Nowadays modern electric power systems consist of large-scale and highly complex interconnected transmission systems, thus transmission expansion planning (TEP) is now a significant power system optimisation problem. The TEP problem is a large-scale, complex and nonlinear combinatorial problem of mixed integer nature where the number of candidate solutions to be evaluated increases exponentially with system size. The accurate solution of the TEP problem is essential in order to plan power systems in both an economic and efficient manner. Therefore, applied optimisation methods should be sufficiently efficient when solving such problems. In recent years a number of computational techniques have been proposed to solve this efficiency issue. Such methods include algorithms inspired by observations of natural phenomena for solving complex combinatorial optimisation problems. These algorithms have been successfully applied to a wide variety of electrical power system optimisation problems. In recent years differential evolution algorithm (DEA) procedures have been attracting significant attention from the researchers as such procedures have been found to be extremely effective in solving power system optimisation problems. The aim of this research is to develop and apply a novel DEA procedure directly to a DC power flow based model in order to efficiently solve the TEP problem. In this thesis, the TEP problem has been investigated in both static and dynamic form. In addition, two cases of the static TEP problem, with and without generation resizing, have also been investigated. The proposed method has achieved solutions with good accuracy, stable convergence characteristics, simple implementation and satisfactory computation time. The analyses have been performed within the mathematical programming environment of MATLAB using both DEA and conventional genetic algorithm (CGA) procedures and a detailed comparison has also been presented. Finally, the sensitivity of DEA control parameters has also been investigated.

Nowadays, electricity markets are becoming more deregulated, especially development of smart grid and introduction of renewable energy promote regulations of energy markets. On the other hand, the uncertainties of new energy sources and market participants’ bidding bring more challenges to power system operation and transmission system planning. These problems motivate us to study spot price (also called locational marginal pricing) of electricity markets, the strategic bidding of wind power producer as an independent power producer into power market, transmission expansion planning considering wind power investment, and analysis of the maximum loadability of a power grid. The work on probabilistic spot pricing for a utility grid includes renewable wind power generation in a deregulated environment, taking into account both the uncertainty of load forecasting and the randomness of wind speed. Based on the forecasted normal-distributed load and Weibull-distributed wind speed, probabilistic optimal power flow is formulated by including spinning reserve cost associated with wind power plants and emission cost in addition to conventional thermal power plant cost model. Simulations show that the integration of wind power can effectively decrease spot price, also increase the risk of overvoltage. Based on the concept of loacational marginal pricing which is determined by a marketclearing algorithm, further research is conducted on optimal offering strategies for wind power producers participating in a day-ahead market employing a stochastic market-clearing algoivrithm. The proposed procedure to drive strategic offers relies on a stochastic bilevel model: the upper level problem represents the profit maximization of the strategic wind power producer, while the lower level one represents the marketing clearing and the corresponding price formulation aiming to co-optimize both energy and reserve. Thirdly, to improve wind power integration, we propose a bilevel problem incorporating two-stage stochastic programming for transmission expansion planning to accommodate large-scale wind power investments in electricity markets. The model integrates cooptimizations of energy and reserve to deal with uncertainties of wind power production. In the upper level problem, the objective of independent system operator (ISO) modelling transmission investments under uncertain environments is to minimize the transmission and wind power investment cost, and the expected load shedding cost. The lower level problem is composed of a two stage stochastic programming problem for energy schedule and reserve dispatch simultaneously. Case studies are carried out for illustrating the effectiveness of the proposed model. The above market-clearing or power system operation is based on direct current optimal power flow (DC-OPF) model which is a linear problem without reactive power constraints. Power system maximum loadability is a crucial index to determine voltage stability. The fourth work in this thesis proposes a Lagrange semi-definite programming (SDP) method to solve the non-linear and non-convex optimization alternating current (AC) problem of the maximum loadability of security constrained power system. Simulation results from the IEEE three-bus system and IEEE 24-bus Reliability Test System (RTS) show that the proposed method is able to obtain the global optimal solution for the maximum loadability problem. Lastly, we summarize the conclusions from studies on the above mentioned optimization problems of electric power market under modern grid, as well as the influence of wind power integration on power system reliability, and transmission expansion planning, as well as the operations of electricity markets. Meanwhile, we also present some open questions on the related research, such as non-convex constraints in the lower-level problem of a bilevel problem, and integrating N-1 security criterion of transmission planning. / Graduate / lei.ming296@gmail.com

abstract: This research develops decision support mechanisms for power system operation and planning practices. Contemporary industry practices rely on deterministic approaches to approximate system conditions and handle growing uncertainties from renewable resources. The primary purpose of this research is to identify soft spots of the contemporary industry practices and propose innovative algorithms, methodologies, and tools to improve economics and reliability in power systems. First, this dissertation focuses on transmission thermal constraint relaxation practices. Most system operators employ constraint relaxation practices, which allow certain constraints to be relaxed for penalty prices, in their market models. A proper selection of penalty prices is imperative due to the influence that penalty prices have on generation scheduling and market settlements. However, penalty prices are primarily decided today based on stakeholder negotiations or system operator’s judgments. There is little to no methodology or engineered approach around the determination of these penalty prices. This work proposes new methods that determine the penalty prices for thermal constraint relaxations based on the impact overloading can have on the residual life of the line. This study evaluates the effectiveness of the proposed methods in the short-term operational planning and long-term transmission expansion planning studies. The second part of this dissertation investigates an advanced methodology to handle uncertainties associated with high penetration of renewable resources, which poses new challenges to power system reliability and calls attention to include stochastic modeling within resource scheduling applications. However, the inclusion of stochastic modeling within mathematical programs has been a challenge due to computational complexities. Moreover, market design issues due to the stochastic market environment make it more challenging. Given the importance of reliable and affordable electric power, such a challenge to advance existing deterministic resource scheduling applications is critical. This ongoing and joint research attempts to overcome these hurdles by developing a stochastic look-ahead commitment tool, which is a stand-alone advisory tool. This dissertation contributes to the derivation of a mathematical formulation for the extensive form two-stage stochastic programming model, the utilization of Progressive Hedging decomposition algorithm, and the initial implementation of the Progressive Hedging subproblem along with various heuristic strategies to enhance the computational performance. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2017

Orientador: Sergio Azevedo de Oliveira / Banca: Rubén Augusto Romero Lázaro / Banca: Antônio César Baleeiro Alves / Resumo: Neste trabalho propõe-se o desenvolvimento de uma interface gráfica voltada para a resolução do problema de planejamento da expansão das linhas de transmissão, que utiliza-se de programas para a obtenção das soluções ótimas ou de boas soluções. A grande dificuldade encontrada por usuários ao interagir com estes programas, motivou o desenvolvimento de uma aplicação com interface gráfica, a qual disponibiliza ao usuário diversas metodologias para a resolução do problema do planejamento da expansão das linhas de transmissão de energia elétrica. Espera-se que software como este, agregado ao sistema de ensino tradicional que normalmente 'e utilizado num curso de engenharia elétrica, possa fortalecer o processo de aprendizagem do aluno. Assim, o software educacional Transmission Expansion Planning (TEP 1.0) está sendo desenvolvido visando propiciar um ambiente agradável para a realização de simulações e testes e favorecer a aprendizagem dos conceitos que envolvem o problema do planejamento da expansão da transmissão. É possível através deste software fazer simulações para os sistemas: Garver (6 barras/ 15 ramos), Sul brasileiro (46 barras/79 ramos) e Norte-Nordeste brasileiro (87 barras/179 ramos). O software se beneficia de recursos oferecidos por programas que são executados em background, bem como da utilização de meta-heurísticas e do ambiente de processamento de máquinas paralelas virtuais, as quais podem ser selecionadas para realização dos testes em determinado sistema / Abstract: This work proposes the development of a computational tool aimed at solving the problem of the transmission expansion planning, which uses programs in the background to obtain optimal solutions or good solutions. The great difficulty for users to interact with these programs, motivated the development of an application with a graphical interface, which provides the user with various methodologies for solving the problem of expansion planning of transmission lines of electricity. It is expected that software like this, added to the traditional school system which is normally used in electrical engineering courses, can strengthen the process of student learning. Thus, the educational software Transmission Expansion Planning (TEP 1.0) is being developed to provide a pleasant environment for simulations and testing and promote the learning of concepts involving the issue of transmission expansion planning. It is possible using this software to do simulations for the systems: Garver (6 nodes / 15 branches), South Brazilian (46 nodes / 79 branches) and North-Northeast Brazilian (87 nodes / 179 branches). The software takes advantage of capabilities offered by programs that run on background, and using meta-heuristics and the processing environment, parallel virtual machine, which can be selected to test on a system / Mestre

Electricity transmission network investments are playing a key role in the integration process of power systems in the European Union. Given the magnitude of investment costs, their irreversibility, and their impact in the overall development of a region, accounting for the role of uncertainties as well as the involvement of multiple parties in the decision process allows for improved and more robust investment decisions. Even though the creation of this internal energy market requires attention to flexibility and strategic decision-making, existing literature and practitioners have not given proper attention to these topics. Using portfolios of real options, we present two stochastic mixed integer linear programming models for transmission network expansion planning. We study the importance of explicitly addressing uncertainties, the option to postpone decisions and other sources of flexibility in the design of transmission networks. In a case study based on the Azores archipelago we show how renewables penetration can increase by introducing contingency planning into the decision process considering generation capacity uncertainty. We also present a two-party Nash-Coase bargaining transmission capacity investment model. We illustrate optimal fair share cost allocation policies with a case study based on the Iberian market. Lastly, we develop a new model that considers both interconnection expansion planning under uncertainty and cross-border cost allocation based on portfolios of real options and Nash-Coase bargaining. The model is illustrated using Iberian transmission and market data.

No description available.

Tese de Programa Doutoral. Sistemas Sustentáveis de Energia. Universidade do Porto. Faculdade de Engenharia. 2011

Made available in DSpace on 2014-06-11T19:22:32Z (GMT). No. of bitstreams: 0 Previous issue date: 2009-11-20Bitstream added on 2014-06-13T18:08:26Z : No. of bitstreams: 1 proto_ab_me_ilha.pdf: 2777482 bytes, checksum: ac3152da7c340dcf6ab04c187cabe418 (MD5) / Neste trabalho propõe-se o desenvolvimento de uma interface gráfica voltada para a resolução do problema de planejamento da expansão das linhas de transmissão, que utiliza-se de programas para a obtenção das soluções ótimas ou de boas soluções. A grande dificuldade encontrada por usuários ao interagir com estes programas, motivou o desenvolvimento de uma aplicação com interface gráfica, a qual disponibiliza ao usuário diversas metodologias para a resolução do problema do planejamento da expansão das linhas de transmissão de energia elétrica. Espera-se que software como este, agregado ao sistema de ensino tradicional que normalmente ´e utilizado num curso de engenharia elétrica, possa fortalecer o processo de aprendizagem do aluno. Assim, o software educacional Transmission Expansion Planning (TEP 1.0) está sendo desenvolvido visando propiciar um ambiente agradável para a realização de simulações e testes e favorecer a aprendizagem dos conceitos que envolvem o problema do planejamento da expansão da transmissão. É possível através deste software fazer simulações para os sistemas: Garver (6 barras/ 15 ramos), Sul brasileiro (46 barras/79 ramos) e Norte-Nordeste brasileiro (87 barras/179 ramos). O software se beneficia de recursos oferecidos por programas que são executados em background, bem como da utilização de meta-heurísticas e do ambiente de processamento de máquinas paralelas virtuais, as quais podem ser selecionadas para realização dos testes em determinado sistema / This work proposes the development of a computational tool aimed at solving the problem of the transmission expansion planning, which uses programs in the background to obtain optimal solutions or good solutions. The great difficulty for users to interact with these programs, motivated the development of an application with a graphical interface, which provides the user with various methodologies for solving the problem of expansion planning of transmission lines of electricity. It is expected that software like this, added to the traditional school system which is normally used in electrical engineering courses, can strengthen the process of student learning. Thus, the educational software Transmission Expansion Planning (TEP 1.0) is being developed to provide a pleasant environment for simulations and testing and promote the learning of concepts involving the issue of transmission expansion planning. It is possible using this software to do simulations for the systems: Garver (6 nodes / 15 branches), South Brazilian (46 nodes / 79 branches) and North-Northeast Brazilian (87 nodes / 179 branches). The software takes advantage of capabilities offered by programs that run on background, and using meta-heuristics and the processing environment, parallel virtual machine, which can be selected to test on a system

No description available.

Orientador: Rubén Augusto Romero Lázaro / Resumo: Os sistemas elétricos do futuro próximo terão um comportamento dinâmico porque grandes fontes renováveis de geração, principalmente geração eólica e solar, serão construídas nos sistemas de potência de vários países do mundo incluindo o Brasil. A incerteza introduzida pelas fontes renováveis de energia é um problema que deve ser solucionado. Para resolver o problema da incerteza é necessário criar uma rede mais flexível. A alocação de armazenadores de energia no sistema de potência será necessária para lidar com as novas incertezas e para manter o funcionamento adequado do sistema. Adicionalmente, o sistema de transmissão deve-se tornar muito mais ativo através do uso de novas tecnologias flexíveis que permitirão ter um controle ótimo do sistema. As novas tecnologias incluem Sistemas Flexíveis de Transmissão em Corrente Alternada (FACTS), sistemas de transmissão de corrente continua (HVDC) e outras tecnologias que permitirão controlar as direções dos fluxos de potência sem alterar a geração ou demanda do sistema. Portanto, nesta tese são estudadas diferentes representações matemáticas para os problemas de fluxo de potência ótimo (FPO), planejamento da transmissão de longo prazo (PERT) e alocação de fontes de reativos (AFR) usando as equações de fluxo de potência de corrente alternada (CA). Adicionalmente, são propostas novas formulações para representar os problemas de fluxo de potência ótimo multiperíodo para sistemas de transmissão ativos que incluem FACTS, sistemas HVDC e ... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: The future power systems will have a dynamic behaviour due to a significant amount of renewable generation, especially wind and solar generation, will be installed in the power systems of many countries in the world including Brazil.The uncertainty introduced by the renewable energy resources is a problem that has to be solved. The development of a flexible network is necessary to solve the aforementioned problem. The installation of energy storage in the power system will be necessary to manage the new uncertainties and to maintain the adequate system’s operation. Additionally, the transmission system will become more active though new flexible technologies, which allows having an optimal control of the power system. The new technologies include Flexible AC Transmission System (FACTS), High Voltage Direct current (HVDC) transmission systems and other technologies, which allow controlling the power flow direction without changing the power injections of generation or demand. Therefore, in this thesis are studied different mathematical formulations using the AC power flow equations for the optimal power flow (OPF) problem, the transmission expansion planning (TEP) problem and the reactive power planning (RPP) problem. Furthermore, two additional contributions have been made. The first contribution is the development of new mathematical formulations for the multiperiod optimal power flow for active transmission systems that includes FACTS, HVDC and batteries. The second contrib... (Complete abstract click electronic access below) / Doutor