DocumentCode :
740563
Title :
A Generalized Approach for DG Planning and Viability Analysis Under Market Scenario
Author :
Jain, Nikhil ; Singh, S.N. ; Srivastava, S.C.
Author_Institution :
Dept. of Electr. Eng., Indian Inst. of Technol. Kanpur, Kanpur, India
Volume :
60
Issue :
11
fYear :
2013
Firstpage :
5075
Lastpage :
5085
Abstract :
In this paper, a heuristic approach is considered for the distributed generator (DG) placement to minimize system loss. The constriction-factor particle swarm optimization method is used as an optimization tool for the planning problem. A Monte-Carlo-simulation-based probabilistic load flow is proposed to find the unavailability of the DGs in the planning problem. The net-present-value analysis of the planning in electricity-market scenario is carried out for biomass, wind, solar-photovoltaic, and diesel-engine DGs to see their viability under bilateral- and competitive market scenarios. Various factors such as profit, incentives on capital, replacement, startup, operation, and maintenance costs have been taken into account. The proposed market-based analysis is simple and generic, and can provide choices to the distribution utilities to select DGs under various constraints. The effectiveness of the proposed method is tested on 16-, 33-, and 69-bus distribution systems, and results are compared with an improved analytical method suggested in literature.
Keywords :
Monte Carlo methods; distributed power generation; particle swarm optimisation; power generation planning; power markets; DG planning; Monte Carlo simulation; constriction-factor particle swarm optimization; distributed generator; market scenario; net-present-value analysis; probabilistic load flow; system loss; viability analysis; Batteries; Electricity supply industry; Fuels; Particle swarm optimization; Planning; Probabilistic logic; Wind speed; Distribution load flow; Monte Carlo simulation (MCS); particle swarm optimization (PSO); renewable energy sources (RES);
fLanguage :
English
Journal_Title :
Industrial Electronics, IEEE Transactions on
Publisher :
ieee
ISSN :
0278-0046
Type :
jour
DOI :
10.1109/TIE.2012.2219840
Filename :
6307848
Link To Document :
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