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This invention belongs to the field of photovoltaic power generation control technology and discloses a method for partitioning distributed photovoltaic clusters in a regional distribution network. It calculates the electrical distance between nodes based on a frequency-active power sensitivity matrix and obtains the electrical distance matrix. An optimized initial centroid is obtained using the PSO algorithm. Based on the initial centroid, the K-means algorithm is applied to perform cluster analysis on the nodes of the distribution network, completing the cluster partitioning of energy storage nodes. Using energy storage nodes as centroids, the remaining photovoltaic nodes without energy storage and load nodes are further partitioned into clusters. A comprehensive performance index is obtained by weighting three indicators: active power balance, energy storage balance, and modularity. The partitioning scheme with the highest comprehensive performance index is considered the optimal cluster partitioning. This invention uses the energy storage area as the center to partition distribution areas containing distributed photovoltaics into clusters, providing necessary inertia and frequency support for the power grid.

This invention discloses an adaptive differential evolution algorithm for optimizing passive radar station deployment, comprising the following steps: establishing a passive time difference station deployment simulation scenario; step 2: population initialization; step 3: fitness value calculation; step 4: genetic operation. On the one hand, this invention addresses the problem of numerous variable parameters and complex parameter settings in particle swarm optimization (PSO) algorithms by incorporating iteration counts, fitness values, and weights into parameter generation, making the algorithm's search and convergence more reasonable. On the other hand, this invention considers the impact of station location error, time difference error, and communication distance between observation stations on the deployment results during experimental simulation, making the modeling process more realistic.