考虑夏普比率的虚拟电厂日前投标策略

Day Ahead Bidding Strategy for Virtual Power Plants Considering Sharpe Ratio

由于风电、光伏机组出力不确定性及负荷等预测误差的存在,虚拟电厂日前投标行为面临风险,而目前应用于日前投标的风险–收益多目标优化方法仍需主观决策风险厌恶系数。夏普比率能够同时衡量收益与风险,可在无需决策风险厌恶系数的同时实现风险和收益的帕累托最优,目前已被广泛地用于评价投资组合的业绩、评判资本市场的运行效率等方面。该文将虚拟电厂日前投标行为类比于投资组合,以最大夏普比率为目标,采用场景生成法刻画风电光伏出力、负荷及电价的不确定性,并引入场景评价指标,提出考虑夏普比率的虚拟电厂日前–实时随机优化投标策略。结果表明,以最大夏普比率为目标的投标策略能够降低决策的主观性,在设备参数改变时自主修正风险厌恶系数,与传统风险管理方法的计算结果对比验证了模型有效性。

Due to the existence of the output uncertainty of wind power/photovoltaic units and the load forecasting errors,the day-ahead bidding behavior of the virtual power plants faces risks,while the risk aversion coefficient still needs to be determined by the risk management stochastic optimization applied to the day-ahead bidding.The Sharpe Ratio measures both the returns and the risks,and it can realize the Pareto optimization of the risks and the returns without using the risk aversion coefficient,which has been widely used in evaluating the performance of portfolio and the operating efficiency of the capital market.In this paper,the day-ahead bidding behavior of the virtual power plants is compared to the investment portfolio.Aiming at the maximum Sharpe Ratio,the uncertainty of the wind power,the PV output,the load and the electricity price is characterized by the scenario generation method,and the scenario evaluation index is introduced.The day-ahead and real-time stochastic optimization bidding strategy of the virtual power plants considering the Sharpe Ratio is proposed.The results show that the bidding strategy aiming at the maximum Sharpe Ratio reduces the subjectivity of the decision and modifies the risk aversion coefficient when the equipment parameters change.The validity of the model is verified compared with the calculation results of the traditional risk management method.