Variable generator output levels from renewable energies is an important technical obstacle to the transition from fossil fuels to renewable resources. Super grids and smart grids are among the most effective solutions to mitigate generation variability. In a super grid, electric utilities within an interconnected system can share generation and reserve units so that they can produce electricity at a lower overall cost. Smart grids, in particular demand response programs, enable flexible loads such as plug-in electric vehicles and HVAC systems to consume electricity preferntially in a grid-friendly way that assists the grid operator to maintain the power balance. These solutions, in conjunction with energy storage systems, can facilitate renewable integration. This study aims to provide an understanding of the achievable benefits from integrating demand response into wholesale and retail electricity markets, in particular in the presence of significant amounts of variable generation. Among the options for control methods for demand response, market-based approaches provide a relatively efficient use of load flexibility, without restricting consumers' autonomy or invading their privacy. In this regard, a model of demand response integration into bulk electric grids is presented to study the interaction between variable renewables and demand response in the double auction environment, on an hourly basis. The cost benefit analysis shows that there exists an upper limit of renewable integration, and that additional solutions such as super grids and/or energy storage systems are required to go beyond this threshold. The idea of operating an interconnection in an unified (centralized) manner is also explored. The traditional approach to the unit commitment problem is to determine the dispatch schedule of generation units to minimize the operation cost. However, in the presence of price-sensitive loads (market-based demand response), the maximization of economic surplus is a preferred objective to the minimization of cost. Accordingly, a surplus-maximizing hour-ahead scheduling problem is formulated, and is then tested on a system that represents a 20-area reduced model of the North America Western Interconnection for the planning year 2024. The simulation results show that the proposed scheduling method reduces the total operational costs substantially, taking advantage of renewable generation diversity. The value of demand response is more pronounced when ancillary services (e.g. real-time power balancing and voltage/frequency regulation) are also included along with basic temporal load shifting. Relating to this, a smart charging strategy for plug-in electric vehicles is developed that enables them to participate in a 5-minute retail electricity market. The cost reduction associated with implementation of this charging strategy is compared to uncontrolled charging. In addition, an optimal operation method for thermostatically controlled loads is developed that reduces energy costs and prevents grid congestion, while maintaining the room temperature in the comfort range set by the consumer. The proposed model also includes loads in the energy imbalance market. The simulation results show that market-based demand response can contribute to a significant cost saving at the sub-hourly level (e.g. HVAC optimal operation), but not at the super-hourly level. Therefore, we conclude that demand response programs and super grids are complementary approaches to overcoming renewable generation variation across a range of temporal and spatial scales. / Graduate / 0791 / sahandbehboodi@gmail.com

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.

Vários países ao redor do mundo têm procurado cada vez mais diversificar suas matrizes elétricas com o objetivo de diminuir a dependência de combustíveis fósseis e reduzir as emissões dos gases responsáveis pelo agravamento do efeito estufa na atmosfera. Com isso, tem crescido a participação de algumas fontes renováveis de energia que, até duas décadas atrás, não ocupavam lugar de destaque na matriz elétrica mundial, como por exemplo, a energia eólica. O gás natural, embora seja um recurso fóssil, é considerado menos poluente e este tem substituído os derivados de petróleo em várias aplicações, entre elas na geração de eletricidade. O Peru, no intuito de atender a sua demanda crescente por eletricidade, vem buscando novas alternativas energéticas, como por exemplo, a energia eólica e, em maior escala, a termeletricidade com o uso do gás natural, cuja disponibilidade aumentou consideravelmente após o início da exploração das jazidas de Camisea. O presente trabalho tem o objetivo de avaliar, tanto em um cenário de curto prazo como de longo prazo, o impacto de uma maior inserção da energia eólica e a expansão das térmicas a gás natural na operação econômica do sistema hidrotérmico Peruano. Esta avaliação é realizada com base na análise das seguintes figuras de mérito: custo marginal de operação (CMO), custo de operação do sistema, deslocamento de geração térmica e perfil de despacho de geração das unidades geradoras (MWh). Foram realizadas simulações do sistema elétrico peruano com e sem participação da geração eólica e a partir dos resultados obtidos, efetuou-se uma análise comparativa com base nos cenários propostos. Para efetuar as simulações foi utilizada a ferramenta computacional denominada PERSEO. Este programa, utilizado pelo setor Elétrico Peruano, permite simular o sistema hidrotérmico com característica de representação de um sistema multi-reservatório, multi-nodal e multi-cenário utilizando programação dinâmica estocástica. O trabalho também apresenta as principais características do Setor Elétrico Peruano enfocando sua evolução, desafios e plano de expansão, onde, com base neste se elaborou as simulações propostas. Os resultados obtidos com a inserção da geração eólica, baseados nas premissas e cenários propostos, foram considerados positivos. Houve uma diminuição média anual de 18% nos custos marginais de operação, o que representa uma diminuição nos custos de operação em torno de US$ 28 milhões ao ano, ou seja, 4% do total. Com relação à geração térmica a gás natural, o impacto da maior inserção desta no sistema também foi positivo, com redução dos custos de operação do sistema e deslocamento de geração térmica mais poluente (óleo combustível e carvão mineral). Adicionalmente efetuou-se uma análise do potencial de complementaridade da geração eólica e hídrica e do plano de expansão da geração hídrica com exportação de energia elétrica para o Brasil. / Several countries around the world have increasingly sought to diversify their electrical matrix in order to reduce dependence on fossil fuels and reduce emissions of gases responsible for worsening greenhouse effect in the atmosphere. As a result, has grown the participation of some renewable energy sources that until two decades ago did not occupied a prominent place in the world energy matrix, such as wind power. The Natural gas, although it is a fossil resource, is considered less pollutant and it has replaced petroleum products in various applications among them in the generation of electricity. The Peru, in order to meet its growing demand for electricity, has been seeking new alternatives between them wind power, and on a larger scale, thermoelectricity with the use of natural gas whose availability has increased considerably since the beginning of the exploitation of the fields of Camisea. This study has the objective of evaluate, both in a short-term outlook and long-term the impact of a greater insertion of wind energy and expansion of natural gas thermal on the economic operation of the hydrothermal Peruvian system. This evaluation is performed based on the analysis of the following arguments of merit: the marginal cost of operation (CMO), cost of system operation, displacement of thermal generation and profile and generation dispatch of generating units (MWh). Simulations of Peruvian electric system \"with\" and \"without\" participation of wind generation were realized and from the results obtained, it was performed a comparative analysis based on the proposed scenarios. To effectuate the simulations, it was used a computational tool called PERSEO. This program, used by the Peruvian electricity sector, allows simulating the hydrothermal system with features of a representation of system multi-reservoir, multi-nodal and multi-scenario using stochastic dynamic programming. The study also presents the main characteristics of the Peruvian Electric Sector focusing on its evolution, challenges and expansion plan, where, based on this proposal were elaborated the simulations. The results obtained with the insertion the wind generation, based on premises and proposed scenarios, were considered positive. There was an average annual decline of 18% in the marginal costs of operation, which represents a decrease in operating costs around U.S. $ 28 million a year, i.e. 4% of the total. With respect to natural gas thermal generation, the impact of greater insertion of this in the system was also positive, with reduction the cost system operation and displacement of more polluting thermal generation (fuel oil and coal). Additionally it was performed an analysis of the complementarity potential of generation wind and hydro and of the plan for expansion of hydro power with electrical energy export to Brazil.

Vários países ao redor do mundo têm procurado cada vez mais diversificar suas matrizes elétricas com o objetivo de diminuir a dependência de combustíveis fósseis e reduzir as emissões dos gases responsáveis pelo agravamento do efeito estufa na atmosfera. Com isso, tem crescido a participação de algumas fontes renováveis de energia que, até duas décadas atrás, não ocupavam lugar de destaque na matriz elétrica mundial, como por exemplo, a energia eólica. O gás natural, embora seja um recurso fóssil, é considerado menos poluente e este tem substituído os derivados de petróleo em várias aplicações, entre elas na geração de eletricidade. O Peru, no intuito de atender a sua demanda crescente por eletricidade, vem buscando novas alternativas energéticas, como por exemplo, a energia eólica e, em maior escala, a termeletricidade com o uso do gás natural, cuja disponibilidade aumentou consideravelmente após o início da exploração das jazidas de Camisea. O presente trabalho tem o objetivo de avaliar, tanto em um cenário de curto prazo como de longo prazo, o impacto de uma maior inserção da energia eólica e a expansão das térmicas a gás natural na operação econômica do sistema hidrotérmico Peruano. Esta avaliação é realizada com base na análise das seguintes figuras de mérito: custo marginal de operação (CMO), custo de operação do sistema, deslocamento de geração térmica e perfil de despacho de geração das unidades geradoras (MWh). Foram realizadas simulações do sistema elétrico peruano com e sem participação da geração eólica e a partir dos resultados obtidos, efetuou-se uma análise comparativa com base nos cenários propostos. Para efetuar as simulações foi utilizada a ferramenta computacional denominada PERSEO. Este programa, utilizado pelo setor Elétrico Peruano, permite simular o sistema hidrotérmico com característica de representação de um sistema multi-reservatório, multi-nodal e multi-cenário utilizando programação dinâmica estocástica. O trabalho também apresenta as principais características do Setor Elétrico Peruano enfocando sua evolução, desafios e plano de expansão, onde, com base neste se elaborou as simulações propostas. Os resultados obtidos com a inserção da geração eólica, baseados nas premissas e cenários propostos, foram considerados positivos. Houve uma diminuição média anual de 18% nos custos marginais de operação, o que representa uma diminuição nos custos de operação em torno de US$ 28 milhões ao ano, ou seja, 4% do total. Com relação à geração térmica a gás natural, o impacto da maior inserção desta no sistema também foi positivo, com redução dos custos de operação do sistema e deslocamento de geração térmica mais poluente (óleo combustível e carvão mineral). Adicionalmente efetuou-se uma análise do potencial de complementaridade da geração eólica e hídrica e do plano de expansão da geração hídrica com exportação de energia elétrica para o Brasil. / Several countries around the world have increasingly sought to diversify their electrical matrix in order to reduce dependence on fossil fuels and reduce emissions of gases responsible for worsening greenhouse effect in the atmosphere. As a result, has grown the participation of some renewable energy sources that until two decades ago did not occupied a prominent place in the world energy matrix, such as wind power. The Natural gas, although it is a fossil resource, is considered less pollutant and it has replaced petroleum products in various applications among them in the generation of electricity. The Peru, in order to meet its growing demand for electricity, has been seeking new alternatives between them wind power, and on a larger scale, thermoelectricity with the use of natural gas whose availability has increased considerably since the beginning of the exploitation of the fields of Camisea. This study has the objective of evaluate, both in a short-term outlook and long-term the impact of a greater insertion of wind energy and expansion of natural gas thermal on the economic operation of the hydrothermal Peruvian system. This evaluation is performed based on the analysis of the following arguments of merit: the marginal cost of operation (CMO), cost of system operation, displacement of thermal generation and profile and generation dispatch of generating units (MWh). Simulations of Peruvian electric system \"with\" and \"without\" participation of wind generation were realized and from the results obtained, it was performed a comparative analysis based on the proposed scenarios. To effectuate the simulations, it was used a computational tool called PERSEO. This program, used by the Peruvian electricity sector, allows simulating the hydrothermal system with features of a representation of system multi-reservoir, multi-nodal and multi-scenario using stochastic dynamic programming. The study also presents the main characteristics of the Peruvian Electric Sector focusing on its evolution, challenges and expansion plan, where, based on this proposal were elaborated the simulations. The results obtained with the insertion the wind generation, based on premises and proposed scenarios, were considered positive. There was an average annual decline of 18% in the marginal costs of operation, which represents a decrease in operating costs around U.S. $ 28 million a year, i.e. 4% of the total. With respect to natural gas thermal generation, the impact of greater insertion of this in the system was also positive, with reduction the cost system operation and displacement of more polluting thermal generation (fuel oil and coal). Additionally it was performed an analysis of the complementarity potential of generation wind and hydro and of the plan for expansion of hydro power with electrical energy export to Brazil.

Carbon dioxide (CO2) is the most important component of Greenhouse Gas (GHG) that causes global warming and sea-level rising. Thermal power plants dominate electric power generation in the world, and has been reported to be the major contributor of CO2 emission. To prevent the related global warming caused by GHG emission, carbon quota trading is implemented and becomes a gradually arising market. This thesis proposed a research focused on the relationship between the carbon trading scheme and dynamic economic dispatch (DED) problem for the public utility. A model of the carbon trading market was investigated and introduced into DED problem incorporating wind and solar power plant. A refined particle swarm optimization (PSO) algorithm, PSO with time-varying acceleration coefficients (PSO-TVAC), is applied to determine the DED strategy with the incorporation of independent power providers (IPPs) and green power plant. The model of the carbon trading was considered in the DED problem. Carbon reduction is treated as the inner-cost of utility, and the fictitious carbon quotas can be resold to the market, while the energy shortage can be satisfied by purchasing quotas from the market. In order to avoid premature convergence of the original PSO, the PSO-TVAC method is introduced to improve the searching efficiency.

The future smart grid is envisioned as a large scale cyber-physical system encompassing advanced power, computing, communications and control technologies. This work provides comprehensive accounts of the application with optimization methods, probability theory, commitment and dispatching technologies for addressing open problems in three emerging areas that pertain to the smart grid: unit commitment, service restoration problems in microgrid systems, and charging services for the plug-in hybrid electric vehicle (PHEV) markets. The work on the short-term scheduling problem in renewable-powered islanded microgrids is to determine the least-cost unit commitment (UC) and the associated dispatch, while meeting electricity load, environmental and system operating requirements. A novel probability-based concept, {\em probability of self-sufficiency}, is introduced to indicate the probability that the microgrid is capable of meeting local demand in a self-sufficient manner. Furthermore, we make the first attempt in approaching the mixed-integer UC problem from a convex optimization perspective, which leads to an analytical closed-form characterization of the optimal commitment and dispatch solutions. The extended research of the renewable-powered microgrid in the connection mode is the second part of this work. In this situation, the role of microgrid is changed to be either an electricity provider selling energy to the main grid or a consumer purchasing energy from the main grid. This interaction with the main grid completes work on the scheduling schemes. Third, a microgrid should be connected with the main grid most of the time. However, when a blackout of the main grid occurs, how to guarantee reliability in a microgrid as much as possible becomes an immediate question, which motivates us to investigate the service restoration in a microgrid, driven islanded by an unscheduled breakdown from the main grid. The objective is to determine the maximum of the expected restorative loads by choosing the best arrangement of the power network configurations immediately from the beginning of the breakdown all the way to the end of the island mode. Lastly, the work investigating the pricing strategy in future PHEV markets considers a monopoly market with two typical service classes. The unique characteristics of battery charging result in a piecewise linear quality of service model. Resorting to the concept of subdifferential, some theoretical results, including the existence and uniqueness of the subscriber equilibrium as well as the convergence of the corresponding subscriber dynamics are established. In the course of developing revenue-maximizing pricing strategies for both service classes, a general tradeoff has been identi ed between monetization and customer acquisition. / Graduate

Today the modern power system is more dynamic and its operation is a subject to a number of constraints that are reflected in various management and planning tools used by system operators. In the case of hourly generation planning, Economic Dispatch (ED) allocates the outputs of all committed generating units, which are previously identified by the solution of the Unit Commitment (UC) problem. Thus, the accurate solutions of the ED and UC problems are essential in order to operate the power system in an economic and efficient manner. A number of computation techniques have progressively been proposed to solve these critical issues. One of them is a Particle Swarm Optimisation (PSO), which belongs to the evolutionary computation techniques, and it has attracted a great attention of the research community since it has been found to be extremely effective in solving a wide range of engineering problems. The attractive characteristics of PSO include: ease of implementation, fast convergence compared with the traditional evolutionary computation techniques and stable convergence characteristic. Although the PSO algorithms can converge very quickly towards the optimal solutions for many optimisation problems, it has been observed that in problems with a large number of suboptimal areas (i.e. multi-modal problems), PSO could get trapped in those local minima, including ED and UC problems. Aiming at enhancing the diversity of the traditional PSO algorithms, this thesis proposes a method of combining the PSO algorithms with a real-valued natural mutation (RVM) operator to enhance the global search capability and investigate the performance of the proposed algorithm compared with the standard PSO algorithms and other algorithms. Prior to applying to ED and UC problems, the proposed method is tested with some selected mathematical functions where the results show that it can avoid being trapped in local minima. The proposed methodology is then applied to ED and UC problems, and the obtained results show that it can provide solutions with good accuracy and stable convergence characteristic with simple implementation and satisfactory calculation time. Furthermore, the sensitivity analysis of PSO parameters has been studied so as to investigate the response of the proposed method to the parameter variations, especially in both ED and UC problems. The outcome of this research shows that the proposed method succeeds in dealing with the PSO' s drawbacks and also shows the superiority over the traditional PSO algorithms and other methods in terms of high quality solutions, stable convergence characteristic, and robustness.

abstract: Traditional deterministic reserve requirements rely on ad-hoc, rule of thumb methods to determine adequate reserve in order to ensure a reliable unit commitment. Since congestion and uncertainties exist in the system, both the quantity and the location of reserves are essential to ensure system reliability and market efficiency. The modeling of operating reserves in the existing deterministic reserve requirements acquire the operating reserves on a zonal basis and do not fully capture the impact of congestion. The purpose of a reserve zone is to ensure that operating reserves are spread across the network. Operating reserves are shared inside each reserve zone, but intra-zonal congestion may block the deliverability of operating reserves within a zone. Thus, improving reserve policies such as reserve zones may improve the location and deliverability of reserve. As more non-dispatchable renewable resources are integrated into the grid, it will become increasingly difficult to predict the transfer capabilities and the network congestion. At the same time, renewable resources require operators to acquire more operating reserves. With existing deterministic reserve requirements unable to ensure optimal reserve locations, the importance of reserve location and reserve deliverability will increase. While stochastic programming can be used to determine reserve by explicitly modelling uncertainties, there are still scalability as well as pricing issues. Therefore, new methods to improve existing deterministic reserve requirements are desired. One key barrier of improving existing deterministic reserve requirements is its potential market impacts. A metric, quality of service, is proposed in this thesis to evaluate the price signal and market impacts of proposed hourly reserve zones. Three main goals of this thesis are: 1) to develop a theoretical and mathematical model to better locate reserve while maintaining the deterministic unit commitment and economic dispatch structure, especially with the consideration of renewables, 2) to develop a market settlement scheme of proposed dynamic reserve policies such that the market efficiency is improved, 3) to evaluate the market impacts and price signal of the proposed dynamic reserve policies. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2015

The integration of variable renewable energy sources (VRE) is likely to cause fundamental and structural changes to the operation of future power systems. In the United Kingdom (UK), large amounts of price-insensitive and variable-output wind generation is expected to be deployed to contribute towards renewable energy and carbon dioxide (CO2) emission targets. Wind generation, with near-zero marginal costs, limited predictability, and a limited ability to provide upward dispatch, displaces price-setting thermal power plants, with higher marginal costs, changing flexibility and reserve requirements. New-build, commercial-scale, and low-carbon generation capacity, such as CO2 capture and storage (CCS) and nuclear, may impact power system flexibility and ramping capabilities. Low-carbon generation portfolios with price-sensitive thermal power plants and energy storage are therefore likely to be required to manage increased levels of variability and uncertainty at operational timescales. This work builds on a high-resolution wind reanalysis dataset of UK wind sites. The locations of existing and proposed wind farms are used to produce plausible and internally consistent wind deployment scenarios that represent the spatial distribution of future UK wind capacity. Temporally consistent electricity demand data is used to characterise and assess demand-wind variability and net demand ramp events. A unit commitment and economic dispatch (UCED) model is developed to evaluate the likely operating regimes of thermal power plants and CCS-equipped units across a range of future UK wind scenarios. Security constraints for reserve and power plant operating constraints, such as power output limits, ramp rates, minimum up/down times, and start-up times, ensure the operational feasibility of dispatch schedules. The load factors, time spent at different loads, and the ramping and start-up requirements of thermal power plants are assessed. CO2 duration curves are developed to assess the impacts of increasing wind capacity on the distribution of CO2 emissions. A sensitivity analysis investigates the impacts of part-load efficiency losses, ramp rates, minimum up/down times, and start-up/shut-down costs on power plant operating regimes and flexibility requirements. The interactions between a portfolio of energy storage units and flexible CO2 capture units are then explored. This multi-disciplinary research presents a temporally-explicit and detailed assessment of operational flexibility requirements at full 8760 hour resolution, highlighting the non-linear impacts of increasing wind capacity. The methodological framework presented here uses high spatial-and temporal-resolution wind data but is expected to provide useful insights for other VREbased power systems to mitigate the implications of inadequate flexibility.

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