电力系统及其自动化学报2017，Vol.29Issue(7)：1-6,6.DOI:10.3969/j.issn.1003-8930.2017.07.001
考虑业扩报装的相关向量机月度负荷预测方法
Monthly Load Forecasting Method Considering Business Expansion Based on Relevance Vector Machine
摘要
Abstract
Considering that the traditional monthly load forecasting method doses not take the load's intrinsic factors in?to account,a monthly load forecasting method is proposed with the consideration of business expansion based on rele?vance vector machine(RVM). In the proposed method,the electricity consumption trend after business expansion is studied by using growth curve fitting and k-means clustering algorithm,which is further used to extract monthly effect ratio and calculate the business expansion increment that has a substantial impact on the monthly load. Then,a load forecasting model is established based on SVM with the actual business expansion increment and historical load data as sample inputs. Meanwhile,particle swarm optimization and compound kernel function are used to improve the adapt?ability of the proposed model. From the comparison of forecasting results among the models which consider the actual and unmodified business expansion increments respectively,as well as the one that does not consider business expan?sion increment,it is proved that the actual business expansion increment influences the monthly load obviously and it can help to improve the accuracy of forecasting effectively.关键词
月度负荷预测/生长曲线/业扩报装/实际业扩增量/相关向量机Key words
monthly load forecasting/growth curve/business expansion/actual business expansion increment/rele⁃vance vector machine(RVM)分类
信息技术与安全科学引用本文复制引用
江梦洋,程浩忠,吴臻,黄锦华..考虑业扩报装的相关向量机月度负荷预测方法[J].电力系统及其自动化学报,2017,29(7):1-6,6.基金项目
国家自然科学基金重点资助项目(51337005) （51337005）
