Metodologia de otimização estocástica para coordenação eólico-fotovoltaica

Esta dissertação incide sobre o tema da coordenação entre sistemas eólicos e fotovoltaicos que participam no mercado de eletricidade. A incerteza da potência eólica e fotovoltaica é uma caraterística predominante nesta coordenação, devendo ser considerada no planeamento ótimo de sistemas eólico-fotovoltaicos. A fim de modelizar a incerteza é apresentada uma metodologia de otimização estocástica baseada em programação linear para maximizar o lucro esperado de uma empresa produtora de energia elétrica que participa no mercado diário. A coordenação entre sistemas eólicos e fotovoltaicos visa mitigar os desequilíbrios de energia, resultantes das ofertas horárias submetidas no mercado diário e, consequentemente, reduzir as penalizações financeiras. Os resultados da coordenação entre um sistema eólico e um sistema fotovoltaico são comparados com os resultados obtidos para a operação não coordenada. Estes resultados permitem concluir que a metodologia desenvolvida aplicada à coordenação apresenta um lucro esperado superior ao lucro obtido para a operação não coordenada; Abstract Stochastic Optimization Methodology for Wind-Photovoltaic Coordination This dissertation focuses on the issue of coordination between wind and photovoltaic systems participating in electricity markets. The uncertainty of wind and photovoltaic power is a main characteristic of these systems, which must be included in the optimal scheduling of the coordination of wind with photovoltaic systems. In order to model the uncertainty is presented a stochastic approach based on linear programming to maximize the profit of a wind photovoltaic power producer which participates in electricity markets. The coordination of wind with photovoltaic systems aims to mitigate the energy deviations, as a result of the participation in day-ahead market and therefore reducing economic penalties. The results obtained by the coordination are compared to results obtained by the separated operation of wind and photovoltaic systems. The results allow concluding that the proposed approach applied to the coordination presents an expected profit higher than the expected profit without coordination.

Short-Term Trading for a Wind-PV Power Producer in an Electricity Market

This paper deals with the problem of coordinated trading of wind and photovoltaic systems in order to find the optimal bid to submit in a pool-based electricity market. The coordination of wind and photovoltaic systems presents uncertainties not only due to electricity market prices, but also with wind and photovoltaic power forecast. Electricity markets are characterized by financial penalties in case of deficit or excess of generation. So, the aim o this work is to reduce these financial penalties and maximize the expected profit of the power producer. The problem is formulated as a stochastic linear programming problem. The proposed approach is validated with real data of pool-based electricity market of Iberian Peninsula.

Bidding and Optimization Strategies for Wind-PV Systems in Electricity Markets

The variability in non-dispatchable power generation raises important challenges to the integration of renewable energy sources into the electricity power grid. This paper provides the coordinated trading of wind and photovoltaic energy to mitigate risks due to the wind and solar power variability, electricity prices, and financial penalties arising out the generation shortfall and surplus. The problem of wind-photovoltaic coordinated trading is formulated as a linear programming problem. The goal is to obtain the optimal bidding strategy that maximizes the total profit. The wind-photovoltaic coordinated operation is modeled and compared with the uncoordinated operation. A comparison of the models and relevant conclusions are drawn from an illustrative case study of the Iberian day-ahead electricity market.

Coordinated Scheduling of Wind-Thermal Gencos in Day-Ahead Markets

This paper presents a stochastic mixed-integer linear programming approach for solving the self-scheduling problem of a price-taker thermal and wind power producer taking part in a pool-based electricity market. Uncertainty on electricity price and wind power is considered through a set of scenarios. Thermal units are modeled by variable costs, start-up costs and technical operating constraints, such as: ramp up/down limits and minimum up/down time limits. An efficient mixed-integer linear program is presented to develop the offering strategies of the coordinated production of thermal and wind energy generation, aiming to maximize the expected profit. A case study with data from the Iberian Electricity Market is presented and results are discussed to show the effectiveness of the proposed approach.

Bidding and Optimization Strategies for Wind-PV Systems in Electricity Markets Assisted by CPS

The variability in non-dispatchable power generation raises important challenges to the integration of renewable energy sources into the electricity power grid. This paper provides the coordinated trading of wind and photovoltaic energy assisted by a cyber-physical system for supporting management decisions to mitigate risks due to the wind and solar power variability, electricity prices, and financial penalties arising out the generation shortfall and surplus. The problem of wind-photovoltaic coordinated trading is formulated as a stochastic linear programming problem. The goal is to obtain the optimal bidding strategy that maximizes the total profit. The wind-photovoltaic coordinated operation is modelled and compared with the uncoordinated operation. A comparison of the models and relevant conclusions are drawn from an illustrative case study of the Iberian day-ahead electricity market.

Bidding Decision of Wind-Thermal GenCo in Day-Ahead Market

This paper deals with the self-scheduling problem of a price-taker having wind and thermal power production and assisted by a cyber-physical system for supporting management decisions in a day-ahead electric energy market. The self-scheduling is regarded as a stochastic mixed-integer linear programming problem. Uncertainties on electricity price and wind power are considered through a set of scenarios. Thermal units are modelled by start-up and variable costs, furthermore constraints are considered, such as: ramp up/down and minimum up/down time limits. The stochastic mixed-integer linear programming problem allows a decision support for strategies advantaging from an effective wind and thermal mixed bidding. A case study is presented using data from the Iberian electricity market.

Bidding strategy of wind-thermal energy producers

This paper presents a stochastic mixed-integer linear programming approach for solving the self-scheduling problem of a price-taker thermal and wind power producer taking part in a pool-based electricity market. Uncertainty on electricity price and wind power is considered through a set of scenarios. Thermal units are modelled by variable costs, start-up costs and technical operating constraints, such as: forbidden operating zones, ramp up/down limits and minimum up/down time limits. An efficient mixed-integer linear program is presented to develop the offering strategies of the coordinated production of thermal and wind energy generation, having as a goal the maximization of profit. A case study with data from the Iberian Electricity Market is presented and results are discussed to show the effectiveness of the proposed approach.

Optimal Wind Bidding Strategies in Day-Ahead Markets

This paper presents a computer application for wind energy bidding in a day-ahead electricity market to better accommodate the variability of the energy source. The computer application is based in a stochastic linear mathematical programming problem. The goal is to obtain the optimal bidding strategy in order to maximize the revenue. Electricity prices and financial penalties for shortfall or surplus energy deliver are modeled. Finally, conclusions are drawn from an illustrative case study, using data from the day-ahead electricity market of the Iberian Peninsula.

Impactes do Preço da Água na Agricultura no Perímetro Irrigado do Vale de Caxito

O aumento da pressão sobre os recursos hídricos tem levado muitos países a reconsiderarem os mecanismos utilizados na indução do uso eficiente da água, especialmente na agricultura irrigada. Estabelecer o preço correto da água é um dos mecanismos de tornar mais eficiente a alocação da água. O presente trabalho tem como objetivo a análise dos impactes económicos, sociais e ambientais de políticas de preço da água. A metodologia utilizada foi a Programação Linear, aplicada ao Perímetro Irrigado do Vale de Caxito, Província do Bengo, a 45 km de Luanda, que tem como fonte o rio Dande. Foram testados três cenários relativos a políticas de tarifação de água: tarifa volumétrica simples, tarifa volumétrica variável, e tarifa fixa por superfície. As principais conclusões mostram que, do ponto de vista do uso eficiente da água na agricultura, os melhores resultados obtêm-se com a tarifa volumétrica variável; do ponto de vista social, a tarifação volumétrica simples apresenta os melhores resultados; o método de tarifa volumétrica variável foi o mais penalizador, reduzindo rapidamente a área das culturas mais consumidoras de água, sendo o melhor do ponto de vista ambiental. Qualquer um dos métodos traz aspetos negativos relativamente à redução da margem bruta total. Palavras-chaves: Recursos hídricos; Preço da água; Programação linear. Abstract: Increased pressure on water resources has led many countries to reconsider the mechanisms used in the induction of efficient water use, especially for irrigated agriculture, a major consumer of water. Establishing the correct price of water is one of the mechanisms for more efficient allocation of water. This paper aims to analyze the economic, social and essenenvironmental impacts of water price policies. The methodology used is the linear programming, applied to the Irrigated Valley Caxito, in Bengo Province, 45 kilometers from Luanda, which has the river Dande as its source. Three scenarios concerning water price policies were tested: simple volumetric rate, variable volumetric rate and flat rate per surface. The main findings show that from the point of view of the efficient use of water in agriculture, the best results are obtained with variable volumetric rate; from the social point of view, the simple volumetric rate has the best results; the volume variable rate method proved to be the most penalizing, quickly reducing the area of most water consuming cultures, being the method in which the environmental objectives would be more readily achieved. Either methods bring negative aspects in relation to the reduction of total gross margin. Key-words: Water resources; Water price; Linear programming.