Short-term Load Forecasting of CCHP System Based on PSO-LSTM

With the inherent need to accelerate the high-quality development of China's economy, it is necessary to build a clean, low-carbon, safe and efficient modern energy system. The traditional energy system is centralized and large-scale, and the transmission and distribution system are complex, with low adaptability and reliability. The Combined cooling, heating and power system has been widely promoted and concerned for its advantages of improving energy efficiency, saving energy and reducing emissions. This paper takes the Combined cooling, heating and power system of Shanghai Qiantan Energy Station as the research object and establishes a load prediction model on the user side. This paper first introduces the Combined cooling, heating and power system of Shanghai Qiantan Energy Station, then explores the influencing factors of load data, builds the PSO-LSTM model and analyzes the prediction results, and finally draws a conclusion.