基于混合智能技术的微电网剩余负荷超短期预测

对微电网中分布式电源发电量和短期负荷的准确预报是微电网运行控制和能量管理的重要基础.提出了微电网剩余负荷的概念和计算方法,分析了微电网剩余负荷超短期预测的特点和影响因素.在考虑微电源历史输出功率、微电网历史负荷以及本地气象因素的同时,综合运用k均值聚类分析、遗传算法和人工神经网络建立了微电网剩余负荷超短期预测模型.搭建了一个含有风电、燃气轮机和燃料电池的微电网仿真模型,仿真结果表明,模型中分布式电源发电量和微电网负荷的预测结果与实测数据非常吻合,验证了模型的预测精度.

Ultra-short-term forecasting of microgrid surplus load based on hybrid intelligence techniques

As the accurate forecasting of distributed generation and short-term load is the basis of operational control and energy management of microgrid,the concept and calculation method of microgrid surplus load are proposed and the features and influencing factors of its ultra-short-term forecasting are discussed.With the consideration of historical power outputs,loads and weather data,an ultra-short-term forecasting model of microgrid surplus load is developed,which integrates k-means clustering analysis,genetic algorithm and artificial neural network.A simulation model of microgrid with wind farms,micro-turbines and fuel cells is established and results show that,the forecasting outputs of distributed generators and the forecasting load of microgrid are very close to the measured data,which verifies the accuracy of the proposed forecasting model.