Similar Days Fuzzy Clustering Load Forecasting

Power system operation needs to match generation to load demand. Accurate load forecasting helps operators maintain the power balance, reducing generation costs and preventing outages. This paper proposes an improved fuzzy clustering load forecasting method based on similar day and normalization approaches, especially for short-term power system load forecasting. Simulation results utilizing data from PJM, demonstrate a reasonable forecast error compared to PJM day-ahead hourly load forecasts. The superiority of this method is the simple calculations and accuracy based on the historical data.