Multi-Objective Distributionally Robust Optimization of Power-Gas Energy Integrated Systems Considering Environmental-Economic Dispatch - Liu, Yubing; Gao, Guangkuo; Zhao, Wenhui (Journal of electrical engineering & technology, 2025)
Since gas turbines have fast start-stop and load regulation characteristics, they can effectively suppress the instability caused by wind power and solar power units, so the collaborative operation of integrated power-gas systems(IPGS) is increasingly important. In this paper, a multi-objective environmental-economic dispatch optimization model for the IPGS with wind power and solar power is considered in a random environment, and the coupling constraint of the IPGS is established. Aiming at the random problem in the model, considering the statistical significance, the random variables are limited to the Wasserstein distribution set, and the distribution robust optimization is introduced. Since multi-objective optimization problems are difficult to solve exactly, this paper improves the multi-objective gray wolf optimization algorithm(IMOGWO) and verifies the effectiveness of the improved algorithm by standard functions. Finally, through numerical experiments for comparison, the results show that: (1) The IMOGWO algorithm is more suitable for this type of problem as it can solve the multi-objective distribution robust model more quickly than the existing algorithms; (2) Distributed robust multi-objective modeling effectively reduces the environmental-economic dispatch cost of the IPGS, improves the dispatch economy, reduces CO 2 emissions, and provides a powerful decision-making tool for policy-makers.