LAPSE:2023.28003
Published Article

LAPSE:2023.28003
Two-Stage Energy Management Strategy of EV and PV Integrated Smart Home to Minimize Electricity Cost and Flatten Power Load Profile
April 11, 2023
Abstract
The efficient use of the incorporation of photovoltaic generation (PV) and an electric vehicle (EV) with the home energy management system (HEMS) can play a significant role in improving grid stability in the residential area and bringing economic benefit to the homeowner. Therefore, this paper presents an energy management strategy in a smart home that integrates an electric vehicle with/without PV generation. The proposed strategy seeks to reduce the household electricity costs and flatten the load curve based on time-of-use pricing, time-varying household power demand, PV generation profile, and EV parameters (arrival and departure times, minimum and maximum limit of the state-of-charge, and initial state-of-charge). The proposed control strategy is divided into two stages: Stage A, which operates in three operating modes according to the unavailability of PV power generation, and Stage B, which operates in five operating modes according to the availability of PV generation. In this study, the proposed strategy enables controlling the amount of energy absorbed by the EV from the grid and/or PV and the amount of energy injected from the EV to the load to ensure that the household electricity costs are minimized, and the household power load profile is flattened. The findings show that both household electricity costs reduction and flattening of the power load profile are achieved. Moreover, the corresponding simulation results exhibit that the proposed strategy for the smart home with EV and PV provides better results than the smart home with EV and without PV in terms of electricity costs reduction and power load profile flattening.
The efficient use of the incorporation of photovoltaic generation (PV) and an electric vehicle (EV) with the home energy management system (HEMS) can play a significant role in improving grid stability in the residential area and bringing economic benefit to the homeowner. Therefore, this paper presents an energy management strategy in a smart home that integrates an electric vehicle with/without PV generation. The proposed strategy seeks to reduce the household electricity costs and flatten the load curve based on time-of-use pricing, time-varying household power demand, PV generation profile, and EV parameters (arrival and departure times, minimum and maximum limit of the state-of-charge, and initial state-of-charge). The proposed control strategy is divided into two stages: Stage A, which operates in three operating modes according to the unavailability of PV power generation, and Stage B, which operates in five operating modes according to the availability of PV generation. In this study, the proposed strategy enables controlling the amount of energy absorbed by the EV from the grid and/or PV and the amount of energy injected from the EV to the load to ensure that the household electricity costs are minimized, and the household power load profile is flattened. The findings show that both household electricity costs reduction and flattening of the power load profile are achieved. Moreover, the corresponding simulation results exhibit that the proposed strategy for the smart home with EV and PV provides better results than the smart home with EV and without PV in terms of electricity costs reduction and power load profile flattening.
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Keywords
electric vehicle, electricity cost, energy management strategy, photovoltaic, smart home
Subject
Suggested Citation
Abdalla MAA, Min W, Mohammed OAA. Two-Stage Energy Management Strategy of EV and PV Integrated Smart Home to Minimize Electricity Cost and Flatten Power Load Profile. (2023). LAPSE:2023.28003
Author Affiliations
Abdalla MAA: College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China; Department of Electrical and Electronic Engineering, College of Engineering Science, Nyala University, Nyala 63311, Sudan [ORCID]
Min W: College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China [ORCID]
Mohammed OAA: Department of Electrical and Electronic Engineering, College of Engineering Science, Nyala University, Nyala 63311, Sudan; School of Automation, Nanjing University of Science and Technology, Nanjing 210094, China [ORCID]
Min W: College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China [ORCID]
Mohammed OAA: Department of Electrical and Electronic Engineering, College of Engineering Science, Nyala University, Nyala 63311, Sudan; School of Automation, Nanjing University of Science and Technology, Nanjing 210094, China [ORCID]
Journal Name
Energies
Volume
13
Issue
23
Article Number
E6387
Year
2020
Publication Date
2020-12-03
ISSN
1996-1073
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Original Submission
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PII: en13236387, Publication Type: Journal Article
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LAPSE:2023.28003
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https://doi.org/10.3390/en13236387
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