摘要
为解决微电网大规模超短期负荷预测的计算速度和准确度问题,建立最优局部形相似超短期负荷预测模型,引入表征气象综合影响因素的人体舒适度指数,并对人体舒适度指数公式进行改进。根据最优局部形相似数列与实时数据给出了一种基于加权平均的最优局部形相似超短期负荷预测方法,以获取超短期负荷预测初始值,利用改进人体舒适度指数对该初始值进行一次修正;再根据实时数据与预测数据的偏差并运用超稳定自适应控制理论对一次修正值进行二次修正,最终获得超短期负荷预测值。实例验证了所提方法的可行性,同时证明该方法在大规模超短期负荷预测中对计算速度和计算准确性都有较好的适应性。
In order to solve the problem of calculation speed and accuracy in large-scale ultra short-term load forecasting for the micro-grid , an optimal local shape similarity ultra short-term load forecasting model was established , human comfort in-dex representing comprehensive influencing factors on weather was introduced and formula of human comfort index was im-proved. According to the optimal local shape similarity sequence and real-time data , a similarity ultra short-term load forecasting based on weight average was proposed so as to obtainshort-term load forecasting and amend this value for once by using the improved human comfortdeviation of real-time data and forecasting data , hyperstable adaptive control theory was applied for twice amendment on the modified value and the ultra short-term load forecasting value was finally acquired. Actual example proposed method and indicates that it has preferable adaptability to calculation speed and accuracy in large-scale ultra short-term load forecasting.
出处
《广东电力》
2017年第4期137-142,共6页
Guangdong Electric Power
关键词
微电网
超短期负荷预测
局部形相似
人体舒适度指数
空气质量指数
micro-grid
ultra short-term load forecasting
local shape similarity
human comfort index
air quality index
