Economic operation analysis of the power grid combining communication network and distributed optimization algorithm

Abstract With the widespread application of smart grids, their economic scheduling and operational decisions need to meet the requirements of large-scale network data and improve the transmission performance of communication resources. Therefore, a distributed network architecture is proposed to analyze the scheduling and management of power systems. A distributed discrete-time optimization algorithm based on communication strategies is applied to analyze the power generation allocation and economic operation of grid nodes. The simulation testing and strategy analysis showed that the distributed optimization algorithm achieved a total output power of 850 MW for the power grid and stabilized the regional electricity load. In the verification of the economic dispatch problem, the total output power of the distributed optimization algorithm reached 13594.87 MW, and the economic cost was reduced by about 23%. The designed method is feasible for economic dispatch, and its contribution lies in using the distributed discrete-time optimization algorithm to provide scientific and reasonable communication strategy solutions for smart grid operation, thereby improving information transmission efficiency and reducing the loss of communication resources. However, the scale and scheduling management of the power grid have not yet been explored. It is necessary to strengthen communication and resource allocation in practical applications.