Relevant bibliographies by topics / DISTRIBUTED GENERATION PLANNING

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'DISTRIBUTED GENERATION PLANNING'

Author: Grafiati
Published: 19 January 2024

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Journal articles on the topic "DISTRIBUTED GENERATION PLANNING"

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Dugan, R. C., T. E. McDermott, and G. J. Ball. "Planning for distributed generation." IEEE Industry Applications Magazine 7, no. 2 (2001): 80–88. http://dx.doi.org/10.1109/2943.911193.

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Bazrafshan, Mohammadhafez, Likhitha Yalamanchili, Nikolaos Gatsis, and Juan Gomez. "Stochastic Planning of Distributed PV Generation." Energies 12, no. 3 (January 31, 2019): 459. http://dx.doi.org/10.3390/en12030459.

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Recent studies by electric utility companies indicate that maximum benefits of distributed solar photovoltaic (PV) units can be reaped when siting and sizing of PV systems is optimized. This paper develops a two-stage stochastic program that serves as a tool for optimally determining the placing and sizing of PV units in distribution systems. The PV model incorporates the mapping from solar irradiance to AC power injection. By modeling the uncertainty of solar irradiance and loads by a finite set of scenarios, the goal is to achieve minimum installation and network operation costs while satisfying necessary operational constraints. First-stage decisions are scenario-independent and include binary variables that represent the existence of PV units, the area of the PV panel, and the apparent power capability of the inverter. Second-stage decisions are scenario-dependent and entail reactive power support from PV inverters, real and reactive power flows, and nodal voltages. Optimization constraints account for inverter’s capacity, PV module area limits, the power flow equations, as well as voltage regulation. A comparison between two designs, one where the DC:AC ratio is pre-specified, and the other where the maximum DC:AC ratio is specified based on historical data, is carried out. It turns out that the latter design reduces costs and allows further reduction of the panel area. The applicability and efficiency of the proposed formulation are numerically demonstrated on the IEEE 34-node feeder, while the output power of PV systems is modeled using the publicly available PVWatts software developed by the National Renewable Energy Laboratory. The overall framework developed in this paper can guide electric utility companies in identifying optimal locations for PV placement and sizing, assist with targeting customers with appropriate incentives, and encourage solar adoption.
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Liu, Zi Fa, Gang Liu, and Wei Zhang. "Substation Optimization Planning Considering Distributed Generation." Advanced Materials Research 732-733 (August 2013): 1314–19. http://dx.doi.org/10.4028/www.scientific.net/amr.732-733.1314.

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This paper established a transformer substation comprehensive optimal planning model considering distribution generation (DG) and different block geographic information factors (GIF), set form, volume, location of existing DG in planning area and transformer substation load-bearing capacity as constraint condition, taking construction cost of distribution transform substation and feeder and operation cost including current supply loss into account, in the meantime, regarding the influence of GIF such as land properties and so on to location and cost of construction with load demand satisfied. Furthermore, influence factors of different block information factor to construction cost were work out by means of interval analytical hierarchy process. On the basis of the established objective function, an particle swarm optimization (PSO) algorithm is proposed to solve the problem in this paper. By empirical study of certain planning area, the proposed model and algorithm are proved to be scientific and effective.
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Singh, Bindeshwar, and Janmejay Sharma. "A review on distributed generation planning." Renewable and Sustainable Energy Reviews 76 (September 2017): 529–44. http://dx.doi.org/10.1016/j.rser.2017.03.034.

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Rouhani, Ahmad, Seyyed Hadi Hosseini, and Mahdi Raoofat. "Composite generation and transmission expansion planning considering distributed generation." International Journal of Electrical Power & Energy Systems 62 (November 2014): 792–805. http://dx.doi.org/10.1016/j.ijepes.2014.05.041.

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Keane, A., Q. Zhou, J. W. Bialek, and Mark O'Malley. "Planning and operating non-firm distributed generation." IET Renewable Power Generation 3, no. 4 (2009): 455. http://dx.doi.org/10.1049/iet-rpg.2008.0058.

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Dzamarija, Mario, and Andrew Keane. "Autonomous Curtailment Control in Distributed Generation Planning." IEEE Transactions on Smart Grid 7, no. 3 (May 2016): 1337–45. http://dx.doi.org/10.1109/tsg.2015.2427378.

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Kochukov, O., and A. Mutule. "Network-Oriented Approach to Distributed Generation Planning." Latvian Journal of Physics and Technical Sciences 54, no. 3 (June 27, 2017): 3–12. http://dx.doi.org/10.1515/lpts-2017-0015.

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AbstractThe main objective of the paper is to present an innovative complex approach to distributed generation planning and show the advantages over existing methods. The approach will be most suitable for DNOs and authorities and has specific calculation targets to support the decision-making process. The method can be used for complex distribution networks with different arrangement and legal base.
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Wu, Lei, Hai Zhang, Zhaojie Hu, Yinghua Wang, Hairong Wang, Hua Yang, Bin Fan, and Hao Chang. "Multi-objective distribution network planning method with distributed generation based on non dominated sorting differential evolution algorithm." Journal of Physics: Conference Series 2247, no. 1 (April 1, 2022): 012019. http://dx.doi.org/10.1088/1742-6596/2247/1/012019.

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Abstract Combined with the specific problems of distribution network planning with distributed generation, this paper constructs a multi-objective optimization model of distribution network planning with distributed generation. According to the distributed generation distribution network layout planning with distributed generation, under the condition of uncertain load prediction value of distributed generation distribution network, taking the minimum voltage stability index, minimum network loss and minimum investment cost of distributed generation as sub objectives, a multi-objective programming model is established, and the model is solved by non dominated sorting differential evolution (NSDE) algorithm.
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Contreras, Javier, and Gregorio Muñoz-Delgado. "Distributed Power Generation Scheduling, Modeling, and Expansion Planning." Energies 14, no. 22 (November 19, 2021): 7757. http://dx.doi.org/10.3390/en14227757.

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Dissertations / Theses on the topic "DISTRIBUTED GENERATION PLANNING"

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Huang, Yalin. "Electricity Distribution Network Planning Considering Distributed Generation." Licentiate thesis, KTH, Elektriska energisystem, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-141482.

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One of EU’s actions against climate change is to meet 20% of our energy needs from renewable resources. Given that the renewable resources are becoming more economical to extract electricity from, this will result in that more and more distributed generation (DG) will be connected to power distribution. The increasing share of DG in the electricity networks implies both increased costs and benefits for distribution system operators (DSOs), customers and DG producers. How the costs and benefits will be allocated among the actors will depend on the established regulation. Distribution networks are traditionally not designed to accommodate generation. Hence, increasing DG penetration is causing profound changes for DSOs in planning, operation and maintenance of distribution networks. Due to the unbundling between DSOs and electricity production, DSOs can not determine either the location or the size of DG. This new power distribution environment brings new challenges for the DSOs and the electric power system regulator. The DSOs are obliged to enable connection of DG meanwhile fulfilling requirements on power quality and adequate reliability. Moreover, regulatory implications can make potential DG less attractive. Therefore regulation should be able to send out incentives for the DSOs to efficiently plan the network to accommodate the increasing levels of DG. To analyze the effects of regulatory polices on network investments, risk analysis methods for integrating the DG considering uncertainties are therefore needed. In this work, regulation impact on network planning methods and network tariff designs in unbundled electricity network is firstly analyzed in order to formulate a realistic long-term network planning model considering DG. Photovoltaic (PV) power and wind power plants are used to demonstrate DG. Secondly, this work develops a deterministic model for low-voltage (LV) networks mainly considering PV connections which is based on the worst-case scenario. Dimension the network using worst-case scenario is the convention in the long-term electricity distribution network planning for the reliability and security reason. This model is then further developed into a probabilistic model in order to consider the uncertainties from DG production and load. Therefore more realistic operation conditions are considered and probabilistic constrains on voltage variation can be applied. Thirdly, this work develops a distribution medium-voltage (MV) network planning model considering wind power plant connections. The model obtains the optimal network expansion and reinforcement plan of the target network considering the uncertainties from DG production and load. The model is flexible to modify the constraints. The technical constraints are respected in any scenario and violated in few scenarios are implemented into the model separately. In LV networks only PV connections are demonstrated and in MV networks only wind power connections are demonstrated. The planning model for LV networks is proposed as a practical guideline for PV connections. It has been shown that it is simple to be implemented and flexible to adjust the planning constraints. The proposed planning model for MV networks takes reinforcement on existing lines, new connection lines to DG, alternatives for conductor sizes and substation upgrade into account, and considers non-linear power flow constraints as an iterative linear optimization process. The planning model applies conservative limits and probabilistic limits for increasing utilization of the network, and the different results are compared in case studies. The model’s efficiency, flexibility and accuracy in long-term distribution network planning problems are shown in the case studies.

QC 20140217


Elforsk Risknanlys II
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Liang, Wen-Ting. "Optimal Planning of the Distribution Network with Distributed Generation." Thesis, The University of Sydney, 2016. http://hdl.handle.net/2123/15526.

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The deregulation of electricity market created a competitive market environment. For Distribution companies (DISCOs), how to maximize its profit is the primary purpose of this planning and operations. Therefore, to achieve the best economic and technical benefits, a DISCOs should determine where and how much DG units allow to install in the system. Distributed generation is a key component in the power market. There is a brief introduction of DG in this thesis including: the definition of DG, size and several often used DG types. The benefit and risk of DG which may bring to the power system also have been appropriately evaluated in this study. The review of literature of optimal size and location of DG in distribution system have shown that a number of economic and technical impacts have been considered in DG planning. The selection of the best places and the preferable size of DG units for installation in the distribution system is a complex combinatorial optimization problem. The various solution techniques along with various objective function and constraints for the optimal solution of the problem of size and location problem of DG are discussed and compared in this work. With the increasing of load demand, distributed generation becomes an attractive alternative method to supply the power in the distribution system. DG can not only help to defer the T&D investment but also bring benefits to environment protection. The technical benefit which can bring to the distribution system also cannot be ignored. Such as power loss reduction, voltage profile and power quality improvement. The impact of DG units on voltage stability has become significant. A review of the indices refers to voltage stability has been shown in this work and an index named voltage collapse proximity index (VCPI) was introduced and used in this work. This study proposed a planning framework for effective planning of DG units in the distribution system due to minimize total cost and enhance the voltage stability of the system. To achieve the purpose of minimizing the total cost and maximize the technical benefit of DG units to voltage stability, a multi-objective methodology to decide optimal locations and size of DG units. The total cost in the proposed planning model includes investment cost, operation and maintenance cost except the revenue from the utility grid. VCPI which is given in this study have been used in this model to identify the voltage stability of this system. The uncertainties associated with the load value, and generated power of renewable energy DG units also take a part in this study. A Monte Carlo simulation method has been introduced in this work to calculate the uncertainty because of probabilistic nature of renewable DG unit (WTs, PVs). The Pareto optimal set is found by using non-dominated sorting genetic algorithm method and the final result is chosen by using the max-min method. An IEEE 33-bus distribution system with DG installation has been used to achieve the goals of minimum total cost and improvement of voltage stability.
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Su, Wencong. "Microgrid Modeling, Planning and Operation." Thesis, Virginia Tech, 2009. http://hdl.handle.net/10919/35843.

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As distributed generations and renewable energy are becoming the fastest growing segment of the energy industry, the technical issues and environmental impacts have to be studied and understood. The large number of small-scale Microgrid components with their own characteristics is a big challenge for Microgrid modeling, simulation, planning and operation.

The major goal of this thesis is to build a library of various Microgrid components. First of all, the thesis is going to present a detailed description of Microgrid models with moderate complexity. Next, it will present the modeling of loads, utility grid and transmission lines. Then, the paper will discuss the distributed generation models that have been developed in Matlab/Simulink including Diesel Engine, Fuel Cell, Micro Gas Turbine, Wind Turbine, Photovoltaic Cell, along with the detailed modeling of short-term storage (Battery, Pumped Hydro Storage, Flywheel, and Supercapacitor). In addition to steady-state study, the thesis will also discuss the hybrid sample systems that are built to investigate their transient responses.

To enhance the simulation performance, some improvements on modeling and simulation will be introduced as well. To accommodate the high demand of renewable energy and the environment policy, the planning and operation the of Micro-source generators has been studied using HOMER. Simulation results show a case study of an optimal microgrid configuration on Ontario area in Canada. Sensitivity variables are specified to examine the effect of uncertainties, especially in a long-term planning. Also, demand side management plays an important role in the operation of Microgrid. Based on raw data, case studies are carried out to investigate and validate the demand response methods. Finally, the philosophy for Microgrid protection, especially Time-delay overcurrent protection, will be briefly introduced in both gird-connected and islanding modes.
Master of Science

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Zamani, Iman. "Optimal distributed generation planning based on NSGA-II and MATPOWER." Thesis, Brunel University, 2015. http://bura.brunel.ac.uk/handle/2438/11483.

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The UK and the world are moving away from central energy resource to distributed generation (DG) in order to lower carbon emissions. Renewable energy resources comprise a big percentage of DGs and their optimal integration to the grid is the main attempt of planning/developing projects with in electricity network. Feasibility and thorough conceptual design studies are required in the planning/development process as most of the electricity networks are designed in a few decades ago, not considering the challenges imposed by DGs. As an example, the issue of voltage rise during steady state condition becomes problematic when large amount of dispersed generation is connected to a distribution network. The efficient transfer of power out or toward the network is not currently an efficient solution due to phase angle difference of each network supplied by DGs. Therefore optimisation algorithms have been developed over the last decade in order to do the planning purpose optimally to alleviate the unwanted effects of DGs. Robustness of proposed algorithms in the literature has been only partially addressed due to challenges of power system problems such multi-objective nature of them. In this work, the contribution provides a novel platform for optimum integration of distributed generations in power grid in terms of their site and size. The work provides a modified non-sorting genetic algorithm (NSGA) based on MATPOWER (for power flow calculation) in order to find a fast and reliable solution to optimum planning. The proposed multi-objective planning tool, presents a fast convergence method for the case studies, incorporating the economic and technical aspects of DG planning from the planner‟s perspective. The proposed method is novel in terms of power flow constraints handling and can be applied to other energy planning problems.
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Alnaser, Sahban Wa'el Saeed. "Control of distributed generation and storage : operation and planning perspectives." Thesis, University of Manchester, 2015. https://www.research.manchester.ac.uk/portal/en/theses/control-of-distributed-generation-and-storage-operation-and-planning-perspectives(a937e071-4e6b-4a07-a196-031c3b23655f).html.

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Transition towards low-carbon energy systems requires an increase in the volume of renewable Distributed Generation (DG), particularly wind and photovoltaic, connected to distribution networks. To facilitate the connection of renewable DG without the need for expensive and time-consuming network reinforcements, distribution networks should move from passive to active methods of operation, whereby technical network constraints are actively managed in real time. This requires the deployment of control solutions that manage network constraints and, crucially, ensure adequate levels of energy curtailment from DG plants by using other controllable elements to solve network issues rather than resorting to generation curtailment only. This thesis proposes a deterministic distribution Network Management System (NMS) to facilitate the connections of renewable DG plants (specifically wind) by actively managing network voltages and congestion in real time through the optimal control of on-load tap changers (OLTCs), DG power factor and, then, generation curtailment as a last resort. The set points for the controllable elements are found using an AC Optimal Power Flow (OPF). The proposed NMS considers the realistic modelling of control by adopting one-minute resolution time-series data. To decrease the volumes of control actions from DG plants and OLTCs, the proposed approach departs from multi-second control cycles to multi-minute control cycles. To achieve this, the decision-making algorithm is further improved into a risk-based one to handle the uncertainties in wind power throughout the multi-minute control cycles. The performance of the deterministic and the risk-based NMS are compared using a 33 kV UK distribution network for different control cycles. The results show that the risk-based approach can effectively manage network constraints better than the deterministic approach, particularly for multi-minute control cycles, reducing also the number of control actions but at the expense of higher levels of curtailment. This thesis also proposes energy storage sizing framework to find the minimum power rating and energy capacity of multiple storage facilities to reduce curtailment from DG plants. A two-stage iterative process is adopted in this framework. The first stage uses a multi-period AC OPF across the studied horizon to obtain initial storage sizes considering hourly wind and load profiles. The second stage adopts a high granularity minute-by-minute control driven by a mono-period bi-level AC OPF to tune the first-stage storage sizes according to the actual curtailment. The application of the proposed planning framework to a 33 kV UK distribution network demonstrates the importance of embedding real-time control aspects into the planning framework so as to accurately size storage facilities. By using reactive power capabilities of storage facilities it is possible to reduce storage sizes. The combined active management of OLTCs and power factor of DG plants resulted in the most significant benefits in terms of the required storage sizes.
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Jones, Gavin Wesley. "Distribution system operation and planning in the presence of distributed generation technology." Diss., Rolla, Mo. : University of Missouri-Rolla, 2007. http://scholarsmine.umr.edu/thesis/pdf/Jones_09007dcc803b193d.pdf.

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Thesis (M.S.)--University of Missouri--Rolla, 2007.
Vita. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed November 16, 2007) Includes bibliographical references (p. 71-74).
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Ault, Graham W. "A planning and analysis framework for evaluating distributed generation and utility strategies." Thesis, University of Strathclyde, 2000. http://oleg.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=21142.

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The numbers of smaller scale distributed power generation units connected to the distribution networks of electricity utilities in the UK and elsewhere have grown significantly in recent years. Numerous economic and political drivers have stimulated this growth and continue to provide the environment for future growth in distributed generation. The simple fact that distributed generation is independent from the distribution utility complicates planning and operational tasks for the distribution network. The uncertainty relating to the number, location and type of distributed generating units to connect to the distribution network in the future makes distribution planning a particularly difficult activity. This thesis concerns the problem of distribution network and business planning in the era of distributed generation. A distributed generation strategic analysis framework is proposed to provide the required analytical capability and planning and decision making framework to enable distribution utilities to deal effectively with the challenges and opportunities presented to them by distributed generation. The distributed generation strategic analysis framework is based on the best features of modem planning and decision making methodologies and facilitates scenario based analysis across many utility strategic options and uncertainties. Case studies are presented and assessed to clearly illustrate the potential benefits of such an approach to distributed generation planning in the UK electricity supply industry.
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Hagström, Emil. "Grid planning with a large amount of small scale solar power." Thesis, Uppsala universitet, Institutionen för teknikvetenskaper, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-199060.

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With an increasing interest for renewable power, photovoltaics (PV) have becomemore and more common in the distribution network. If a customer wants to install aPV system, or another type of distributed generation (DG), the distribution systemoperators (DSO) needs a good way to determine if it the grid can handle it or not. InSweden, a guideline to aid the DSO was published in 2011. However, this guidelineonly considers one connection without considering other DG units. This project isabout developing new guidelines for DG connections in grids with a large number ofDG units. Based on a literature study it has been concluded that one of the mostcritical issue is over-voltage, which is the main focus of this project. Two new methods have been developed; the first proposed method is based onneglecting reactance and losses in the grid, a simple linear relationship between thevoltage level, the resistance in the lines, and the installed power is obtained. Thisrelationship is then used to calculate the voltage level at critical points in the grid. Thesecond method is to find the weakest bus, with a connected DG unit. By assumingthat all power is installed at that point we get a very simple guideline; it is veryconservative but can be used before the first method. A simulation tool has been developed in order to analyze the voltage level in grids forvarious cases with connected DG units. The simulated results have proven that theproposed guidelines are, when considering voltage issues, very reliable and can beuseful. However, further work needs to be done to ensure that other problems donot occur.
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Wang, David Tse-Chi. "Incorporating distributed generation into distribution network planning : the challenges and opportunities for distribution network operators." Thesis, University of Edinburgh, 2010. http://hdl.handle.net/1842/4621.

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Diversification of the energy mix is one of the main challenges in the energy agenda of governments worldwide. Technology advances together with environmental concerns have paved the way for the increasing integration of Distributed Generation (DG) seen over recent years. Combined heat and power and renewable technologies are being encouraged and their penetration in distribution networks is increasing. This scenario presents Distribution Network Operators (DNOs) with several technical challenges in order to properly accommodate DG developments. However, depending on various factors, such as location, size, technology and robustness of the network, DG might also be beneficial to DNOs. In this thesis, the impact of DG on network planning is analysed and the implications for DNOs in incorporating DG within the network planning process are identified. In the first part, various impacts of DG to the network, such as network thermal capacity release, security of supply and on voltage, are quantified through network planning by using a modified successive elimination method and voltage sensitivity analysis. The results would potentially assist DNOs in assessing the possibilities and effort required to utilise privately-owned DG to improve network efficiency and save investment. The quantified values would also act as a fundamental element in deriving effective distribution network charging schemes. In the second part, a novel balanced genetic algorithm is introduced as an efficient means of tackling the problem of optimum network planning considering future uncertainties. The approach is used to analyse the possibilities, potential benefits and challenges to strategic network planning by considering the presence of DG in the future when the characteristics of DG are uncertain.
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Madrazo, Vega Fernando. "Breaking barriers : an examination and recommendations regarding the role of clean distributed electricity generation in Mexico." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/113806.

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Thesis: M.C.P., Massachusetts Institute of Technology, Department of Urban Studies and Planning, 2017.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 146-149).
Through the 2013 Energy Reform, the Law of Energy Transition, and the General Law of Climate Change, the policy makers in Mexico have aimed to lower electricity tariffs, generate 35% of electricity from clean energy sources by 2024, and reduce greenhouse gas emissions by 30% in 2020 and 50% in 2050 compared to greenhouse gas emissions in 2000. Furthermore, the 2013 Energy Reform aims to promote economic development and reduce electricity subsidies. In an effort to achieve these goals, policy makers have tried to diversify the country's electricity generation profile, including the promotion of clean distributed generation (DG) technologies. A broad cross section of governmental and non-governmental stakeholders has publicly supported these objectives; however, low domestic electricity prices, high system acquisition costs, and a lack of financing have and will continue to limit the deployment of clean DG systems in Mexico. Furthermore, deep penetration of clean distributed generation under current net metering policies and electricity tariff structures may actually undercut the effective operation of Mexico's electricity market by increasing operation costs and adding technical complexities to the electricity network. In this thesis, I make three short-term and one long-term recommendations to the Ministry of Energy and the Energy Regulatory Commission to promote the deployment of clean DG technologies beyond current barriers to entry and without adding economic and technical strain to the electricity industry. I recommend that these organizations (1) add clean DG to grid planning and develop a distributed energy resources strategy, (2) execute community-scale clean DG capacity auctions, (3) increase investment and financing opportunities for the public, and (4) modify electricity tariff structures and net metering policies. I hope these recommendations to the Ministry of Energy and the Energy Regulatory Commission will help the State achieve its energy policy and greenhouse gas emission reduction goals.
by Fernando Madrazo Vega.
M.C.P.
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Books on the topic "DISTRIBUTED GENERATION PLANNING"

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G, Scott Walter, ed. Distributed power generation: Planning and evaluation. New York: Marcel Dekker, 2000.

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Gianfranco, Chicco, and Mancarella Pierluigi, eds. Characterization and planning of distributed multi-generation. New York: Nova Science Publishers, 2008.

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Woodford, Dennis. Phase 2 report: Oahu Wind Integration and Transmission Study (OWITS), Hawaiian Islands Transmission Interconnection Project. Golden, Colo: National Renewable Energy Laboratory, 2011.

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Woodford, Dennis. Oahu Wind Integration and Transmission Study (OWITS): Hawaiian Islands Transmission Interconnection Project. Golden, Colo.]: National Renewable Energy Laboratory, 2011.

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National Renewable Energy Laboratory (U.S.), ed. Future of grid-tied PV business models: What will happen when PV penetration on the distribution grid is significant? : preprint. Golden, CO: National Renewable Energy Laboratory, 2008.

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Spencer, Abraham, and United States. Dept. of Energy., eds. National Transmission Grid Study. [Washington, D.C.]: U.S. Dept. of Energy, 2002.

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Willis, H. Lee. Distributed Power Generation: Planning and Evaluation. Taylor & Francis Group, 2018.

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Willis, H. Lee. Distributed Power Generation: Planning and Evaluation. Taylor & Francis Group, 2018.

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Willis, H. Lee. Distributed Power Generation: Planning and Evaluation. Taylor & Francis Group, 2018.

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Willis, H. Lee. Distributed Power Generation: Planning and Evaluation. Taylor & Francis Group, 2018.

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Book chapters on the topic "DISTRIBUTED GENERATION PLANNING"

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Dahalan, Wardiah Mohd, and Hazlie Mokhlis. "Simultaneous Network Reconfiguration and Sizing of Distributed Generation." In Electric Distribution Network Planning, 279–98. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-7056-3_10.

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Gon Chaudhuri, S. P., and Rekha Krishnan. "Planning to Mainstream Distributed Electricity Generation from Renewables." In Sustainable Energy Technology and Policies, 335–48. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8393-8_14.

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Bouhouras, Aggelos S., Paschalis A. Gkaidatzis, and Dimitris P. Labridis. "Optimal Distributed Generation Placement Problem for Power and Energy Loss Minimization." In Electric Distribution Network Planning, 215–51. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-7056-3_8.

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Li, Chun, and Xiaoliu Shen. "The Application of Hybrid Immune Algorithm in Distributed Generation Distribution Planning." In Lecture Notes in Electrical Engineering, 639–47. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34522-7_68.

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Pisică, Ioana, Petru Postolache, and Marcus M. Edvall. "Optimal Planning of Distributed Generation via Nonlinear Optimization and Genetic Algorithms." In Energy Systems, 451–82. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-02493-1_20.

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Hou, Yuanhong, Chao Feng, Yougui Aer, Shunhai Xue, Yuqiang Zhou, and Hongchao Wang. "Application of Improved Genetic Algorithm in Distribution Network Planning with Distributed Generation." In Innovative Computing Vol 1 - Emerging Topics in Artificial Intelligence, 937–43. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-2092-1_119.

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Saw, Bikash Kumar, Balmukund Kumar, and Aashish Kumar Bohre. "Intelligent Approach for Distributed Generation Planning and Distribution Network Reconfiguration Using Metaheuristic Technique." In Lecture Notes in Electrical Engineering, 29–44. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-6081-8_2.

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Setayesh Nazar, Mehrdad, and Alireza Heidari. "Multi-stage Resilient Distribution System Expansion Planning Considering Non-utility Gas-Fired Distributed Generation." In Power Systems Resilience, 193–222. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-94442-5_8.

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Velarde Martinez, Apolinar. "Random Generation of Directed Acyclic Graphs for Planning and Allocation Tasks in Heterogeneous Distributed Computing Systems." In Advances in Intelligent Systems and Computing, 793–802. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01174-1_61.

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Ntouros, Vasileios, Nikolaos Kampelis, Martina Senzacqua, Theoni Karlessi, Margarita-Niki Assimakopoulos, Dionysia Kolokotsa, and Cristina Cristalli. "Smart Meter Awareness in Italy, Ancona." In Smart and Sustainable Planning for Cities and Regions, 47–66. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-57764-3_4.

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AbstractSmart meters, one of the crucial enablers of the smart-grid concept and cornerstones in smart planning for cities, offer the opportunity for consumers to address their energy consumption effectively through timely and accurate data on their energy usage. However, previous studies have shown that smart meters may not lead to the desired energy savings unless actively used by households. To this end, the research presented in this paper investigates the penetration of smart meters at community level and explores how such a metering system can help people to understand and manage their energy use better. It examines the awareness about smart meters, looks into their presence in current accommodation and focuses on the views people have about smart meters. For this purpose, a questionnaire was prepared and distributed to a group of individuals residing in the wide area of Ancona province in Italy. Although the deployment of modern second-generation smart meters started in 2017 replacing the outdated smart meters massively installed in the 2000s, the results show low-to-moderate levels of awareness of modern smart meters among the respondents and a low presence of second-generation metering devices in their current accommodation. However, the general view expressed by the participants about smart meters is positive. The findings demonstrate that respondents are in need not only of a gauge that measures energy consumption but also of a tool that assists them to manage effectively their energy use.
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Conference papers on the topic "DISTRIBUTED GENERATION PLANNING"

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Chouhan, Jyoti, Amit Ojha, and Pankaj Swarnkar. "PSO-Based Distributed Generation Planning." In 2022 IEEE 2nd International Symposium on Sustainable Energy, Signal Processing and Cyber Security (iSSSC). IEEE, 2022. http://dx.doi.org/10.1109/isssc56467.2022.10051441.

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Qian, K., C. Zhou, M. Allan, and Y. Yuan. "Load modelling in distributed generation planning." In 2009 International Conference on Sustainable Power Generation and Supply. SUPERGEN 2009. IEEE, 2009. http://dx.doi.org/10.1109/supergen.2009.5348231.

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Al-Yami, I. M., and I. M. El-Amin. "Distributed generation planning using greedy heuristic approach." In 2011 2nd International Conference on Electric Power and Energy Conversion Systems (EPECS). IEEE, 2011. http://dx.doi.org/10.1109/epecs.2011.6126842.

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Malee, Rahul Kumar, Prerna Jain, Pranda Prashant Gupta, and Sharma Suman Dharampal. "Distribution system expansion planning incorporating distributed generation." In 2016 IEEE 7th Power India International Conference (PIICON). IEEE, 2016. http://dx.doi.org/10.1109/poweri.2016.8077273.

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Santoso, S., Nitish Saraf, and G. K. Venayagamoorthy. "Intelligent Techniques for Planning Distributed Generation Systems." In 2007 IEEE Power Engineering Society General Meeting. IEEE, 2007. http://dx.doi.org/10.1109/pes.2007.386170.

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Formigli, Carlos, Riccardo Rovatti, and Gianluca Setti. "Combined topological indices for distributed generation planning." In 2014 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT). IEEE, 2014. http://dx.doi.org/10.1109/isgt.2014.6816481.

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Anderlini, M., L. de Santoli, and F. Fraticelli. "Distributed energy generation: case study of a mountain school campus in Italy." In SUSTAINABLE DEVELOPMENT AND PLANNING 2013. Southampton, UK: WIT Press, 2013. http://dx.doi.org/10.2495/sdp130451.

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Gomes, Phillipe Vilaca, and Joao Tome Saraiva. "Transmission system planning considering solar distributed generation penetration." In 2017 14th International Conference on the European Energy Market (EEM). IEEE, 2017. http://dx.doi.org/10.1109/eem.2017.7981850.

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Wang, H. H., and L. B. Shi. "Optimal distribution network expansion planning incorporating distributed generation." In 2016 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC). IEEE, 2016. http://dx.doi.org/10.1109/appeec.2016.7779782.

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Asmuth, P., and J. F. Verstege. "Planning of distribution systems with predominantly distributed generation." In 2005 IEEE Russia Power Tech. IEEE, 2005. http://dx.doi.org/10.1109/ptc.2005.4524784.

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