Multi-Objective Optimization of Electric–Gas–Thermal Systems via the Hippo Optimization Algorithm: Low-Carbon and Cost-Effective Solutions

Keyong Hu (), Lei Lu, Qingqing Yang, Yang Feng and Ben Wang ()
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Keyong Hu: School of Information Science and Technology, Hangzhou Normal University, Hangzhou 311121, China
Lei Lu: School of Information Science and Technology, Hangzhou Normal University, Hangzhou 311121, China
Qingqing Yang: School of Information Science and Technology, Hangzhou Normal University, Hangzhou 311121, China
Yang Feng: School of Information Science and Technology, Hangzhou Normal University, Hangzhou 311121, China
Ben Wang: School of Information Science and Technology, Hangzhou Normal University, Hangzhou 311121, China

Sustainability, 2025, vol. 17, issue 22, 1-33

Abstract: Integrated energy systems (IES) are central to sustainable energy transitions because sector coupling can raise renewable utilization and cut greenhouse gas emissions. Yet, traditional optimizers often become trapped in local optima and struggle with multi-objective trade-offs between economic and environmental goals. This study applies the hippopotamus optimization algorithm (HOA) to the sustainability-oriented, multi-objective operation of an electricity–gas–heat IES that incorporates power-to-gas (P2G), photovoltaic generation, and wind power. We jointly minimize operating cost and carbon emissions while improving renewable energy utilization. In comparative tests against pigeon-inspired optimization (PIO) and particle swarm optimization (PSO), HOA achieves superior Pareto performance, lowering operating costs by ~1.5%, increasing energy utilization by 16.3%, and reducing greenhouse gas emissions by 23%. These gains stem from HOA’s stronger exploration–exploitation balance and the flexibility introduced by P2G, which converts surplus electricity into storable gas to support heat and power demands. The results confirm that HOA provides an effective decision tool for sustainable IES operation, enabling deeper variable-renewable integration, lower system-wide emissions, and improved economic outcomes, thereby offering practical guidance for utilities and planners pursuing cost-effective decarbonization.

Keywords: integrated energy system; hippo optimization algorithm; multi-objective optimization; carbon emission reduction; energy dispatching; sustainability; renewable energy integration; power-to-gas (P2G) (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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