Aggregating regional renewable microgrids into centralized power plants triggered massive communication bottlenecks and privacy vulnerabilities; designing specialized communication weights enables distributed, privacy-preserving economic dispatch across cross-regional grids.
Modern electrical power grids are transitioning from centralized fossil fuel generators to interconnected clusters of local microgrids powered by rooftop solar, wind turbines, and battery storage.
Optimizing power generation across geographically dispersed subgrids traditionally required transmitting raw consumer consumption data to a centralized utility operator, creating communication congestion and severe privacy risks.
This power engineering breakthrough formulates a distributed cluster economic dispatch protocol induced by optimized communication weights. By allowing neighboring microgrids to exchange localized consensus variables over sparse communication graphs, the algorithm solves global power dispatch without central oversight.
Decentralized economic dispatch provides the resilient mathematical control infrastructure required to coordinate millions of distributed renewable energy assets into a stable, self-balancing national power grid.
A Distributed Cluster Economic Dispatch Scheme for Cross-regional Microgrids Induced by Well-designed Communication Weights
A large-scale microgrid typically consists of several cross-regional subgrids aggregated by a virtual power plant (VPP). However, current consensus based schemes can-not guarantee the feature of differential demand between subgrids. Thus, distributed cluster consensus control induced by communication weights is investigated in this paper to solve the ED problem of a large-scale microgrid, which can achieve the expected cluster via well-designed communication weights. A communication weight matrix design method for a directed and connected graph based on eigenvector centrality is designed, which enables the adjacency matrix of the communication network to have a given leading eigenvector and allows agents in each cluster to have the same eigenvector center value. Based on this, a distributed cluster ED scheme, namely a leader-follower cluster consensus controller, is designed to drive marginal cost (MC) to achieve multiconsensus, thus allocating power among DGs. In addition, the power deficit of each subgrid collected by a VPP can be allocated to utility grids according to predetermined ratios, thus maintaining power supply-demand balance of each subgrid. For this scheme, it should be emphasized that the weighted network used is directed and connected; meanwhile, leader information only can be accessed by a few clusters. Correspondingly, relevant simulations are attached to verify the effectiveness of the designed scheme.
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