Distributed Optimization Dispatch Strategy for Electricity-Gas Coupled System

With the development of energy internet, multi-energy coupling system has received wide attention. This paper addresses the economic dispatch optimization problem in coupled electricity-gas energy systems, with a particular focus on the participation of renewable energy sources. A comprehensive model is proposed, incorporating renewable energy power generation, gas production, and electricity-gas conversion processes. The model further refines the composition of multi-energy loads, transitioning from traditional single-energy loads to more complex multi-energy loads. Additionally, a cost model is established that considers conversion losses, calculation coefficients, and conversion intervals, enhancing adaptability to future new energy system developments and optimal scheduling. A fully distributed optimization algorithm based on neural dynamics is introduced, allowing each energy node to minimize information exchange and perform local optimal power calculations. Theoretical and simulation proofs are provided to validate the effectiveness and efficiency of the proposed model and algorithm.