Integrated strategic energy mix and energy generation planning with multiple sustainability criteria and hierarchical stakeholders

Chandra Ade Irawan, Dylan Jones, Peter Hofman, Lina Zhang

Research output: Journal PublicationArticlepeer-review

Abstract

This paper proposes a combination of two optimization models for simultaneously determining strategic energy planning at both national and regional levels. The first model deals with a single-period energy mix where the electricity production configuration at a future date (e.g., 2050), based on the available generation sources, is optimally obtained. An optimization model, based on a non-linear goal programming method, is designed to ensure a mixed balance between national and regional goals. The desired energy mix configuration, which is the solution obtained by solving the first model, is then fed into the second model as the main data input. In the second model, a multiple-period generation expansion plan is designed which optimizes the energy transition over the time horizon from the present until the future planning date (2050). The model considers uncertain parameters, including the regional energy demand, fuel cost, and national peak load. A two-stage stochastic programming model is developed where the sample average approximation approach is used as a method of solution. The practical use of the proposed models has been assessed through application to the electricity generation system in China.

Original languageEnglish
JournalEuropean Journal of Operational Research
DOIs
Publication statusAccepted/In press - 2022

Keywords

  • Energy planning
  • Goal programming
  • Multiple objective programming
  • Two-stage stochastic programming

ASJC Scopus subject areas

  • Computer Science (all)
  • Modelling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management
  • Industrial and Manufacturing Engineering

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