Method for identifying distributed photovoltaic power generation system and predicting net load curve

The invention provides a method for identifying a distributed photovoltaic power generation system and predicting a net load curve. The method comprises the following steps: dividing weather types into a plurality of different weather types; according to the photovoltaic power generation characteristics and the user net load curve under different weather conditions, target characteristic parameters are extracted, and a binary classification distributed photovoltaic load identification model based on the user net load characteristics is established; a sample entropy theory is introduced to quantify a weather type, an inertia weight and a learning factor in a particle swarm optimization algorithm are improved by using a genetic variation idea to obtain an improved particle swarm optimization algorithm, and a penalty factor and a kernel function parameter in a least square support vector machine are optimized to obtain an improved particle swarm optimization algorithm. And establishing a net load prediction mode