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A stochastic programming model for the thermal optimal day-ahead bid problem with physical futures contracts

机译:具有实物期货合约的热最优日间提前买价问题的随机规划模型

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The reorganization of the electricity industry in Spain completed a new step with the start-up of the Derivatives Market. One main characteristic of MIBEL's Derivatives Market is the existence of physical futures contracts; they imply the obligation to physically settle the energy. The market regulation establishes the mechanism for including those physical futures in the day-ahead bidding of the generation companies. The goal of this work is to optimize coordination between physical futures contracts and the day-ahead bidding which follow this regulation. We propose a stochastic quadratic mixed-integer programming model which maximizes the expected profits, taking into account futures contracts settlement. The model gives the simultaneous optimization for the Day-Ahead Market bidding strategy and power planning production (unit commitment) for the thermal units of a price-taker generation company. The uncertainty of the Day-Ahead Market price is included in the stochastic model through a set of scenarios. Implementation details and some first computational experiences for small real cases are presented.
机译:随着衍生品市场的启动,西班牙电力行业的重组完成了新的一步。 MIBEL衍生品市场的主要特征之一是实物期货合约的存在。它们暗示着必须物理解决能量的义务。市场法规建立了将那些实物期货包括在发电公司的提前报价中的机制。这项工作的目标是优化遵循该规定的实物期货合约与日间投标之间的协调。考虑到期货合约的结算,我们提出了一种随机的二次混合整数规划模型,该模型使预期利润最大化。该模型同时为价格接受发电公司的热力单元同时优化了日间市场招标策略和功率计划生产(单元承诺)。通过一组场景,日随机市场价格的不确定性包括在随机模型中。介绍了实现细节和一些小规模实际案例的初步计算经验。

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