Photovoltaic generation capacity credit evaluation method considering its daily output characteristics

The capacity credit is important to determine the contribution of intermittent power generation to the system. Evaluation of the capacity credit is one of the urgent problems when large-scare PV stations are planned to connect to the traditional power systems. At present, most researches are about the power capacity credit of wind power. However, there are some similarities between photovoltaic power and wind power. Since the change of light intensity, photovoltaic generation system also has a certain regularity. This paper presents a new method for evaluating the power capacity credit of PV generation systems. Firstly, the daily output characteristics are shown based on the data from the photovoltaic generation plants in China using computational methods of probabilistic statistics. Then, based on Latin Hypercube Sampling (LHS) technique, the photovoltaic output characteristics of 24 hours a day are simulated. This paper screens 10 typical scenarios using scenario reduction techniques based on Kantorovich Distance (KD). In each scenario, the system reliability level is calculated by probabilistic production simulation. Based on the effective load carrying capability (ELCC) of photovoltaic, the photovoltaic generation capacity credit is defined. This paper gets the ELCC by the secant method which is efficient with high accuracy. Its correctness and the affectiviry is proved by tests in IEEE RTS-96 with photovoltaic generation system.