Integrated Optimal Energy Management of Multi-Microgrid Network Considering Energy Performance Index: Global Chance-Constrained Programming Framework

Mohammad Hemmati (), Navid Bayati and Thomas Ebel
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Mohammad Hemmati: Center for Industrial Electronics, University of Southern Denmark, 6400 Sønderborg, Denmark
Navid Bayati: Center for Industrial Electronics, University of Southern Denmark, 6400 Sønderborg, Denmark
Thomas Ebel: Center for Industrial Electronics, University of Southern Denmark, 6400 Sønderborg, Denmark

Energies, 2024, vol. 17, issue 17, 1-22

Abstract: Distributed generation (DG) sources play a special role in the operation of active energy networks. The microgrid (MG) is known as a suitable substrate for the development and installation of DGs. However, the future of energy distribution networks will consist of more interconnected and complex MGs, called multi-microgrid (MMG) networks. Therefore, energy management in such an energy system is a major challenge for distribution network operators. This paper presents a new energy management method for the MMG network in the presence of battery storage, renewable sources, and demand response (DR) programs. To show the performance of each connected MG’s inefficient utilization of its available generation capacity, an index called unused power capacity (UPC) is defined, which indicates the availability and individual performance of each MG. The uncertainties associated with load and the power output of wind and solar sources are handled by employing the chance-constrained programming (CCP) optimization framework in the MMG energy management model. The proposed CCP ensures the safe operation of the system at the desired confidence level by involving various uncertainties in the problem while optimizing operating costs under Mixed-Integer Linear Programming (MILP). The proposed energy management model is assessed on a sample network concerning DC power flow limitations. The procured power of each MG and power exchanges at the distribution network level are investigated and discussed.

Keywords: energy management; optimization; chance-constrained; multi-microgrid; demand response; renewable energy; confidence level (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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