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Wind farm portfolio optimization under network capacity constraints

机译:网络容量约束下的风电场投资组合优化

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In this article, we provide a new methodology for optimizing a portfolio of wind farms within a market environment, for two Market Designs (exogenous prices and endogenous prices). Our model is built on an agent based representation of suppliers and generators interacting in a certain number of geographic demand markets, organized as two tiered systems. Assuming rational expectation of the agents with respect to the outcome of the real-time market, suppliers take forward positions, which act as signals in the day-ahead market, to compensate for the uncertainty associated with supply and demand. Then, generators optimize their bilateral trades with the generators in the other markets. The Nash Equilibria resulting from this Signaling Game are characterized using Game Theory. The Markowitz Frontier, containing the set of efficient wind farm portfolios, is derived theoretically as a function of the number of wind farms and of their concentration. Finally, using a case study of France, Germany and Belgium, we simulate the Markowitz Frontier contour in the expected cost-risk plane. (C) 2015 Elsevier B.V. and Association of European Operational Research Societies (EURO) within the International Federation of Operational Research Societies (IFORS). All rights reserved.
机译:在本文中,我们为两个市场设计(外部价格和内部价格)提供了一种优化市场环境中的风电场投资组合的新方法。我们的模型基于在一定数量的地理需求市场中相互作用的供应商和生产者的基于代理的表示形式,组织为两层系统。假设代理商对实时市场的结果有合理的期望,则供应商会采取提前仓位(在日前市场中充当信号)来补偿与供求相关的不确定性。然后,发电机与其他市场的发电机优化双边贸易。信号博弈产生的纳什均衡使用博弈论进行表征。从理论上讲,包含高效风电场投资组合的Markowitz Frontier是风电场数量及其集中度的函数。最后,通过对法国,德国和比利时的案例研究,我们在预期的成本风险飞机上模拟了Markowitz Frontier轮廓。 (C)2015年Elsevier B.V.和国际运营研究学会联合会(IFORS)中的欧洲运营研究学会协会(EURO)。版权所有。

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