基于多阶段鲁棒优化的多站合一能源站市场优化策略

Market Optimization Strategy for Multi-station Integrated Energy Stations Based on Multi-stage Robust Optimization

为解决考虑新能源出力不确定性的多站合一能源站参与电力现货市场问题,提出基于多阶段鲁棒优化的市场竞价策略。对多站融合系统中各子系统进行建模,其中包含分布式新能源、计算中心、电动汽车(EV)充电站、储能电站,并刻画了计算中心负荷的弹性和EV的异构性。以最大化最恶劣新能源出力场景下参与市场收益为目标,优化多站合一能源站的联合竞价,并将其转化为多阶段鲁棒优化进行求解。考虑到计算中心与能源站的利益主体不同,提出了基于拉格朗日乘子的成本分摊方法,将总收益在能源站和计算中心之间根据各自的贡献进行合理分配。最后,采用仿真算例验证了所提模型和算法的有效性。

In order to solve the problem of multi-station integrated energy stations participating in electricity spot market transactions considering the uncertainty of renewable energy output,the paper proposes a market bidding strategy based on multi-stage robust optimization.The subsystems in a multi-station fusion system are modeled,including distributed renewable generation,computing center,electric vehicle(EV)charging station,and energy storage station,and the computing center’s load elasticity and the heterogeneity of EV are described.With the goal of maximizing the market revenue in the worst renewable energy output scenario,the joint bidding strategy for the multi-station integrated energy stations is optimized,transforming it into a multi-stage robust optimization for the solution.Considering the different stakeholders between the computing center and the energy station,a cost allocation method based on Lagrange multipliers is proposed,and the total revenue is reasonably allocated between the energy station and the computing center according to their respective contributions.Finally,a simulation example is used to verify the effectiveness of the proposed model and algorithm.