Share Your Research, Maximize Your Social Impacts
COMPARATIVE ANALYSIS OF EV-MOGA AND GODLIKE MULTIOBJECTIVE EVOLUTIONARY ALGORITHMS FOR RISK BASED OPTIMAL POWER SCHEDULING OF A VIRTUAL POWER PLANT
Journal: ICTACT Journal on Soft Computing (IJSC) (Vol.5, No. 2)Publication Date: 2015-01-01
Authors : Mahesh S. Narkhede; S. Chatterji; Smarajit Ghosh;
Page : 917-924
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);
Source : Download
Find it from : Google Scholar
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.
Other Latest Articles
- REAL TIME PULVERISED COAL FLOW SOFT SENSOR FOR THERMAL POWER PLANTS USING EVOLUTIONARY COMPUTATION TECHNIQUES
- LOAD PROFILE CLUSTERING: AN ALGORITHMIC APPROACH WITH IMPROVED REPLACEMENT IN BEE OPTIMIZATION ALGORITHM
- WORD SENSE DISAMBIGUATION METHOD USING SEMANTIC SIMILARITY MEASURES AND OWA OPERATOR
- IRIS RECOGNITION BASED ON KERNELS OF SUPPORT VECTOR MACHINE
- FUZZY INFERENCE BASED LEAK ESTIMATION IN WATER PIPELINES SYSTEM
Last modified: 2015-01-29 19:02:08