minimization.minimization of the sum of the squares of the voltage deviations of all the load buses has been proposed in this thesis. The study results show that under contingency conditions, the presence of FACTS controllers has considerable impact on over all system voltage stability and also on power loss minimization. As power systems grow in their size and interconnections, their complexity increases. For secure operation and control of power systems under normal and contingency conditions, it is essential to provide solutions in real time to the operator in ECC. For real time control of power systems, the conventional algorithmic software available in ECC are found to be inadequate as they are computationally very intensive and not organized to guide the operator during contingency conditions. Artificial Intelligence (AI) techniques such as, Expert systems, Neural Networks, Fuzzy systems are emerging decision support system tools which give fast, though approximate, but acceptable right solutions in real time as they mostly use symbolic processing with a minimum number of numeric computations. The solution thus obtained can be used as a guide by the operator in ECC for power system control. Optimum real and reactive power dispatch play an important role in the day-to-day operation of power systems. Existing conventional Optimal Power Flow (OPF) methods use all of the controls in solving the optimization problem. The operators can not move so many control devices within a reasonable time. In this context an algorithm using fuzzy-expert approach has been proposed in this thesis to curtail the number of control actions, in order to realize real time objectives in voltage/reactive power control. The technique is formulated using membership functions of linguistic variables such as voltage deviations at all the load buses and the voltage deviation sensitivity to control variables. Voltage deviations and controlling variables are translated into fuzzy set notations to formulate the relation between voltage deviations and controlling ability of controlling devices. Control variables considered are switchable VAR compensators, OLTC transformers and generator excitations. A fuzzy rule based system is formed to select the critical controllers, their movement direction and step size. Results show that the proposed approach is effective for improving voltage security to acceptable levels with fewer numbers of controllers. So, under emergency conditions the operator need not move all the controllers to different settings and the solution obtained is fast with significant speedups. Hence, the proposed method has the potential to be integrated for on-line implementation in energy management systems to achieve the goals of secure power system operation. In a deregulated electricity market, it may not be always possible to dispatch all of the contracted power transactions due to congestion of the transmission corridors. System operators try to manage congestion, which otherwise increases the cost of the electricity and also threatens the system security and stability. An approach for alleviation of network over loads in the day-to-day operation of power systems under deregulated environment is presented in this thesis. The control used for overload alleviation is real power generation rescheduling based on Relative Electrical Distance (RED) concept. The method estimates the relative location of load nodes with respect to the generator nodes. The contribution of each generator for a particular over loaded line is first identified , then based on RED concept the desired proportions of generations for the desired overload relieving is obtained, so that the system will have minimum transmission losses and more stability margins with respect to voltage profiles, bus angles and better transmission tariff. The results obtained reveal that the proposed method is not only effective for overload relieving but also reduces the system power loss and improves the voltage stability margin. The presented concepts are better suited for finding the utilization of resources generation/load and network by various players involved in the day-to-day operation of the system under normal and contingency conditions. This will help in finding the contribution by various players involved in the congestion management and the deviations can be used for proper tariff purposes. Suitable computer programs have been developed based on the algorithms presented in various chapters and thoroughly tested. Studies have been carried out on various equivalent systems of practical real life Indian power networks and also on some standard IEEE systems under simulated conditions. Results obtained on a modified IEEE 30 bus system, IEEE 39 bus New England system and four Indian power networks of EHV 24 bus real life equivalent power network, an equivalent of 36 bus EHV Indian western grid, Uttar Pradesh 96 bus AC/DC system and 205 Bus real life interconnected grid system of Indian southern region are presented for illustration purposes.

The objective of an Energy Control Center (ECC) is to ensure secure and economic operation of power system. The challenge to optimize power system operation, while maintaining system security and quality of power supply to customers, is increasing. Growing demand without matching expansion of generation and transmission facilities and more tightly interconnected power systems contribute to the increased complexity of system operation. Rising costs due to inflation and increased environmental concerns has made transmission, as well as generation systems to be operated closure to design limits, with smaller safety margins and hence greater exposure to unsatisfactory operating conditions following a disturbance. Investigations of recent blackouts indicate that the root cause of most of these major power system disturbances is voltage collapse. Information gathered and preliminary analysis, from the most recent blackout incident in North America on 14th August 2003, is pointing the finger on voltage instability due to some unexpected contingency. In this incident, reports indicate that approximately 50 million people were affected interruption from continuous supply for more than 15 hours. Most of the incidents are related to heavily stressed system where large amounts of real and reactive power are transported over long transmission lines while appropriate real and reactive power resources are not available to maintain normal system conditions. Hence, the problem of voltage stability and voltage collapse has become a major concern in power system planning and operation. Reliable operation of large scale electric power networks requires that system voltages and currents stay within design limits. Operation beyond those limits can lead to equipment failures and blackouts. In the last few decades, the problem of reactive power control for improving economy and security of power system operation has received much attention. Generally, the load bus voltages can be maintained within their permissible limits by reallocating reactive power generations in the system. This can be achieved by adjusting transformer taps, generator voltages, and switchable Ar sources. In addition, the system losses can be minimized via redistribution of reactive power in the system. Therefore, the problem of the reactive power dispatch can be optimized to improve the voltage profile and minimize the system losses as well. The Instability in power system could be relieved or at least minimized with the help of most recent developed devices called Flexible AC Transmission System (FACTS) controllers. The use of Flexible AC Transmission System (FACTS) controllers in power transmission system have led to many applications of these controllers not only to improve the stability of the existing power network resources but also provide operating flexibility to the power system. In the past, transmission systems were owned by regulated, vertically integrated utility companies. They have been designed and operated so that conditions in close proximity to security boundaries are not frequently encountered. However, in the new open access environment, operating conditions tend to be much closer to security boundaries, as transmission use is increasing in sudden and unpredictable directions. Transmission unbundling, coupled with other regulatory requirements, has made new transmission facility construction more difficult. In fact, there are numerous technical challenges emerging from the new market structure. There is an acute need for research work in the new market structure, especially in the areas of voltage security, reactive power support and congestion management. In the last few decades more attention was paid to optimal reactive power dispatch. Since the problem of reactive power optimization is non-linear in nature, nonlinear programming methods have been used to solve it. These methods work quite well for small power systems but may develop convergence problems as system size increases. Linear programming techniques with iterative schemes are certainly the most promising tools for solving these types of problems. The thesis presents efficient algorithms with different objectives for reactive power optimization. The approach adopted is an iterative scheme with successive power-flow analysis using decoupled technique, formulation and solution of the linear-programmingproblem with only upper-bound limits on the state variables. Further the thesispresents critical analysis of the three following objectives, Viz., •Minimization of the sum of the squares of the voltage deviations (Vdesired) •Minimization of sum of the squares of the voltage stability L indices (Vstability) •Minimization of real power losses (Ploss) Voltage stability problems normally occur in heavily stressed systems. While the disturbance leading to voltage collapse may be initiated by a variety of causes, the underlying problem is an inherent weakness in the power system. The factors contributing to voltage collapse are the generator reactive power /voltage control limits, load characteristics, characteristics of reactive compensation devices, and the action of the voltage control devices such as transformer On Load Tap Changers (OLTCs). Power system experiences abnormal operating conditions following a disturbance, and subsequently a reduction in the EHV level voltages at load centers will be reflected on the distribution system. The OLTCs of distribution transformers would restore distribution voltages. With each tap change operation, the MW and MVAR loading on the EHV lines would increase, thereby causing great voltage drops in EHV levels and increasing the losses. As a result, with each tap changing operation, the reactive output of generators throughout the system would increase gradually and the generators may hit their reactive power capability limits, causing voltage instability problems. Thus, the operation of certain OLTCs has a significant influence on voltage instability under some operating conditions. These transformers can be made manual to avoid possible voltage instability due to their operation during heavy load conditions. Tap blocking, based on local measurement of high voltage side of load tap changers, is a common practice of power utilities to prevent voltage collapse. The great advantage of this method is that it can be easily implemented, but does not guarantee voltage stability. So a proper approach for identification of critical OLTC s based on voltage stability criteria is essential to guide the operator in ECC, which has been proposed in this thesis. It discusses the effect of OLTCs with different objectives of reactive power dispatch and proposes a technique to identify critical OLTCs based on voltage stability criteria. The fast development of power electronics based on new and powerful semiconductor devices has led to innovative technologies, such as High Voltage DC transmission (HVDC) and Flexible AC Transmission System (FACTS), which can be applied in transmission and distribution systems. The technical and economicalBenefits of these technologies represent an alternative to the application in AC systems. Deregulation in the power industry and opening of the market for delivery of cheaper energy to the customers is creating additional requirements for the operation of power systems. HVDC and FACTS offer major advantages in meeting these requirements. .A method for co-ordinated optimum allocation of reactive power in AC/DC power systems by including FACTS controller UPFC, with an objective of minimization of the sum of the squares of the voltage deviations of all the load buses has been proposed in this thesis. The study results show that under contingency conditions, the presence of FACTS controllers has considerable impact on over all system voltage stability and also on power loss minimization.minimization of the sum of the squares of the voltage deviations of all the load buses has been proposed in this thesis. The study results show that under contingency conditions, the presence of FACTS controllers has considerable impact on over all system voltage stability and also on power loss minimization. As power systems grow in their size and interconnections, their complexity increases. For secure operation and control of power systems under normal and contingency conditions, it is essential to provide solutions in real time to the operator in ECC. For real time control of power systems, the conventional algorithmic software available in ECC are found to be inadequate as they are computationally very intensive and not organized to guide the operator during contingency conditions. Artificial Intelligence (AI) techniques such as, Expert systems, Neural Networks, Fuzzy systems are emerging decision support system tools which give fast, though approximate, but acceptable right solutions in real time as they mostly use symbolic processing with a minimum number of numeric computations. The solution thus obtained can be used as a guide by the operator in ECC for power system control. Optimum real and reactive power dispatch play an important role in the day-to-day operation of power systems. Existing conventional Optimal Power Flow (OPF) methods use all of the controls in solving the optimization problem. The operators can not move so many control devices within a reasonable time. In this context an algorithm using fuzzy-expert approach has been proposed in this thesis to curtail the number of control actions, in order to realize real time objectives in voltage/reactive power control. The technique is formulated using membership functions of linguistic variables such as voltage deviations at all the load buses and the voltage deviation sensitivity to control variables. Voltage deviations and controlling variables are translated into fuzzy set notations to formulate the relation between voltage deviations and controlling ability of controlling devices. Control variables considered are switchable VAR compensators, OLTC transformers and generator excitations. A fuzzy rule based system is formed to select the critical controllers, their movement direction and step size. Results show that the proposed approach is effective for improving voltage security to acceptable levels with fewer numbers of controllers. So, under emergency conditions the operator need not move all the controllers to different settings and the solution obtained is fast with significant speedups. Hence, the proposed method has the potential to be integrated for on-line implementation in energy management systems to achieve the goals of secure power system operation. In a deregulated electricity market, it may not be always possible to dispatch all of the contracted power transactions due to congestion of the transmission corridors. System operators try to manage congestion, which otherwise increases the cost of the electricity and also threatens the system security and stability. An approach for alleviation of network over loads in the day-to-day operation of power systems under deregulated environment is presented in this thesis. The control used for overload alleviation is real power generation rescheduling based on Relative Electrical Distance (RED) concept. The method estimates the relative location of load nodes with respect to the generator nodes. The contribution of each generator for a particular over loaded line is first identified , then based on RED concept the desired proportions of generations for the desired overload relieving is obtained, so that the system will have minimum transmission losses and more stability margins with respect to voltage profiles, bus angles and better transmission tariff. The results obtained reveal that the proposed method is not only effective for overload relieving but also reduces the system power loss and improves the voltage stability margin. The presented concepts are better suited for finding the utilization of resources generation/load and network by various players involved in the day-to-day operation of the system under normal and contingency conditions. This will help in finding the contribution by various players involved in the congestion management and the deviations can be used for proper tariff purposes. Suitable computer programs have been developed based on the algorithms presented in various chapters and thoroughly tested. Studies have been carried out on various equivalent systems of practical real life Indian power networks and also on some standard IEEE systems under simulated conditions. Results obtained on a modified IEEE 30 bus system, IEEE 39 bus New England system and four Indian power networks of EHV 24 bus real life equivalent power network, an equivalent of 36 bus EHV Indian western grid, Uttar Pradesh 96 bus AC/DC system and 205 Bus real life interconnected grid system of Indian southern region are presented for illustration purposes.