Day Ahead Operation Cost Optimization for Energy Communities

Maria Fotopoulou, George J. Tsekouras, Andreas Vlachos, Dimitrios Rakopoulos (), Ioanna Myrto Chatzigeorgiou, Fotios D. Kanellos and Vassiliki Kontargyri
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Maria Fotopoulou: Department of Electrical and Electronics Engineering, University of West Attica, 12241 Athens, Greece
George J. Tsekouras: Department of Electrical and Electronics Engineering, University of West Attica, 12241 Athens, Greece
Andreas Vlachos: Regulatory Authority for Energy, Waste and Water, 15125 Athens, Greece
Dimitrios Rakopoulos: Centre for Research and Technology Hellas, 15125 Athens, Greece
Ioanna Myrto Chatzigeorgiou: School of Electrical and Computer Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
Fotios D. Kanellos: School of Electrical and Computer Engineering, Technical University of Crete, 73100 Chania, Greece
Vassiliki Kontargyri: Department of Electrical and Electronics Engineering, University of West Attica, 12241 Athens, Greece

Energies, 2025, vol. 18, issue 5, 1-20

Abstract: Energy communities constitute the main collective form for energy consumers to participate in the current energy transition. The purpose of this research paper is to present a tool that assists energy communities to achieve fair and sustainable daily operation. In this context, the proposed algorithm (i) assesses the day-ahead operation cost (or profit) of energy communities, taking into consideration photovoltaic (PV) production, battery energy storage system (BESS), and flexible loads, as well as the potential profit from selling energy to the power system, under the net billing scheme, and (ii) compares the derived cost for each member with the cost for non-cooperative operation, as single prosumers. Taking the aforementioned costs or profits into consideration, the developed algorithm then proposes three cost-sharing options for the members, peer-to-peer (P2P), so that their participation in the community is more beneficial than individual operation. The algorithm is tested on a hypothetical energy community in Greece, highlighting the importance of the cooperation amongst the members of the community for their mutual benefit; for the simulated case of different PV shares, the cooperation can result in a 24.5% cost decrease, while having a BESS can reduce the cost by 25.0%.

Keywords: optimization; energy communities; cost minimization; energy sharing; renewables; battery energy storage system (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: 2025
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