Application of SYR with backtracking search algorithm for long-term load forecasting

作者：Wang Jianjun^*; Li Li; Liu Ding

来源：Journal of Intelligent and Fuzzy Systems, 2016, 31(4): 2341-2347.

DOI：10.3233/JIFS-169075

• Long-term load forecasting
• support vector regression (SVR)
• backtracking search algorithm

Long-term load forecasting is an important issue for a country's power suppliers to determine the future electric system plan, investment and operation. This paper presents a novel hybrid long-term forecasting method with support vector regression(SVR) and backtracking search algorithm(BSA) optimization algorithm, which is used to obtain the parameters of the SVR. The practical case of China's annual electricity demand is used to evaluate the effectiveness of the proposed method. According to the results, the performance of the proposed method is better than the SVR model with default parameters, back propagation artificial neural network (BPNN) and regression forecasting models in annual load forecasting.

• 出版日期2016
• 单位华北电力大学（保定）; 华北电力大学