Nash strategies for load serving entities in dynamic energy multi-markets

J. B. Cruz, A. Kian
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引用次数: 3

Abstract

In this paper the problem of developing bidding strategies for the participants of dynamic energy-multi markets is studied. Attention is given to strategic bidding of load serving entities (LSE) in these markets. We model energy multi-markets as non-linear dynamical systems and use discrete-time Nash bidding strategies. Attention is given to a problem, where the objective functions are quadratic in the deviations of trajectories from desired trajectories and quadratic in the control deviations from the nominal controls. It is assumed that each power marketer can estimate his/her competitors' benefit functions and their minimum and maximum values. The optimal bidding strategies are developed mathematically using dynamic game theory. We deal with games that are non-linear in the state equations. We linearize these equations for complex non-linear energy multi-markets and use discrete-time Nash strategies. We show that the actual dynamic excursions from the operating point where we linearize are small so that the linearization is valid. The developed algorithm is applied to an IEEE 14-bus power system for two cases: (1) No transmission capacity constraints, (2) Transmission capacity limit constraints on two groups of transmission lines. We show that the LSEs' expected profits are higher for our method than those for other methods in the literature.
动态能源多市场中负荷服务主体的纳什策略
本文研究了动态能源多元市场参与者的竞价策略制定问题。在这些市场中,对负荷服务实体(LSE)的战略投标给予了关注。我们将能源多市场建模为非线性动态系统,并采用离散时间纳什竞价策略。注意到一个问题,其中目标函数的轨迹偏离期望轨迹是二次的,控制偏离标称控制是二次的。假设每个电力营销人员可以估计其竞争对手的利益函数及其最小值和最大值。运用动态博弈论对最优竞价策略进行数学推导。我们处理的是状态方程中的非线性博弈。对于复杂的非线性能源多市场,我们将这些方程线性化,并使用离散时间纳什策略。我们证明了从我们线性化的工作点出发的实际动态偏移很小,因此线性化是有效的。将该算法应用于一个IEEE 14总线电力系统中,有两种情况:(1)无传输容量约束;(2)两组传输线的传输容量限制约束。我们表明,我们的方法比文献中其他方法的预期利润更高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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