考虑概率区间的微电网短期负荷多目标预测方法

A Multi-Objective Prediction Method for Short-Term Microgrid Load Considering Interval Probability

微电网负荷随机性强、波动大,负荷单点预测已经难以满足微电网稳定运行需要.提出一种考虑概率区间的微电网短期负荷多目标预测方法,以循环神经网络为预测模型,以逼近理想解排序策略、网格筛选策略对基本多目标人工蜂群算法进行改进,优化循环神经网络的权值和阈值,避免单目标区间预测中惩罚系数难以选择的问题,对历史负荷数据进行记忆并修正预测结果,有效提高微电网短期负荷区间预测准确性与可靠性.仿真结果表明,本文所构建的考虑概率区间的微电网短期负荷多目标预测方法,预测性能优越、结果准确,可为微电网安全经济调度提供决策依据.

Load of microgrid has characteristics of strong randomicity and large fluctuation, so that single point prediction cannot satisfy the need of microgrid operating stability. In this paper,a modified multi-objective optimization prediction intervals（PIs） method for microgrid load is proposed, recurrent neural network（RNN） is adopted to build load prediction model, technique for order preference by similarity to an ideal solution and the grid selection strategy are introduced to modify multi-objective artificial bee colony algorithm（MMOABC）,which optimizes the RNN prediction model, improving the accuracy and reliability of microgrid short-term load intervals prediction. The experiment results show that the proposed method for microgrid load has superior performance,which can provide the decision-making basis for the safety and economy of microgrid operation.