电器与能效管理技术
電器與能效管理技術
전기여능효관리기술
Low Voltage Apparatus
2015年
14期
22-27
,共6页
微电网%短期负荷预测%历史认知果蝇优化算法%支持向量机
微電網%短期負荷預測%歷史認知果蠅優化算法%支持嚮量機
미전망%단기부하예측%역사인지과승우화산법%지지향량궤
micro-grid%short-term load forecasting%fruit fly optimization algorithm based on history cognition ( FOABHC)%support vector machines( SVM)
为适应微电网的建设和发展对负荷预测效率及精度的要求，针对微电网负荷基数小、间歇性和随机性大等特点，提出一种基于历史认知果蝇优化算法（FOABHC）－优化支持向量机（SVM）的微电网短期负荷预测模型。以国内某微电网示范工程项目为例，将FOABHC＿SVM用于微电网短期负荷预测。实例仿真结果表明，所提出的FOABHC＿SVM预测模型优于SVM预测模型，更适用于当前微电网短期负荷预测需要。
為適應微電網的建設和髮展對負荷預測效率及精度的要求，針對微電網負荷基數小、間歇性和隨機性大等特點，提齣一種基于歷史認知果蠅優化算法（FOABHC）－優化支持嚮量機（SVM）的微電網短期負荷預測模型。以國內某微電網示範工程項目為例，將FOABHC＿SVM用于微電網短期負荷預測。實例倣真結果錶明，所提齣的FOABHC＿SVM預測模型優于SVM預測模型，更適用于噹前微電網短期負荷預測需要。
위괄응미전망적건설화발전대부하예측효솔급정도적요구，침대미전망부하기수소、간헐성화수궤성대등특점，제출일충기우역사인지과승우화산법（FOABHC）－우화지지향량궤（SVM）적미전망단기부하예측모형。이국내모미전망시범공정항목위례，장FOABHC＿SVM용우미전망단기부하예측。실례방진결과표명，소제출적FOABHC＿SVM예측모형우우SVM예측모형，경괄용우당전미전망단기부하예측수요。
To meet the requirement of the load forecasting efficiency and accuracy introduced by the construction and development of micro grid , according to the characteristics of micro grid load: small base load, high intermittence and big randomness , a micro grid short term load forecasting model based on support vector machine (SVM) optimized by fruit fly optimization algorithm based on history cognition (FOABHC) was proposed. Taking a domestic micro grid trial project for example , the FOABHC_SVM was used for micro grid short-term load forecasting .The simulation results show that the proposed FOABHC_SVM forecasting model is superior to the SVM forecasting model and is more suitable for the current micro-grid short-term load forecasting .
