An Electric Power Generation Forecasting Method Using Support Vector Machine

The diversity of power generation provides an important guarantee for the electric reliability of human society. The forecasting of power generation is an important topic in the electrical industry. However, most of recent work are focus on some special type power generation, overall electric load forecasting is lacking attention. In order to improve practical applications, this paper proposes a power generation predication method based on one of popular machine learning algorithm that is support vector machine, so as to predict both overall power generation and some special types of power generation. The nonlinear relation of electric net power generation is explored by historical monthly recorded data, this relation can help the predication of net electric generation for the next month. Experimental results show that our proposed electric generation forecasting method based on support vector machine can get suitable predication model and achieve high predicted precision, which is in accordance with the real data in the record.