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A new framework for hierarchical multi-objective energy hub planning considering reliability

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  • Oh, Byeong Chan
  • Son, Yeong Geon
  • Acquah, Moses Amoasi
  • Kim, Sung Yul

Abstract

The concept of an Energy Hub (EH) is a promising approach for constructing a Multi-Energy System (MES). The configuration of equipment within the EH is crucial for ensuring the efficiency, cost-effectiveness, and reliability of MES. This paper introduces a novel hierarchical energy hub planning (H-EHP) approach for EH configuration, employing a multi-objective optimization algorithm to plan optimal EH configurations. Utilizing an epsilon constraint-based Pareto front technique, H-EHP optimizes EH capacity, location, and number of installations at each hierarchical level, and economic and reliability feasibility of the system is hierarchically evaluated. The H-EHP is modeled in three stages for result analysis: 1) Power-to-Power (P2P) equipment-based modeling, 2) Power-to-Gas (P2G) equipment-based modeling, and 3) Sector Coupling (SC) equipment-based modeling. The distribution network and various operating characteristics, along with constraints of EH equipment, are modeled. A novel analysis method based on Branch Rolling is introduced for the reliability assessment of EH-linked distribution network. Mixed-integer linear programming (MILP) is employed to identify the optimal H-EHP that minimizes both economic and reliability aspects through an epsilon-constrained Multi-Objective Problem (MOP). Testing on the IEEE-33 bus system and a 7-node gas system confirms the superiority of the proposed theory through three casestudies. The results show that cost-effectiveness and system reliability are analyzed for each EH stage. Notably, HL1, relying solely on electrical equipment, exhibits poor cost-effectiveness. HL2, incorporating P2G-based equipment, demonstrates significant improvements with F1 enhanced by 29.64 % and F2 by 19.07 %. The HL3 outcome highlights the Sector-Coupling (SC) effect, with F1 and F2 showing improvements of 34.85 % and 45.58 %, respectively, compared to HL1. The analysis of hierarchical EH configuration and results underscore the efficacy of the H-EHP method for optimal EH planning.

Suggested Citation

  • Oh, Byeong Chan & Son, Yeong Geon & Acquah, Moses Amoasi & Kim, Sung Yul, 2024. "A new framework for hierarchical multi-objective energy hub planning considering reliability," Energy, Elsevier, vol. 303(C).
    • Handle: RePEc:eee:energy:v:303:y:2024:i:c:s0360544224016621
    DOI: 10.1016/j.energy.2024.131889
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    1. Morshed, Mohammad Javad & Hmida, Jalel Ben & Fekih, Afef, 2018. "A probabilistic multi-objective approach for power flow optimization in hybrid wind-PV-PEV systems," Applied Energy, Elsevier, vol. 211(C), pages 1136-1149.
    2. Moretti, Luca & Martelli, Emanuele & Manzolini, Giampaolo, 2020. "An efficient robust optimization model for the unit commitment and dispatch of multi-energy systems and microgrids," Applied Energy, Elsevier, vol. 261(C).
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