Peak load reduction through dynamic pricing for electric vehicle charging

• Published in: International journal of electrical power & energy systems Vol. 113; pp. 117 - 128
• Main Authors: Limmer, S., Rodemann, T.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.12.2019
• Subjects: Dynamic pricing; Electric vehicle; Evolutionary algorithm; Linear programming; Multi-objective optimization; Peak shaving; Dynamic pricing; Linear programming; Electric vehicle; Multi-objective optimization; Peak shaving; Evolutionary algorithm
• ISSN: 0142-0615; 1879-3517
• DOI: 10.1016/j.ijepes.2019.05.031

•Approach for setting dynamic prices and charging schedules considering peak load.•Online approach, which deals with uncertainties in user preferences.•Consideration of charging station operator’s profit in multi-objective optimization.•Evaluation of approach in simulations based on a typical German use case.•Description and evaluation of approach for accelerating optimizations. Typically, peak demand charges account for a considerable part of the operating costs of public electric vehicle charging stations. An intelligent control of the charging processes can help to reduce the peak load and the corresponding fees. This can be additionally supported by the use of a dynamic pricing scheme, which encourages customers to provide as much flexibility as possible. The present work proposes a framework for the setting of dynamic price offers for different charging deadlines and the scheduling of charging processes with the objectives of maximizing the charging station operator’s daily profit and reducing the peak of the electrical load. In a simulation study based on a use case typical for Germany, it is shown that the proposed approach can increase the charging station operator’s yearly profit by several thousand euros compared to a pricing and scheduling scheme without consideration of the peak load. Furthermore, an approach for increasing the scalability of the employed optimization of price offers is proposed and evaluated.