Uncertainty management in multiobjective hydro-thermal self-scheduling under emission considerations

In this paper, a stochastic multiobjective framework is proposed for a day-ahead short-term Hydro Thermal Self-Scheduling (HTSS) problem for joint energy and reserve markets. An efficient linear formulations are introduced in this paper to deal with the nonlinearity of original problem due to the dynamic ramp rate limits, prohibited operating zones, operating services of thermal plants, multi-head power discharge characteristics of hydro generating units and spillage of reservoirs. Besides, system uncertainties including the generating units\u27 contingencies and price uncertainty are explicitly considered in the stochastic market clearing scheme. For the stochastic modeling of probable multiobjective optimization scenarios, a lattice Monte Carlo simulation has been adopted to have a better coverage of the system uncertainty spectrum. Consequently, the resulting multiobjective optimization scenarios should concurrently optimize competing objective functions including GENeration COmpany\u27s (GENCO\u27s) profit maximization and thermal units\u27 emission minimization. Accordingly, the ε-constraint method is used to solve the multiobjective optimization problem and generate the Pareto set. Then, a fuzzy satisfying method is employed to choose the most preferred solution among all Pareto optimal solutions. The performance of the presented method is verified in different case studies. The results obtained from ε-constraint method is compared with those reported by weighted sum method, evolutionary programming-based interactive Fuzzy satisfying method, differential evolution, quantum-behaved particle swarm optimization and hybrid multi-objective cultural algorithm, verifying the superiority of the proposed approach

Metaheuristics for the unit commitment problem : The Constraint Oriented Neighbourhoods search strategy

Tese de mestrado. Faculdade de Engenharia. Universidade do Porto. 199

Virtual power plant models and electricity markets - A review

In recent years, the integration of distributed generation in power systems has been accompanied by new facility operations strategies. Thus, it has become increasingly important to enhance management capabilities regarding the aggregation of distributed electricity production and demand through different types of virtual power plants (VPPs). It is also important to exploit their ability to participate in electricity markets to maximize operating profits. This review article focuses on the classification and in-depth analysis of recent studies that propose VPP models including interactions with different types of energy markets. This classification is formulated according to the most important aspects to be considered for these VPPs. These include the formulation of the model, techniques for solving mathematical problems, participation in different types of markets, and the applicability of the proposed models to real case studies. From the analysis of the studies, it is concluded that the most recent models tend to be more complete and realistic in addition to featuring greater diversity in the types of electricity markets in which VPPs participate. The aim of this review is to identify the most profitable VPP scheme to be applied in each regulatory environment. It also highlights the challenges remaining in this field of study

A reliability based model for generation and transmission expansion planning

This paper presents a mixed integer linear multi-objective model based on information gap decision theory (IGDT), which is used to solve coordinated multiyear generation and transmission expansion planning (G&TEP) problems. The model maximizes the robustness of each uncertain parameter while a maximum allowable budget range is set. Fuel transportation price is considered. The results provide a numerical tool for system planner to help him adjust the appropriate level of robustness for each uncertain parameter of the problem. Extra limits on security, gaseous emission, and fuel availability are considered. A multi-objective method called the ε-constraint method is used here to maximize the robust region of load and investment costs simultaneously. The model is implemented on a six-bus Garver test system and 24 bus IEEE test system. The numerical results show the good performance of the model

A Stochastic Model for Self-scheduling Problem

The unit commitment (UC) problem is a typical application of optimization techniques in the power generation and operation. Given a planning horizon, the UC problem is to find an optimal schedule of generating units, including on/off status and production level of each generating unit at each time period, in order to minimize operational costs, subject to a series of technical constraints. Because technical constraints depend on the characteristics of energy systems, the formulations of the UC problem vary with energy systems. The self-scheduling problem is a variant of the UC problem for the power generating companies to maximize their profits in a deregulated energy market. The deterministic self-scheduling UC problem is known to be polynomial-time solvable using dynamic programming. In this thesis, a stochastic model for the self-scheduling UC problem is presented and an efficient dynamic programming algorithm for the deterministic model is extended to solve the stochastic model. Solutions are compared to those obtained by traditional mixed integer programming method, in terms of the solution time and solution quality. Computational results show that the extended algorithm can obtain an optimal solution faster than Gurobi mixed-integer quadratic solver when solving a stochastic self-scheduling UC problem with a large number of scenarios. Furthermore, the results of a simulation experiment show that solutions based on a large number of scenarios can generate more average revenue or less average loss

Parameterisation effect on the behaviour of a head-dependent hydro chain using a nonlinear model

This paper is on the problem of short-term hydro scheduling (STHS), particularly concerning a head-dependent hydro chain. We use a method based on nonlinear programming (NLP), namely quadratic programming, to consider hydroelectric power generation a function of water discharge and of the head. The method has been applied successfully to solve a test case based on a realistic cascaded hydro system with a negligible computational time requirement and is also applied to show that the role played by reservoirs in the hydro chain do not depend only on their relative position. As a new contribution to earlier studies, which presented reservoir operation rules mainly for medium and long-term planning procedures, we show that the physical data defining hydro chain parameters used in the nonlinear model have an effect on the STHS, implying different optimal storage trajectories for the reservoirs accordingly not only with their position in the hydro chain but also with the new parameterisation defining the data for the hydro system. Moreover, considering head dependency in the hydroelectric power generation, usually neglected for hydro plants with a large storage capacity, provides a better short-term management of the conversion of the potential energy available in the reservoirs into electric energy, which represents a major advantage for the hydroelectric utilities in a competitive electricity market

Strategic planning of electricity systems: Integrating renewable energies

Tese de Doutoramento - Programa Doutoral em Engenharia Industrial e Sistemas (PDEIS)The decision making process applied to the energy sector, particularly to the electricity sector, is complex and frequently requires the use of optimization models to deal with problems in the scope of electricity planning. The continuous growth of renewable energy sources (RES) to generate electricity became sustainable over the last years. This growth is justified by the increasing concerns related to the security of supply, the reduction of external energy dependency of most European countries, including Portugal, and the reduction of greenhouse gases emissions. Despite of the RES benefits, their integration is characterized by the difficulties on forecasting and variable electricity output. These difficulties bring considerable challenges to the electricity system management and to its planning. This work is focused on the assessment of the RES impacts on the electricity system and on its integration in the long and short-term electricity planning. The main goals of this work are to analyse in which way the growth of RES can affect the electricity system and its power plants, and also to propose new optimization models for the strategic planning of the electricity system, which are able to recognize and include RES impacts. This will provide the decision maker with tools that will support the design of long-term scenarios for the electricity sector. According to the outlined goals, four different optimization models were developed. All models were tested for a mixed hydro-thermal-wind power system, with characteristics close to the Portuguese one. The first one was proposed for the long-term strategic electricity power planning and a 10 years planning period was considered. Its usefulness was demonstrated by applying it for the analysis of the wind power integration in the electricity system. The second one, with a short-term horizon, aimed to solve the problem of the commissioning of power plants based on the available resources. The implementation of this model showed that modelling the electricity power systems requires a large set of constraints and a large number of data and information, resulting in significant computational effort to obtain a optimal solution. The development of a third model, a simplified approach of the short-term model, became therefore necessary. As previously, both short-term model and its simplified approach were used for the analysis of the impacts of wind power in the electricity system and in the operation of the different power plants. The last model resulted from the combination of the strategic electricity power planning model with the simplified model proposed for the commissioning of the power plants. The goal of this fourth model is to allow the inclusion of RES impacts in the design of scenarios for the electricity system, for a 10 years planning period. The models application demonstrated the need to acknowledge and include the impacts of RES integration, particularly wind power, on the strategic electricity expansion planning. Throughout the work, the complexity of models was evidenced along with the difficulties that non-experienced users may face when applying them. A user-friendly platform enabling researchers and stakeholders to deal with electricity planning problems in a simpler but reliable way was then proposed, resulting in an important contribution for the effective dissemination and usage of these models.A tomada de decisão no sector da energia, e em particular no sector da eletricidade, é uma atividade complexa, sendo frequentemente suportada em modelos de otimização, para apoio à resolução de problemas relativos ao planeamento elétrico. O crescimento da utilização das fontes de energia renováveis para a produção de eletricidade tem sido consistente nos últimos anos, sendo este crescimento justificado pelas preocupações relativas à segurança do abastecimento, passando por estratégias de diversificação de tecnologias e fornecedores, pela necessidade de redução da dependência energética externa de diversos paises Europeus, onde se inclui o caso português, e pelos objetivos de redução dos gases com efeito de estufa. Apesar dos seus benefícios, a integração das energias renováveis está frequentemente associada à dificuldade de previsão da produção de eletricidade e à produção variável, trazendo assim desafios consideráveis à gestão do sistema elétrico e ao seu planeamento. Este trabalho centra-se na avaliação dos impactos das energias renováveis nos sistemas elétricos e na sua inclusão no planeamento elétrico de curto e longo prazo. Tem assim como objetivos principais analisar de que modo o crescimento das energias renováveis poderá afetar o sistema elétrico e as diferentes unidades produtoras, bem como propor novos modelos de otimização para planeamento estratégico para o setor elétrico que permitam reconhecer e incluir estes impactos, dotando assim o decisor de ferramentas que o possam apoiar da definição de cenários estratégicos de longo prazo. De acordo com os objetivos traçados, são apresentados quatro diferentes modelos de otimização. Todos estes modelos foram testados para um sistema elétrico com caracteristicas próximas do caso português, detacando-se as componentes hídrica, térmica e eólica. O primeiro modelo visa o planeamento estratégico a longo prazo resultando na apresentação e caracterização de cenários para o setor elétrico para um período de 10 anos, tendo sido demonstrada a sua aplicação para a análise da integração da energia eólica no sistema. O segundo modelo utiliza um horizonte temporal de curto prazo, tendo como objetivo apoiar a resolução do problema de comissionamento das unidades de geração eléctrica com base nos recursos disponíveis. A sua implementação demonstrou que a modelação dos sistemas de geração de energia eléctrica pressupõe um conjunto de restrições e um elevado número de dados e informações que resultam num esforço computacional significativo. Desta forma, surgiu a necessidade de desenvolver um terceiro modelo que consiste numa versão simplificada deste modelo de curto-prazo. Ambos os modelos de curto prazo, foram também utilizados para a análise dos impactos da energia eólica no funcionamento das diferentes unidades de produção de eletricidade. O último modelo desenvolvido resulta da combinação do modelo estratégico de expansão do sistema elétrico com o modelo aplicado ao problema do comissionamento das unidades de geração eléctrica, tendo como objetivo ter em consideração os impactos das energias renováveis na definição de cenários para o setor elétrico para um período de 10 anos. Da aplicação dos modelos fica demonstrada a importância de reconhecer e incluir no planeamento elétrico estratégico de longo prazo os impactos resultantes da integração de fontes renováveis de energia de produção variável, e em particular da energia eólica, nos sistemas elétricos. Fica ainda evidente, a complexidade dos modelos e a dificuldade de aplicação por utilizadores menos experientes. Resulta por isso como uma importante contribuição, o desenvolvimento de uma aplicação gráfica com interface amigável que deverá permitir a ampla disseminação dos modelos desenvolvidos e sua adaptação a diferentes sistemas elétricos