Risk‐Averse Distributionally Robust Environmental‐Economic Dispatch Strategy Based on Renewable Energy Operation: A New Improved Whale Optimization Algorithm

Although the use of optimization techniques for environmental and economic dispatch of integrated electricity and natural gas systems has been widely applied, there are still significant challenges in meeting the multiple energy demands of conventional and renewable energy sources, mainly wind‐solar. In this study, Wasserstein distance is introduced to measure the randomness of wind‐solar power generation to construct the uncertainty set. A multi‐objective distributionally robust optimization (MODRO) environmental‐economic scheduling model for risk aversion that minimizes the risk cost, the system operation cost, and the carbon emission cost is proposed to achieve the balance between the risk cost, the operation cost, and the pollutant emission. To solve the model efficiently, the multi‐objective whale optimization algorithm (IMOWOA) was improved and used the 4‐node power system and the 7‐node natural gas system as case studies. The results show that the MODRO environmental‐economic scheduling model can measure the operational risk due to the stochastic fluctuation of wind‐solar energy sources, and provide an effective decision‐making tool for policymakers. Considering P2G technology and gas turbines at the same time, it promotes the coupled operation of electric‐gas integrated systems and achieves good economic efficiency. Thus, the model provides an effective solution for the stability, economy, and cleanliness of the integrated electric gas system. © 2024 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.