Day‐ahead charging operation of electric vehicles with on‐site renewable energy resources in a mixed integer linear programming framework. Issue 3 (22nd April 2020)

• Record Type: Journal Article
• Authors: Şengör, İbrahim; Erenoğlu, Ayşe Kübra; Erdinç, Ozan; Taşcıkaraoğlu, Akın; Catalão, João P.S.
• Is Part Of: IET smart grid. Volume 3:Issue 3(2020)
• Page Start: 367
• Page End: 375
• Publication Date: 2020-04-22
• Subjects: linear programming -- pricing -- electric vehicles -- integer programming -- battery storage plants -- demand side management -- photovoltaic power systems -- smart power grids -- power generation scheduling; electric vehicles -- on‐site renewable energy resources -- mixed integer linear programming framework -- large‐scale penetration -- power system -- distribution system operators -- DSOs -- demand response strategies -- smart grid paradigm -- different aggregators -- DR strategies -- PLL -- peak load limitation -- day‐ahead charging operation -- peak load limitation based DR strategies -- operational flexibility -- daily solar irradiation data -- scenario‐based approach -- PV generation -- related EVPL -- arrival time -- state‐of‐energy -- related EV owners -- EVPLs -- EV parking lots; B0260 Optimisation techniques -- B8110B Power system management, operation and economics -- B8250 Solar power stations and photovoltaic power systems -- B8260 Other power stations and plants -- B8520 Transportation; Smart power grids -- Periodicals; Computer science -- Periodicals; Energy industries -- Periodicals; Broadcasting -- Periodicals; 333.79110285
• DOI: 10.1049/iet-stg.2019.0282
• Languages: English
• ISSNs: 2515-2947

Abstract

Abstract : The large‐scale penetration of electric vehicles (EVs) into the power system will provoke new challenges needed to be handled by distribution system operators (DSOs). Demand response (DR) strategies play a key role in facilitating the integration of each new asset into the power system. With the aid of the smart grid paradigm, a day‐ahead charging operation of large‐scale penetration of EVs in different regions that include different aggregators and various EV parking lots (EVPLs) is propounded in this study. Moreover, the uncertainty of the related EV owners, such as the initial state‐of‐energy and the arrival time to the related EVPL, is taken into account. The stochasticity of PV generation is also investigated by using a scenario‐based approach related to daily solar irradiation data. Last but not least, the operational flexibility is also taken into consideration by implementing peak load limitation (PLL) based DR strategies from the DSO point of view. To reveal the effectiveness of the devised scheduling model, it is performed under various case studies that have different levels of PLL, and for the cases with and without PV generation.