Impact of Energy Storage on Effective Load Carrying Capability of Renewable Energy Based on Reliability Analysis

Energy storage (ES) resources can play a role in peak-cutting and valley-filling., promoting the consumption of renewable energy and capacity support in the power system. The strategic integration of ES resources into the electricity market holds significant importance in maximizing the capacity value of these resources and ensuring the long-term reliable operation of the power system. Taking into account the physical characteristics of the multi-period coupling relationship of ES resources., this paper proposes a multi-period hybrid power system time-series production model with the participation of renewable energy sources (RESs) and ES. According to the stochastic optimization method based on scenario analysis., Latin hypercube sampling and K-means clustering are used to generate and reduce the predicted power output scenarios of RESs by known probability distribution functions., describing the probabilistic output characteristics of RESs through different scenarios. Based on the time-series production model., an effective capacity assessment model is proposed., applying the reliability-based Effective Load Carrying Capability (ELCC) method., which employs loss of load probability (LOLP) and expected energy not supplied (EENS) as reliability indices. Finally., the CPLEX solver is used in the YALMIP toolbox to solve the mixed integer linear programming (MILP) model in MATLAB., verifying the effectiveness of the proposed model.