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Authors
Affiliations
1 Department of Electrical Engineering, National Institute of Technical Teachers Training and Research, Chandigarh, IN
2 Department of Electrical and Instrumentation Engineering, Thapar University, IN
Source
ICTACT Journal on Soft Computing, Vol 5, No 2 (2015), Pagination: 917-924
Abstract
An attempt has been made in this article to compare the performances of two multiobjective evolutionary algorithms namely ev-MOGA and GODLIKE. The performances of both are evaluated on risk based optimal power scheduling of virtual power plant. The risk based scheduling is proposed as a conflicting bi objective optimization problem with increased number of durations of day. Both the algorithms are elaborated in detail. Results based on the performance analysis are depicted at the end.
Keywords
MCP (Market Clearing Price), RTO (Regional Transmission Operator), VPP (Virtual Power Plant), RES (Renewable Energy Sources), LCOE (Levelised Cost of Electricity), Distributed Generation (DG).
