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Power Portfolio Optimization in Deregulated Electricity Markets With Risk Management

机译:带有风险管理的放松管制电力市场中的电力组合优化

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In a deregulated electric power system, multiple markets of different time scales exist with various power supply instruments. A load serving entity (LSE) has multiple choices from these instruments to meet its load obligations. In view of the large amount of power involved, the complex market structure, the risks in such volatile markets, the stringent constraints to be satisfied, and the long time horizon, a power portfolio optimization problem is of critical importance for an LSE to serve its load, maximize its profit, and manage its risks. In this paper, a midterm power portfolio optimization problem with risk management is presented. Key instruments are considered, risk terms based on semi-variances of spot market transactions are introduced, and penalties on load obligation violations are added to the objective function to improve algorithm convergence and constraint satisfaction. To overcome the inseparability of the resulting problem, a surrogate optimization framework is developed, enabling a decomposition and coordination approach. Numerical testing results show that our method effectively provides decisions for various instruments to maximize profit and manage risks, and it is computationally efficient
机译:在解除管制的电力系统中,各种电源设备存在着不同时标的多个市场。负载服务实体(LSE)从这些工具中有多种选择可以满足其负载义务。鉴于涉及的电力量巨大,市场结构复杂,在这种动荡的市场中面临的风险,要满足的严格限制以及长期的发展,电力组合优化问题对于伦敦证交所为其服务至关重要加载,最大化其利润并管理其风险。本文提出了带有风险管理的中期电力投资组合优化问题。考虑了关键工具,引入了基于现货市场交易半方差的风险术语,并将对违背负荷义务的惩罚加到了目标函数中,以提高算法的收敛性和约束满意度。为了克服由此产生的问题的不可分割性,开发了替代优化框架,该框架启用了分解和协调方法。数值测试结果表明,我们的方法有效地为各种工具提供了决策,以最大化利润和管理风险,并且计算效率高

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