Comprehensive Evaluation Method for Source-Load Matching Based on Scenario Probability

Abstract

Abstract With the continuous increase in the penetration rate of distributed photovoltaic (PV) and diversification of load types, temporal variability and uncertainty of distributed PV output and loads have exerted significant impacts on distribution grids. The planning and operation of future power systems dominated by renewable energy sources requires a quantitative assessment of source-load matching. This paper proposes a comprehensive assessment method for source-load matching that takes into account scenario probabilities. The first step is to establish a source-load matching index system that takes into account the temporal differences between sources and loads. Metrics such as supply-demand matching, volatility matching, and electricity quantity matching are included in this system. Subsequently, data-driven and K-means synchronous clustering is used to generate representative PV and load temporal scenario sets, along with the probabilities of each scenario, enabling the evaluation of various indicators. The combined weights of each indicator are determined by employing the Analytic Hierarchy Process (AHP) and Entropy Weight Method (EWM). Weighted summation is used to obtain the final comprehensive evaluation result. Finally, a case study using a residential distribution area is used to verify the effectiveness and feasibility of the proposed method.