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

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

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

Orientador: Paulo de Barros Correia / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecanica / Made available in DSpace on 2018-08-09T13:14:43Z (GMT). No. of bitstreams: 1 Colnago_GlauberRenato_M.pdf: 2199430 bytes, checksum: a29163d68691a2b1bec8be6c8bf1d470 (MD5) Previous issue date: 2007 / Resumo: Os modelos de despacho ótimo atuais em usinas hidrelétricas (UHEs) são realizados tendo em conta as eficiências das unidades geradoras (UGs) obtidos com a extrapolação dos dados de um modelo em escala reduzida das turbinas. Uma extrapolação dos dados do modelo para o protótipo realizada com grande precisão poderia ser feita se houvesse semelhança dinâmica, geométrica e cinemática entre eles. Como isto é impossível, os fabricantes de turbinas possuem relações empíricas para corrigir as eficiências medidas no modelo para refletirem melhor o desempenho do protótipo. Apesar desta correção, o desempenho real das turbinas pode ser afetado por características construtivas ou operacionais das UHEs, não levadas em conta pelos fabricantes, e pode variar com o tempo de uso de uma forma diferente para cada UG de uma UHE. Logo, as eficiências das turbinas reais não são iguais às eficiências extrapoladas do modelo em escala reduzida e, sob esta ótica, um modelo de despacho realizado com as curvas de eficiência derivadas do modelo reduzido provavelmente não otimiza a eficiência de uma UHE. Pode-se obter dados de eficiência mais precisos (atualizados) das UGs instaladas com o auxílio de métodos de medição de vazão da água nos condutos forçados das UGs. Neste trabalho foi desenvolvido um modelo de despacho ótimo em UGs de UHEs que trata individualmente as UGs, pois as mesmas possuem, provavelmente, curvas diferentes quando se trata dos dados atualizados. A formulação matemática do modelo de despacho ótimo proposto é não linear inteiro misto e não convexo e foi utilizado o programa Lingo 8.0 para sua resolução, com buscas global e local. Os melhores resultados foram obtidos com a busca global. Foi realizado o despacho com os dois tipos de dados, os derivados do modelo reduzido e os atualizados de uma UHE real. Na simulação com dados atualizados chegou-se a ganhos entre 0,34% até 0,99% na operação da UHE, em comparação com a simulação com os dados derivados do modelo reduzido. Estas quantias significam, em valores monetários, entre R$ 700 mil e R$ 2 milhões anuais (para R$ 50/MWh). Os custos para a obtenção dos dados atualizados no caso em estudo foi quase nulo, no entanto, mesmo que utilizados métodosmais precisos para medição de vazão, que possuem um custo associado, este trabalho indica uma relação baixo custo e alto benefício para a utilização dos dados atualizados obtendo-se o retorno em poucos meses do capital investido / Abstract: Currently used models for optimal dispatch in hydro plants (HP) are based on generation units (GU) efficiency extrapolated from the reduced scale turbine data. An extrapolation from the reduced model data to obtaining real prototype data with excellent precision could occur only if dynamical, geometrical and kinematical similarity between prototype and reduced model would exist. As this is impossible, turbine manufacturers use empirical relations to correct model efficiency in order to reflect in a better way the prototype efficiency. Despite this correction, the turbines¿ real performance can be affected by HPs¿ constructive and operational characteristics, not taken into account by manufacturers; therefore, the real turbine efficiency in a specific GU is not similar to the one obtained from the reduced model by means of extrapolation. Considering this, optimal dispatch using extrapolated reduced model¿s efficiency data will probably not optimize the HP¿s efficiency. More exact efficiency data from the installed GU¿s can be obtained by means of water discharge measurements in penstocks. There was developed a dispatch model in GUs of HPs that treat GUs individually because, probably, their efficiency curves are different. The proposed dispatch model is a mixed integer nonlinear mathematical formulation. The software used to solve the problem was Lingo 8.0, with global and local searchs. Better results were obtained when using global search. This work presents a simulation of optimal dispatch using both kind of data: the extrapolated from the reduced model, and the more detailed data. The simulation that uses the more detailed data from a real HP permitted a gain between 0.34 and 0.99% compared to the one that uses reduced scale model data. These amounts, converted to monetary values, represent between R$700 thousand and R$2 million per year (for a tariff of 50 R$/MWh). The costs for obtaining the more detailed data used in this work are almost null. This work shows the introduction of more precise measurement techniques in GUs implies investments that can rapidly returned. / Mestrado / Mestre em Planejamento de Sistemas Energéticos

Electric grids across the world are experiencing an ever increasing number of extreme events ranging from extreme weather events to cyberattacks. Such extreme events have the potential to cause widespread power outages and even a blackout. A vast majority of power outages impacting the U.S. electric grid impact the distribution system. There are an estimated five million miles of distribution lines in the US electric grid. A majority of these lines are low-clearance overhead lines making them even more susceptible to damage during extreme events. However, this vital component of the U.S. electric grid remained neglected until recently. In recent decades, the integration of distributed energy resources (DERs) such as solar photovoltaic systems and battery energy storage systems at the grid edge have provided a major opportunity for enhancing the resilience of distribution systems. These DERs can be used to restore power supply when the bulk grid becomes unavailable. However, managing the interactions among different types of DERs has been challenging. Low inertia and significant differences in time constants of operation between conventional generation and inverter based resources (IBRs) are some of these challenges. Widespread deployment of microgrid controller capabilities can be a promising solution to manage these interactions. However, due to interoperability and integration challenges of optimization and dynamics control systems, power conversion systems and communication systems, the adoption of microgrids especially in underserved communities has been slow. The research presented in this dissertation is a significant step forward in this direction by proposing an approach which integrates optimal dispatch, sequential microgrid restoration and control algorithms. Potential cyberattack paths are identified by creating a detailed cyber-physical system model for microgrids. A two-tiered intrusion detection system is developed to detect and mitigate cyberattacks within the cyber layer itself. The developed sequential microgrid restoration algorithm coordinates optimal DER dispatch with the operation of legacy devices with no remote control or communication capabilities and net-metered loads with limited communications. By better utilizing the control capabilities of IBRs, reliance on low-latency centralized control algorithms has also been reduced. The developed approach systematically ensures adequate availability of control during dispatch and restoration to maintain microgrid stability. This research can thus pave the way for faster and more cost-effective deployment of microgrids. / Doctor of Philosophy / A U.S. National Academy of Engineering report has described the power grid as the greatest engineering achievement of the 20th century. The power grid is a complex interconnected system consisting of the power transmission system and the distribution system. The power transmission system consists of the power lines seen while driving on the freeways and the large power generating stations consisting of renewable, coal or nuclear power plants. Ensuring the reliable operation of the transmission system has always been a priority. The distribution system on the other hand consists of pole top transformers seen closer to homes which reduce the voltage to levels safe for electrical appliances. It also consists of the millions of miles of low-clearance overhead distribution lines deployed across the U.S. that provide electricity to every household. This critical part of U.S. electricity infrastructure had remained neglected which is the reason why 90% of power outages impact the distribution system. In recent decades, the integration of renewable energy sources like solar systems and battery storage systems has created an unprecedented opportunity for increasing the resilience of distribution systems against extreme events. These energy sources can provide power supply when the transmission system becomes unavailable. However, ensuring safe and reliable integrated operation of these sources with conventional diesel generators especially while isolated from the transmission system is challenging. This is where microgrids, which are self-sufficient miniature power grids, can help. Microgrids provide required control, communication and cybersecurity features necessary for reliable integrated operation of renewable and conventional energy sources. However, the challenges involved with interoperability of these systems has slowed down the deployment of microgrids especially in underserved communities. This is the research gap addressed in this dissertation. This research provides an approach for integrating the optimization, control, power electronics and cybersecurity systems. Reliance on expensive low-latency communication systems is reduced by utilizing the emerging capabilities of power electronics devices used for integrating the renewable energy sources with the electric power grid. Voltage control devices already deployed in the distribution systems which do not have remote control or communication capabilities have also been coordinated with energy sources. The research presented in this dissertation is a significant step forward for increasing access to power supply during outages and for reducing the time and cost of deployment of microgrids.

This Master s Dissertation presents the development of a methodology to optimize the modulation of dispatch of Small Hydro Power Plants (SHPs). The main objective is to minimize the cost of supplying contracts, which comprise both the contracts of energy and the contracts of the use of the transmission and distribution systems by the power utilities. The application of the proposed methodology is technically subject to the operative constraints of the SHPs as well as to the constraints of the substations located in the connection points among utilities and the transmission system. The methodology is also based on the regulation of the Brazilian electrical system. The flow duration curves are taken in order to optimize the dispatch and the load curves from periods of the highest annual demands are considered to represent the distribution system behavior. We used the technique of genetic algorithms to the simulations with real data, from a Brazilian power utility are applied in order to analyze the economic and technical results and then proven the methodology. / Esta dissertação apresenta o desenvolvimento de uma metodologia para a otimização da modulação do despacho de Pequenas Centrais Hidrelétricas (PCHs), com objetivo de minimizar os custos da contratação do suprimento, que compreende a contratação da energia e a contratação do uso dos sistemas de transmissão e ou distribuição, para as concessionárias de distribuidoras de energia elétrica. A aplicação da metodologia proposta, tecnicamente, está sujeita ao atendimento das restrições operativas das PCHs, bem como, das subestações localizadas no ponto de conexão das distribuidoras com a rede básica. A metodologia leva em consideração a regulação do setor elétrico. Para a otimização do despacho, é considerada a vazão afluente do aproveitamento hidrelétrico das PCHs, obtida a partir da curva de permanência de vazões. Representando o comportamento do sistema de distribuição foi usada a curva de carga, no período em que foi registrada a maior demanda anual. Para validação da metodologia, foi utilizada a técnica de algoritmos genéticos para as simulações com dados reais, de uma distribuidora do sul do Brasil foram utilizados e os resultados técnicos e econômicos foram comprovados.