DocumentCode :
1758464
Title :
Management Scheme for Increasing the Connectivity of Small-Scale Renewable DG
Author :
Eltantawy, Ayman B. ; Salama, Magdy M. A.
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Waterloo, Waterloo, ON, Canada
Volume :
5
Issue :
4
fYear :
2014
fDate :
Oct. 2014
Firstpage :
1108
Lastpage :
1115
Abstract :
This paper presents a planning model and an active network management (ANM) scheme for increasing small-scale renewable distributed generation (DG) capacity in distribution networks. The capacity of each DG unit is assumed to include two components: 1) unconditional and 2) conditional. Unconditional DG capacity is calculated using an appropriate economic model that ensures adequate profit for DG investors. For all online distribution system conditions, a DG unit whose capacity is less than or equal to the unconditional DG capacity is granted permission to inject power into the system without curtailment. The first phase of this work involved the development of a proposed planning model that maximizes the number of DG units installed based on the calculated unconditional capacity. Any capacity higher than the unconditional DG capacity is considered conditional capacity. The second phase of this work is focused on an ANM scheme for minimizing the curtailment of conditional DG capacity using a novel scalable optimization model. The simulation results show that the proposed planning model with the ANM scheme significantly increases the photovoltaic (PV) DG capacity that can be installed. The simulation results indicate that online operation of the proposed ANM scheme would provide a favorable outcome and enhanced performance.
Keywords :
distributed power generation; genetic algorithms; photovoltaic power systems; power distribution planning; power system management; ANM scheme; PV power; active network management; conditional DG capacity; distribution networks; photovoltaic power; planning model; scalable optimization model; small-scale renewable DG unit; small-scale renewable distributed generation capacity; unconditional DG capacity; Distributed power generation; Economics; Genetic algorithms; Photovoltaic systems; Power system planning; Voltage control; Active network management (ANM); distributed generation (DG); genetic algorithm (GA); photovoltaic (PV) power; unbalanced distribution systems;
fLanguage :
English
Journal_Title :
Sustainable Energy, IEEE Transactions on
Publisher :
ieee
ISSN :
1949-3029
Type :
jour
DOI :
10.1109/TSTE.2014.2329647
Filename :
6855333
Link To Document :
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