Intelligent Energy Management in a Prosumer Community Considering the Load Factor Enhancement

Fernando V. Cerna, Mahdi Pourakbari-Kasmaei, Luizalba S. S. Pinheiro, Ehsan Naderi, Matti Lehtonen and Javier Contreras
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Fernando V. Cerna: Department of Electrical Engineering, Federal University of Roraima, Boa Vista 69310-000, Brazil
Mahdi Pourakbari-Kasmaei: Department of Electrical Engineering and Automation, Aalto University, 02150 Espoo, Finland
Luizalba S. S. Pinheiro: Department of Electrical Engineering, Federal University of Roraima, Boa Vista 69310-000, Brazil
Ehsan Naderi: School of Electrical, Computer, and Biomedical Engineering, Southern Illinois University, Carbondale, IL 62901, USA
Matti Lehtonen: Department of Electrical Engineering and Automation, Aalto University, 02150 Espoo, Finland
Javier Contreras: School of Industrial Engineering, University of Castilla-La Mancha, 13071 Ciudad Real, Spain

Energies, 2021, vol. 14, issue 12, 1-24

Abstract: In prosumers’ communities, the use of storage batteries (SBs) as support for photovoltaic (PV) sources combined with coordination in household appliances usage guarantees several gains. Although these technologies increase the reliability of the electricity supply, the large-scale use of home appliances in periods of lower solar radiation and low electricity tariff can impair the performance of the electrical system. The appearance of new consumption peaks can lead to disturbances. Moreover, the repetition of these events in the short term can cause rapid fatigue of the assets. To address these concerns, this research proposes a mixed-integer linear programming (MILP) model aiming at the optimal operation of the SBs and the appliance usage of each prosumer, as well as a PV plant within a community to achieve the maximum load factor (LF) increase. Constraints related to the household appliances, including the electric vehicle (EV), shared PV plant, and the SBs, are considered. Uncertainties in consumption habits are simulated using a Monte Carlo algorithm. The proposed model was solved using the CPLEX solver. The effectiveness of our proposed model is evaluated with/without the LF improvement. Results corroborate the efficient performance of the proposed tool. Financial benefits are obtained for both prosumers and the energy company.

Keywords: community of prosumers; new consumption peak; shared PV plant; storage batteries; load factor (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: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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