Handling Non-Linearities in Modelling the Optimal Design and Operation of a Multi-Energy System

Antoine Mallégol (), Arwa Khannoussi, Mehrdad Mohammadi, Bruno Lacarrière and Patrick Meyer ()
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Antoine Mallégol: IMT Atlantique, Lab-STICC, UMR CNRS 6285, F-29238 Brest, France
Arwa Khannoussi: IMT Atlantique, LS2N, UMR CRNS 6004, F-44307 Nantes, France
Mehrdad Mohammadi: Department of Industrial Engineering and Innovation Sciences, Eindhoven University of Technology, 5600 MB Eindhoven, The Netherlands
Bruno Lacarrière: IMT Atlantique, GEPEA, UMR CRNS 6144, F-44307 Nantes, France
Patrick Meyer: IMT Atlantique, Lab-STICC, UMR CNRS 6285, F-29238 Brest, France

Mathematics, 2023, vol. 11, issue 23, 1-28

Abstract: Multi-energy systems (MESs) combining different energy carriers like electricity and heat allow for more efficient and sustainable energy solutions. However, optimizing the design and operation of MESs is challenging due to non-linearities in the mathematical models used, especially the performance curves of technologies like combined heat and power units. Unlike similar work from the literature, this paper proposes an improved piecewise linearization method to efficiently handle the non-linearities, models an MES as a multi-objective mixed-integer linear program (MILP), and solves the optimization problem over a year with hourly resolution to enable detailed operation and faithful system design. The method uses fewer linear pieces to approximate non-linear functions compared to a standard technique, resulting in lower complexity while preserving accuracy. The MES design and operation problem maximizes cost reduction and the rate of renewable energy sources. A case study on an MES with electricity and heat over one year with hourly resolution demonstrates the effectiveness of the new method. It allows for solving a long-term MES optimization problem in reasonable computation times.

Keywords: multi-energy systems; combined heat and power efficiency; multi-objective optimization; piecewise linear approximation; mixed integer linear programming; maximization of cost reduction; maximization of the renewable energy sources rate (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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