摘要:市场环境下,径流的随机性、发电量的不确定性使得水电站愈加关注其面临的收益风险,如何在调度决策中进行风险管理是其需要解决的重要问题。提出以随机场景分析方法表示电价的波动特征,结合风险惩罚模式和风险约束模式,建立基于动态风险管理方法的水电站短期优化调度模型,以改进快速进化算法(improved fast evolutionary algorithm,IFEP)与遗传算法(genetic algorithm,GA)相结合的IFEP—GA混合优化算法作为模型的求解方法,进化策略结合了高斯变异和柯西变异的特点,约束的处理结合了惩罚机制与修复机制,这使得算法具有良好的寻优能力和收敛特性。不同风险管理模式对水电站优化运行影响的分析结果表明,动态风险管理策略能够更好地平衡期望收益、风险及末期库容约束的违反,减小风险的同时获得了更高的期望收益,为水电站依据自身风险接受程度灵活安排调度决策提供理论依据。
In an electricity market, hydropower producers pay more attention to the revenue risk due to the stochastic characteristic of inflows and electricity generation. How to consider risk management in the process of hydro scheduling is an important problem to be solved. In this paper, multiple scenarios were utilized to represent the stochastic market prices Risk penalization mode and risk constraint mode were combined to construct short-term optimal hydro scheduling model based on dynamic risk management. A new algorithm combing the improved fast evolutionary algorithm (IFEP) and genetic algorithm (GA) was proposed, in which Gaussian and Cauchy mutation were combined, and penalizing and repairing mechanism were combined to deal with the constraints, therefore the algorithm has good performance in search and convergence. The analysis results about the influence of various risk management modes on optimal hydro scheduling show that, dynamic risk management can obtain a better trade-off among expected profit, risk and violation of end reservoir storage, and can obtain more expected profit with less risk, and can provide theory reference for flexible scheduling decisions based on its acceptable risk level.