Greedy Algorithm for Routing Power and Source Assignment on a Digital Microgrid

被引:1
|
作者
Jiang, Zhengqi [1 ]
Sahasrabudhe, Vinit [1 ]
Grebel, Haim [1 ]
Mohamed, Ahmed [2 ]
Rojas-Cessa, Roberto [1 ]
机构
[1] New Jersey Inst Technol, Dept Elect & Comp Engn, Newark, NJ 07102 USA
[2] CUNY City Coll, Dept Elect Engn, New York, NY 11031 USA
来源
2019 INTERNATIONAL CONFERENCE ON INTERNET OF THINGS (ITHINGS) AND IEEE GREEN COMPUTING AND COMMUNICATIONS (GREENCOM) AND IEEE CYBER, PHYSICAL AND SOCIAL COMPUTING (CPSCOM) AND IEEE SMART DATA (SMARTDATA) | 2019年
关键词
Digital Microgrid; power grid; integer linear programming; routing energy; distributed energy resources; Di-jkstra algorithm; COMPLEXITY; NETWORKS; SYSTEMS;
D O I
10.1109/iThings/GreenCom/CPSCom/SmartData.2019.00141
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
In this paper, we propose the Greedy SmAlleSt-cost Path first (GRASP) algorithm to route power from sources to loads in a digital microgrid (DMG). Routing of power from Distributed Energy Resources (DERs) to loads of a DMG comprises the matching loads to DERs and the selection of the smallest -cost path from a load to its supplying DERs. In such a microgrid, one DER may supply power to one or many loads, and one or many DERs may supply the power requested by a load. We compare GRASP with an optimal method based on integer linear programming. GRASP addresses the NP-completeness of the optimal solution while finding paths with comparable costs. GRASP uses heuristics to select match sources and loads and to select the lowest -cost paths in the DMG. We compare the cost achieved by both methods on different test networks to show the trade-offs between lowering complexity and achieving optimal-cost paths. Our results show that GRASP approaches the costs attained by the optimal solution by small margins.
引用
收藏
页码:761 / 767
页数:7
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