Data-driven cost-effective capacity provisioning scheme in electric vehicle charging facility. (November 2022)
- Record Type:
- Journal Article
- Title:
- Data-driven cost-effective capacity provisioning scheme in electric vehicle charging facility. (November 2022)
- Main Title:
- Data-driven cost-effective capacity provisioning scheme in electric vehicle charging facility
- Authors:
- Kim, Jangkyum
Oh, Hyeontaek
Lee, Joohyung - Abstract:
- Abstract: In the actual power system, managing the amount of Contract power, which directly related to the capacity of electric vehicle (EV) charging facility, becomes an important issue to stabilize the power system and minimize the financial loss of the EV charging facility. Since, determining the Contract power is one of critical issues to implement the cost-effective charging service in EV charging facility, it influences the charging decision of EV users. To consider the concern of both the operator and EV users, this paper derives analytical models considering not only electricity tariff polices but also EV users' inflow rate and behavior (i.e., the users' willingness to charge and leaving without charging probability) based on an open-dataset about EV users. Then, using the analytical models, this paper proposes a novel method to optimize the capacity of EV charging facility by considering the relationship between various monetary factors and Contract power . Finally, applying the obtained optimal Contract power in actual power system and market environment, we confirm that the proposed scheme could achieve reduction of overall monetary cost 24.6% compared to other benchmark models. Graphical abstract: Highlights: Analyze revenues of EV charging facility considering users and power system policies. Formulate EV users' willingness-to-charge regarding power sales price. Formulate EV users' leaving-without-charging service to model uncertain situation. Propose a methodAbstract: In the actual power system, managing the amount of Contract power, which directly related to the capacity of electric vehicle (EV) charging facility, becomes an important issue to stabilize the power system and minimize the financial loss of the EV charging facility. Since, determining the Contract power is one of critical issues to implement the cost-effective charging service in EV charging facility, it influences the charging decision of EV users. To consider the concern of both the operator and EV users, this paper derives analytical models considering not only electricity tariff polices but also EV users' inflow rate and behavior (i.e., the users' willingness to charge and leaving without charging probability) based on an open-dataset about EV users. Then, using the analytical models, this paper proposes a novel method to optimize the capacity of EV charging facility by considering the relationship between various monetary factors and Contract power . Finally, applying the obtained optimal Contract power in actual power system and market environment, we confirm that the proposed scheme could achieve reduction of overall monetary cost 24.6% compared to other benchmark models. Graphical abstract: Highlights: Analyze revenues of EV charging facility considering users and power system policies. Formulate EV users' willingness-to-charge regarding power sales price. Formulate EV users' leaving-without-charging service to model uncertain situation. Propose a method to set a proper contract power capacity of the charging facility. … (more)
- Is Part Of:
- Computers & industrial engineering. Volume 173(2022)
- Journal:
- Computers & industrial engineering
- Issue:
- Volume 173(2022)
- Issue Display:
- Volume 173, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 173
- Issue:
- 2022
- Issue Sort Value:
- 2022-0173-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-11
- Subjects:
- Electric vehicle -- EV user behavior -- Contract power -- Cost minimization
Engineering -- Data processing -- Periodicals
Industrial engineering -- Periodicals
620.00285 - Journal URLs:
- http://www.sciencedirect.com/science/journal/03608352 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.cie.2022.108743 ↗
- Languages:
- English
- ISSNs:
- 0360-8352
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3394.713000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 24158.xml