5 research outputs found

    Optimal Bidding Strategies of Wind-Thermal Power Producers

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    This paper addresses a stochastic mixed-integer linear programming model for solving the self-scheduling problem of a thermal and wind power producer acting in an electricity market. Uncertainty on market prices and on wind power is modelled via a scenarios set. The mathematical formulation of thermal units takes into account variable and start-up costs and operational constraints like: ramp up/down limits and minimum up/down time limits. A mixed-integer linear formulation is used to obtain the offering strategies of the coordinated production of thermal and wind energy generation, aiming the profit maximization. Finally, a case study is presented and results are discussed

    Self-scheduling of wind-thermal systems using a stochastic MILP approach

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    In this work a stochastic (Stoc) mixed-integer linear programming (MILP) approach for the coordinated trading of a price-taker thermal (Ther) and wind power (WP) producer taking part in a day-ahead market (DAM) electricity market (EMar) is presented. Uncertainty (Uncer) on electricity price (EPr) and WP is considered through established scenarios. Thermal units (TU) are modelled by variable costs, start-up (ST-UP) technical operating constraints and costs, such as: forbidden operating zones, minimum (Min) up/down time limits and ramp up/down limits. The goal is to obtain the optimal bidding strategy (OBS) and the maximization of profit (MPro). The wind-Ther coordinated configuration (CoConf) is modelled and compared with the unCoConf. The CoConf and unCoConf are compared and relevant conclusions are drawn from a case study

    Optimal Scheduling of Joint Wind-Thermal Systems

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    This paper is about the joint operation of wind power with thermal power for bidding in day-ahead electricity market. Start-up and variable costs of operation, start-up/shut-down ramp rate limits, and ramp-up limit are modeled for the thermal units. Uncertainty not only due to the electricity market price, but also due to wind power is handled in the context of stochastic mix integer linear programming. The influence of the ratio between the wind power and the thermal power installed capacities on the expected profit is investigated. Comparison between joint and disjoint operations is discussed as a case study

    Incerteza e risco em coordenação térmica-eólica por metodologia estocástica

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    A tese é uma contribuição no âmbito do problema para a determinação de estratégias de oferta ótimas a submeter em mercado diário de eletricidade, considerando incerteza e risco. A metodologia proposta tem em consideração o caráter estocástico de variáveis envolvidas no problema e constitui um suporte racional à exploração de coordenação eólica-térmica. A metodologia de otimização estocástica de dois estados com recurso é a base para o desenvolvimento proposto para suporte à tomada de decisão de uma empresa produtora de energia elétrica por coordenação térmica-eólica sujeita a eventos aleatórios. Estes eventos são as fontes de incerteza associadas com o mercado de eletricidade e com a disponibilidade de energia eólica, caracterizando a aleatoriedade do problema em estudo. As fontes de incerteza são descritas por um conjunto de cenários eventualmente factíveis ou com potencialidade para qualificar boas decisões. A metodologia proposta conduz a uma exploração mais fidedigna em ambiente competitivo, acedendo com níveis superiores de racionalidade a estratégias de licitação para o mercado, tendo em consideração a ponderação de risco na tomada de decisão. Ainda, a metodologia tem em consideração a computação de aspetos relevantes, como a emissão antropogénica e o cumprimento do regulamento do UCTE relativo a segurança no fornecimento. Casos de estudos são apresentados permitindo concluir sobre o interesse e as vantagens que a metodologia oferece; Uncertainty and Risk on Wind-Thermal Coordination by Stochastic Methodology Abstract: This thesis is a contribution in the context of the problem of the optimal offer strategies determination to submit in electricity markets considering uncertainty and risk. The proposed method takes into account the stochastic character of variables involved in the problem and provides a rational support for the operation of wind-thermal coordination. Stochastic optimization of two-stages with recourse modelling is the basis for the proposed development to support the decision making of a company producing electricity by wind-thermal coordination subject to random events. These events are the sources of uncertainty associated with the electricity market and the availability of wind power characterizing the randomness of the problem under study. The sources of uncertainty are described by a set of possibly achievable scenarios or with potential to qualify good decisions. The proposed method leads to a more accurate operating in a competitive environment by accessing with higher levels of rationality bidding strategies to submit in the market, having a risk weighting consideration in decision making. Further, the methodology takes into account relevant aspects to be computed, such as anthropogenic emissions and compliance with the UCTE regulation on the security of supply. Case studies are presented allowing to conclude on the interest and the advantages offered by the methodology

    Optimal Bidding Strategies of Wind-Thermal Power Producers

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    Part 14: Optimization in Energy ManagementInternational audienceThis paper addresses a stochastic mixed-integer linear programming model for solving the self-scheduling problem of a thermal and wind power producer acting in an electricity market. Uncertainty on market prices and on wind power is modelled via a scenarios set. The mathematical formulation of thermal units takes into account variable and start-up costs and operational constraints like: ramp up/down limits and minimum up/down time limits. A mixed-integer linear formulation is used to obtain the offering strategies of the coordinated production of thermal and wind energy generation, aiming the profit maximization. Finally, a case study is presented and results are discussed
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