基于FKNN算法的分布式光伏发电功率智能调控方法
Intelligent Control Method for Distributed Photovoltaic Power Generation Based on FKNN Algorithm
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摘要: 针对现有方法难以有效抑制并网功率波动的问题,提出基于模糊K近邻(Fuzzy K-Nearest Neighbor,FKNN)算法的分布式光伏发电功率智能调控方法。首先,利用FKNN算法构建映射模型预测功率;然后,基于预测结果,以平抑并网功率波动为目标,建立包含储能充放电策略与逆变器控制的功率分配模型;最后,通过滚动优化求解各单元的最优出力。测试结果表明该方法所得预测值与实际值最接近,说明该方法具有较高的预测精度。应用该方法后,光伏发电功率曲线稳定性较高,说明该方法可以迅速调整储能系统的充放电状态,使并网功率保持在设定稳定范围内。Abstract: In response to the problem that existing methods are difficult to effectively suppress grid connected power fluctuations, this study proposes a distributed photovoltaic power generation intelligent control method based on the fuzzy k-nearest neighbor algorithm. Firstly, a mapping model is constructed using the FKNN algorithm to predict power; then, based on the predicted results, a power allocation model is established with the goal of smoothing grid connected power fluctuations, which includes energy storage charging and discharging strategies and inverter control; finally, the optimal output instructions for each unit are solved through rolling optimization. The test results show that the predicted values obtained by this method are closest to the actual values, indicating that this method has high prediction accuracy. After applying this method, the stability of the photovoltaic power generation curve is relatively high, indicating that this method can quickly adjust the charging and discharging state of the energy storage system, keeping the grid connected power within the set stable range.
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