دورية أكاديمية

A Convex Optimization Algorithm for Electricity Pricing of Charging Stations

التفاصيل البيبلوغرافية
العنوان: A Convex Optimization Algorithm for Electricity Pricing of Charging Stations
المؤلفون: Jing Zhang, Xiangpeng Zhan, Taoyong Li, Linru Jiang, Jun Yang, Yuanxing Zhang, Xiaohong Diao, Sining Han
المصدر: Algorithms, Vol 12, Iss 10, p 208 (2019)
بيانات النشر: MDPI AG, 2019.
سنة النشر: 2019
المجموعة: LCC:Industrial engineering. Management engineering
LCC:Electronic computers. Computer science
مصطلحات موضوعية: charging station, convex optimization, multi-objective programming, polyhedral approximation, scaling method, Industrial engineering. Management engineering, T55.4-60.8, Electronic computers. Computer science, QA75.5-76.95
الوصف: The problem of electricity pricing for charging stations is a multi-objective mixed integer nonlinear programming. Existing algorithms have low efficiency in solving this problem. In this paper, a convex optimization algorithm is proposed to get the optimal solution quickly. Firstly, the model is transformed into a convex optimization problem by second-order conic relaxation and Karush−Kuhn−Tucker optimality conditions. Secondly, a polyhedral approximation method is applied to construct a mixed integer linear programming, which can be solved quickly by branch and bound method. Finally, the model is solved many times to obtain the Pareto front according to the scalarization basic theorem. Based on an IEEE 33-bus distribution network model, simulation results show that the proposed algorithm can obtain an exact global optimal solution quickly compared with the heuristic method.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 1999-4893
Relation: https://www.mdpi.com/1999-4893/12/10/208; https://doaj.org/toc/1999-4893
DOI: 10.3390/a12100208
URL الوصول: https://doaj.org/article/72fcb8f30eb343d4ad8b3f8aead16049
رقم الأكسشن: edsdoj.72fcb8f30eb343d4ad8b3f8aead16049
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:19994893
DOI:10.3390/a12100208