loading page

A Multi-Objective Interval Optimization Approach to Expansion Planning of Active Distribution System with Distributed Internet Data Centers and Renewable Energy Resources
  • +3
  • Yuying Zhang,
  • Chen Liang,
  • Han Wang,
  • Jiayi Zhang,
  • Bo Zeng,
  • Wenxia Liu
Yuying Zhang
North China Electric Power University
Author Profile
Chen Liang
North China Electric Power University
Author Profile
Han Wang
North China Electric Power University
Author Profile
Jiayi Zhang
North China Electric Power University

Corresponding Author:[email protected]

Author Profile
Bo Zeng
North China Electric Power University
Author Profile
Wenxia Liu
North China Electric Power University
Author Profile

Abstract

With the development of the digital economy, the power demand for data centers (DCs) is rising rapidly, which presents a challenge to the economic and low-carbon operation of the future distribution network. To this end, this paper fully considers the multiple flexibility of DC and its impact on the distribution network, and establishes a collaborative planning model of DC and distribution network. In this model, the interval method is utilized to capture the inherent uncertainties within the system (such as the renewable energy source (RES) output, wholesale market price, power load demand, carbon emission factor and workloads), and the planning model is transformed into a multi-objective optimization problem with interval parameters problem (IMOP) to minimize economic cost and carbon emission. On this basis, an interval multi-objective optimization evolutionary algorithm based on decomposition (IMOEA/D) is proposed to solve the IMOP and obtain the Pareto optimal solution while retaining all the uncertainty information. Finally, an improved IEEE 33-node distribution network is utilized as an example for simulation and analysis to confirm the efficacy of the proposed approach.
Submitted to IET Generation, Transmission & Distribution
15 Jul 20241st Revision Received
22 Jul 2024Submission Checks Completed
22 Jul 2024Assigned to Editor
22 Jul 2024Review(s) Completed, Editorial Evaluation Pending
22 Jul 2024Reviewer(s) Assigned
06 Aug 2024Editorial Decision: Accept