Optimal Cooperative Power Management Framework for Smart Buildings Using Bidirectional Electric Vehicle Modes

Author:

Naji EL idrissi Rajaa1ORCID,Ouassaid Mohammed1ORCID,Maaroufi Mohamed1,Cabrane Zineb2,Kim Jonghoon3ORCID

Affiliation:

1. Engineering for Smart and Sustainable Systems Research Center, Mohammadia School of Engineers, Mohammed V University in Rabat, Rabat 10090, Morocco

2. Laboratory of Innovative Technologies, National School of Applied Sciences of Tangier, Abdelmalek Essaadi University, Tetouan 93000, Morocco

3. Department of Electrical Engineering, Chungnam National University, Daejeon 34134, Republic of Korea

Abstract

The high potential for implementing demand management approaches across multiple objectives has been significantly enhanced. This study proposes a cooperative energy management strategy based on the end-user sharing of energy. The proposed method promotes the intelligent charging and discharging of EVs to achieve vehicle-to-anything (V2X) and anything-to-vehicle (X2V) operating modes for both integrated and nonrenewable residential applications. These sharing modes have already been discussed, but resolution approaches are applicable to a specific use case. Other application cases may require additional metrics to plan the fleet of electric vehicles. To avoid that problem, this study proposes the MIP method using a robust Gurobi optimiser based on a generic framework for cooperative power management (CPM). Moreover, the CPM ensures an overall target state of charge (SoC) at leaving time for all the vehicles without generating a rebound peak in total grid power, even without introducing photovoltaic power. Two different methods are proposed based on the flow direction of the EV power. The first method only includes the one-way power flow, while the second increases the two-way power flow between vehicles, operating in vehicle-to-vehicle or vehicle-to-loads modes. A thorough analysis of the findings of the proposed model was conducted to demonstrate the robustness and efficiency of the charging and discharging schedule of several EVs, favouring a sharing economy concept, reducing peak power, and increasing user comfort.

Publisher

MDPI AG

Subject

Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous),Building and Construction

Reference29 articles.

1. Luo, X., Zhu, X., and Lim, E.G. (2019). Exergy and Its Application—Toward Green Energy Production and Sustainable Environment, IntechOpen.

2. A review of optimal charging strategy for electric vehicles under dynamic pricing schemes in the distribution charging network;Amin;Sustainability,2020

3. Robust Optimization-Based Energy Pricing and Dispatching Model Using DSM for Smart Grid Aggregators to Tackle Price Uncertainty;Rehman;Arab. J. Sci. Eng.,2020

4. Review of key management techniques for advanced metering infrastructure;Kebotogetse;Int. J. Distrib. Sens. Netw.,2021

5. A review of demand response in an efficient smart grid environment;Hussain;Electr. J.,2018

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