摘要
将人工蜂群(ABC)算法应用到中长期电力负荷预测中,通过与组合预测模型相结合,对组合预测目标函数进行优化权重求解。另外针对该算法的早期收敛速度慢、后期容易陷入局部最优的缺点,通过引入扰动项,并进行最坏蜜源替代予以解决。实例分析证明该改进算法收敛速度快,全局寻优能力强。利用它求得的组合预测值,相对于单一模型的预测结果,精度有较大的提高,说明该改进算法应用到中长期电力负荷预测中是可行的。
Artificial bee colony （ABC） algorithm is applied to the medium and long term power load forecasting. Combined with the combination forecasting model, it optimizes the weights of combination prediction in objective function. A disturbing term and worst honey substitution are introduced to overcome the problems of slow convergence speed in the early stage and easy falling to local optimum in the late stage of the existing ABC algorithm. Case analysis shows that the improved method has rapid convergence and strong global optimization. Compared with the forecasting result of single model, the combination forecasting value by using the improved method is more accurate, which shows it is feasible in the medium and long term power load forecasting.
出处
《电力系统保护与控制》
EI
CSCD
北大核心
2014年第23期113-117,共5页
Power System Protection and Control
基金
国家自然科学基金项目(51277059)~~
关键词
ABC算法
中长期电力负荷
组合预测
扰动项
OBL策略
artificial bee colony algorithm
medium and long-term electricity load
combination forecasting
disturbing term
OBL strategy
