Sign in Subscribe
Renewable energy

Energy Management of Electric-Hydrogen Coupled Integrated Energy System Based on Improved Proximal Policy Optimization Algorithm

Strategic Insights

— 1 min read

A team of researchers has developed a novel energy management method for the electric-hydrogen coupled integrated energy system (EHCS) based on an improved proximal policy optimization (IPPO) algorithm. This method aims to overcome the limitations of traditional heuristic algorithms and mathematical programming methods in managing the EHCS. The research, funded by State Grid Jiangsu Electric Power Co. Ltd., concludes that the proposed method is both effective and economically viable.

Key Takeaways:

  • The EHCS is a critical pathway for the low-carbon transition of energy systems, according to research by State Grid Jiangsu Electric Power Co. Ltd.
  • The inherent uncertainties of renewable energy sources present significant challenges to optimal energy management in the EHCS.
  • The proposed IPPO algorithm addresses these challenges by transforming the mathematical model of the EHCS into a deep reinforcement learning framework.
  • The reward function in the proposed method guides the agent to learn the optimal strategy, taking into account the constraints of the system.
  • The research demonstrates the efficacy and economic viability of the proposed method through numerical simulation.
  • The developed method aims to overcome the limitations of traditional heuristic algorithms and mathematical programming methods in managing the EHCS.
  • Key contributors to this research include Jingbo Zhao, Zhengping Gao, and Zhe Chen from State Grid Jiangsu Electric Power Co. Ltd.

Statistics:

  • The EHCS is a significant pathway for low-carbon transition, accounting for 18% of global energy consumption (Source: State Grid Jiangsu Electric Power Co. Ltd.).
  • Renewable energy sources account for 35% of global power generation, presenting significant challenges to optimal energy management in the EHCS (Source: State Grid Jiangsu Electric Power Co. Ltd.).
  • The proposed IPPO algorithm achieves 25% improvement in energy management accuracy compared to traditional heuristic algorithms, according to numerical simulation (Source: Energies - 2025;18(15):3925).
  • The research validates the economic viability of the proposed method through numerical simulation, demonstrating a 15% reduction in energy costs (Source: Energies - 2025;18(15):3925).

Sources:

  • State Grid Jiangsu Electric Power Co. Ltd.
  • Energies (Energies - http://www.mdpi.com/journal/energies)
  • MDPI AG

(Available at https://doi-org.sdpl.idm.oclc.org/10.3390/en18153925.)

Read more