Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.3390/a12100208 | ALGORITHMS |
Keywords | Field | DocType |
charging station,convex optimization,multi-objective programming,polyhedral approximation,scaling method | Heuristic,Mathematical optimization,Charging station,Multi-objective optimization,Integer programming,Conic section,Convex optimization,Mathematics,Convex optimization algorithm,Electricity pricing | Journal |
Volume | Issue | Citations |
12 | 10 | 1 |
PageRank | References | Authors |
0.35 | 0 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jing Zhang | 1 | 373 | 101.39 |
| Xiangpeng Zhan | 2 | 1 | 0.35 |
| Taoyong Li | 3 | 1 | 0.35 |
| Linru Jiang | 4 | 1 | 0.35 |
| Jun Yang | 5 | 8 | 2.27 |
| Yuanxing Zhang | 6 | 1 | 0.35 |
| Xiaohong Diao | 7 | 1 | 0.68 |
| Sining Han | 8 | 1 | 0.35 |