Optimizing Energy Usage and Smoothing Load Profile via a Home Energy Management Strategy with Vehicle-to-Home and Energy Storage System

Modawy Adam Ali Abdalla, Wang Min (), Gehad Abdullah Amran (), Amerah Alabrah, Omer Abbaker Ahmed Mohammed, Hussain AlSalman and Bassiouny Saleh
Additional contact information
Modawy Adam Ali Abdalla: College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China
Wang Min: College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China
Gehad Abdullah Amran: Department of Management Science and Engineering, Dalian University of Technology, Dalian 116024, China
Amerah Alabrah: Department of Information Systems, College of Computer and Information Science, King Saud University, Riyadh 11543, Saudi Arabia
Omer Abbaker Ahmed Mohammed: School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510006, China
Hussain AlSalman: Department of Computer Science, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia
Bassiouny Saleh: College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

Sustainability, 2023, vol. 15, issue 20, 1-28

Abstract: This study investigates an energy utilization optimization strategy in a smart home for charging electric vehicles (EVs) with/without a vehicle-to-home (V2H) and/or household energy storage system (HESS) to improve household energy utilization, smooth the load profile, and reduce electricity bills. The proposed strategy detects EV arrival and departure time, establishes the priority order between EV and HESS during charge and discharge, and ensures that the EV battery state of energy at the departure time is sufficient for its travel distance. It also ensures that the EV and HESS are charged when electricity prices are low and discharged in peak hours to reduce net electricity expenditure. The proposed strategy operates in different modes to control the energy amount flowing from the grid to EV and/or HESS and the energy amount drawn from the HESS and/or EV to feed the demand to maintain the load curve level within the average limits of the daily load curve. Four different scenarios are presented to investigate the role of HESS and EV technology in reducing electricity bills and smoothing the load curve in the smart house. The results demonstrate that the proposed strategy effectively reduces electricity costs by 12%, 15%, 14%, and 17% in scenarios A, B, C, and D, respectively, and smooths the load profile. Transferring valley electricity by V2H can reduce the electricity costs better than HESS, whereas HESS is better than EV at flattening the load curve. Transferring valley electricity through both V2H and HESS gives better results in reducing electricity costs and smoothing the load curve than transferring valley electricity by HESS or V2H alone.

Keywords: electric vehicles; vehicle-to-home; electricity bill; household energy storage system; load curve (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/15/20/15046/pdf (application/pdf)
https://www.mdpi.com/2071-1050/15/20/15046/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:15:y:2023:i:20:p:15046-:d:1262971

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().