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A bi-level multi-node optimal siting, sizing, and operation of multi energy system in an integrated energy network of electricity-gas-heat with peer-to-peer trading

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  • Rowe, Kirkland
  • Cooke, Kavian
  • Mokryani, Geev
  • Campean, Felician
  • Chambers, Therese

Abstract

Multi-energy system (MES) technologies, such as energy hubs, link energy networks like electricity, natural gas, and district heating networks. This interlinking enhances the interdependence and interaction of the networks. While the interlinking of the networks to form an integrated energy system (IES) can improve flexibility, there are challenges in coordinating the IES. As a result, the integration and synchronisation of energy flows become challenging, affecting the coordination and optimisation of the overall energy system. This paper presents a novel bi-level optimisation model for the optimal siting, sizing, and operation of MES within an IES encompassing electricity, gas, and heat with peer-to-peer (P2P) trading and demand response. The research addresses the strategic placement and sizing of interconnected energy hubs with various distributed energy resources (DER), including renewable energy sources (RES) and power-to-gas (P2G) systems, to enhance the efficiency and sustainability of the IES. The upper-level optimisation aims to minimise the energy hubs' total investment and operating costs, while the lower-level focuses on reducing the cost of energy imports from upstream networks and implementing demand response programs to balance supply and demand, considering the constraints of the IES. By utilising the Karush-Kuhn-Tucker (KKT) optimality conditions and the big-M method, the bi-level problem is converted into a single-level Mixed-Integer Linear Programming (MILP) problem. The proposed model and methodology are validated through case studies on an integrated energy network based on the 16-bus 33 kV UK generic distribution system, a 20-node gas network and a 30-node heat network, demonstrating their effectiveness in the IES. The research demonstrates that coupled energy networks are viable for creating efficient and flexible IES. The strategic scheduling of energy hubs, equipped with generation equipment such as RES, storage, P2G and other conversion technologies operating within the IES with P2P energy trading, not only meets diverse energy demands but also enhances the sustainability and economic viability of the energy system.

Suggested Citation

  • Rowe, Kirkland & Cooke, Kavian & Mokryani, Geev & Campean, Felician & Chambers, Therese, 2025. "A bi-level multi-node optimal siting, sizing, and operation of multi energy system in an integrated energy network of electricity-gas-heat with peer-to-peer trading," Applied Energy, Elsevier, vol. 382(C).
    • Handle: RePEc:eee:appene:v:382:y:2025:i:c:s0306261924026400
    DOI: 10.1016/j.apenergy.2024.125256
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    References listed on IDEAS

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    1. Muhammad Haris Khan & Abasin Ulasyar & Abraiz Khattak & Haris Sheh Zad & Mohammad Alsharef & Ahmad Aziz Alahmadi & Nasim Ullah, 2022. "Optimal Sizing and Allocation of Distributed Generation in the Radial Power Distribution System Using Honey Badger Algorithm," Energies, MDPI, vol. 15(16), pages 1-18, August.
    2. Patrick Sunday Onen & Geev Mokryani & Rana H. A. Zubo, 2022. "Planning of Multi-Vector Energy Systems with High Penetration of Renewable Energy Source: A Comprehensive Review," Energies, MDPI, vol. 15(15), pages 1-25, August.
    3. Liu, Ye & Wu, Xiaogang & Du, Jiuyu & Song, Ziyou & Wu, Guoliang, 2020. "Optimal sizing of a wind-energy storage system considering battery life," Renewable Energy, Elsevier, vol. 147(P1), pages 2470-2483.
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