电力市场环境下虚拟电厂两阶段能量经济优化调度

Two-Stage Energy Economic Optimal Dispatch of Virtual Power Plant in Deregulated Electricity Market

随着分布式可再生能源在电网中的渗透率不断增加,虚拟电厂作为一种高效管理分布式可再生能源的技术已经引起国内外学者的广泛关注。提出一种非管制电力市场环境下的虚拟电厂两阶段能量经济优化调度方法,该方法将虚拟电厂的调度分为日前和日内2个阶段。在日前阶段,基于预测信息制定次日的最优调度计划并与日前电力市场签订协议;在日内阶段,以日前计划为参考,采用模型预测控制策略调整日内的运行计划,以消除由于预测误差导致的净负荷波动,同时尽可能减少来自日内平衡市场的罚款,降低总体运行成本。所提出的模型均使用商业求解器Gurobi进行求解。仿真数值结果表明:所提出的算法通过日前计划和日内调控的手段提高了可再生能源设备的利用率,具备一定的经济性和实用性,为虚拟电厂的经济调度提供了新的思路和途径。

With the increasing penetration of renewable distributed energy resources(DER) in power grids, virtual power plant(VPP)as an effective management technology of DERs has attracted widespread attentions. In this paper, a two-stage energy economic optimal scheduling method is proposed for VPP in a deregulated electricity market, which consists of day-ahead stage and intra-day stage. In the day-ahead stage, the optimal scheduling plan for the next day is formulated based on the forecasting information, and an agreement is signed with the day-ahead electricity market organizer. In the intra-day stage, on the basis of the day-ahead scheduling plan, the model predictive control(MPC) strategy is used to adjust the intra-day operation plan so as to eliminate net load variation caused by forecasting errors as well as to minimize penalties from the intra-day balancing market, thus reducing the overall operation costs. The proposed models are solved by the commercial solver Gurobi 9.1. Numerical simulation results show that the proposed method improves the utilization rate of DER and equipment inside VPP by means of day-ahead scheduling and intra-day redispatching, which is economical and practical, and provides a new approach for the economic dispatch of VPP.