Indexed by:

Journal paper

First Author:

Wei Gan

Correspondence Author:

Mingyu Yan

Co-author:

Jianfeng Wen,Wei Yao,Jing Zhang

Journal:

Applied Energy

Included Journals:

SCI

Place of Publication:

United Kingdom

Discipline:

Engineering

First-Level Discipline:

Electrical Engineering

Document Type:

J

Volume:

311

Page Number:

118595

ISSN No.:

0306-2619

Key Words:

Multi-energy system；Joint planning；Energy hub；Low-carbon energy system；Privacy protection；Enhanced Benders decomposition

DOI number:

10.1016/j.apenergy.2022.118595

Date of Publication:

2022-04-01

Impact Factor:

11.446

Abstract:

The construction of the multi-energy system (MES) is regarded as one of the silver bullets that help construct a low-carbon and high-efficiency energy system. In addition to the synergy of multiple energy systems, the coordination of regional and district energy systems can further improve flexibility. However, current studies rarely focus on the joint planning of regional-district MES. Additionally, privacy protection has not been considered in multi-energy system planning yet. This paper proposes a novel low-carbon planning method for joint regional-district MES which ensures the privacy of regional and district energy systems based on the enhanced Benders decomposition. A new Benders cut generation method with refined iteration and improved convergence is designed for the planning model where the subproblem itself is the mixed-integer linear programming. To ensure convergence and optimality, supplementary Benders cuts for convergence restoration are also generated. Numerical results tested on a real-world MES in North China and a modified IEEE RTS-79 40-node MES show the effectiveness of the proposed planning method and solution technique. The simulation results validate that the proposed joint planning method can enhance the economic benefit of planning and reduce carbon emission, and the computational performance of the enhanced Benders decomposition is also validated from the perspectives of both computational accuracy and time. In the real-world MES, the joint planning method saves 8.8% of the total cost and reduces carbon emission by 11.1 % compared to the separate planning method.

Links to published journals:

https://www.sciencedirect.com/science/article/pii/S0306261922000745