Semimonthly

ISSN 1000-1026

CN 32-1180/TP

+Advanced Search 中文版
Multi-objective Optimal Dispatch Method for Integrated Energy System Considering Exergy Efficiency
Author:
Affiliation:

1. Tsinghua-Berkeley Shenzhen Institute, Tsinghua University, Shenzhen 518055, China; 2. Department of Electrical Engineering, Tsinghua University, Beijing 100084, China; 3. State Key Laboratory of Control and Simulation of Power System and Generation Equipments(Tsinghua University), Beijing 100084, China; 4. State Key Laboratory of Alternate Electric Power System with Renewable Energy Sources(North China Electric Power University), Beijing 102206, China

Abstract:

A multi-objective optimal dispatch method for an integrated energy system(IES), concerning energy efficiency, economy and environment is proposed, and its corresponding solution method is proposed, which can bring up an energy-saving, economic and environmental-friendly dispatching plan for the IES. Firstly, the model of multi-objective function for the IES, which takes exergy efficiency into consideration, is established to meet the demand of an economic, efficient and environmental-friendly IES. Secondly, a convex IES mathematical model for the multi-objective dispatch method is established with convex relaxation method to preserve the convexity. Thirdly, the solution method for the multi-objective optimization model is studied, the scalarization method is used to find the Pareto front(PF)of the convex model and a selection method is brought up to choose the multi-objective optimal dispatch plan from the PF. Numerical results based on a case from Guizhou Province in China validate the applicability of the proposed multi-objective dispatch method in efficiently bringing up a dispatch plan for the IES and making the IES operated with a better overall performance.

Keywords:

Foundation:

Get Citation
[1]CHEN Cong, SHEN Xinwei, XIA Tian, et al. Multi-objective Optimal Dispatch Method for Integrated Energy System Considering Exergy Efficiency[J]. Automation of Electric Power Systems,2019,43(12):60-67. DOI:10.7500/AEPS20180731010
Copy
Share
History
  • Received:July 31,2018
  • Revised:April 29,2019
  • Adopted:March 21,2019
  • Online: April 26,2019
  • Published: June 25,2019