Micro-grid group load prediction method and system, medium and electronic equipment

The invention provides a micro-grid group load prediction method and system, a medium and electronic equipment. The method comprises the following steps: acquiring operation parameter data of a micro-grid group; and obtaining a load prediction result according to the obtained operation parameter data and a preset neural network model, wherein the preset neural network model is a ridgelet recurrent neural network model, and the ridgelet recurrent neural network model is trained by adopting a particle swarm optimization algorithm. The particle swarm optimization ridgelet recurrent neural network model is adopted, so that the load prediction precision of the micro-grid group is greatly improved, and then more accurate load scheduling of the micro-grid group is realized. 本公开提供了一种微电网群负荷预测方法、系统、介质及电子设备，所述方法为：获取微电网群的运行参量数据；根据获取的运行参量数据和预设神经网络模型，得到负荷预测结果；其中，预设神经网络模型为脊波递归神经网络模型，且脊波递归神经网络模型采用粒子群优化算法训练；本公开采用粒子群优化的脊波递归神经网络模型，极大的提高了微电网群负荷预测精度，进而实现了更精准的微电网群负荷调度。