Multi-Resource and Multi-Objective Peak Shaving Optimization Dispatch of Large Power Grids Considering Efficient Utilization of Multiple Energy Storage and Demand Response

With the increasing proportion of clean energy in power systems, the curtailment of wind and solar power has intensified during periods of high clean energy generation. Meanwhile, the high penetration of clean energy installed capacity has further compressed the operating capacity of traditional power generation units, weakening the grid's peak shaving and supply security regulation capabilities. Energy storage, as a key means of smoothing the fluctuations of renewable energy and alleviating supply-demand contradictions, is crucial for ensuring the safe, stable, and flexible operation of the power grid. Demand-side response, as a means of optimizing the load curve, can also reduce the impact of the counter-peak characteristics and intermittency of wind and solar power on grid optimization scheduling. This paper addresses the challenges of ensuring power supply and peak shaving in power systems with a high proportion of clean energy penetration, as well as the difficulties in new energy consumption. It proposes a multi-resource, multi-objective peak shaving optimization scheduling method for large power grids that considers the efficient utilization of multiple energy storage systems and demand-side response. First, taking the new type of power system with a high proportion of clean energy as the research object, this paper sorts out three key needs: grid flexible peak shaving, efficient clean energy consumption, and the guarantee of system operation economy. Based on these, an evaluation index system for the joint optimization scheduling of multiple resources in large power grids is constructed. Second, according to the proposed evaluation index system, fully considering the efficient utilization of multiple energy storage systems and demand-side response, a multi-resource, multi-objective, two-level peak shaving optimization scheduling model for large power grids is established. In this model, the upper-level model aims to minimize the fluctuation of net load to complete the startup combination plan of conventional units, while the lower-level model aims to minimize the curtailed clean energy and system operation costs to complete the optimization of the output curves of multiple resources, providing a reference for power grid generation plan formulation. Finally, based on the actual operation case of a provincial power grid in Southwest China, the effectiveness and advanced nature of the proposed modeling method are verified. The results show that compared with not configuring multiple energy storage or demand-side response resources, using multiple energy storage or demand-side response alone can improve grid peak shaving, clean energy consumption, and system operation economy to a certain extent. Furthermore, by jointly optimizing demand-side response resources and multiple energy storage resources, the utilization of multiple energy storage can be effectively improved, and the degree of improvement in the three key needs proposed is significantly greater than that of using multiple energy storage or demand-side response alone.