Open AccessIncentive-based demand response in grid-connected microgrid using quasi-opposed grey wolf optimizer
Author(s) -
Salil Madhav Dubey,
Hari Mohan Dubey,
Manjaree Pandit
Publication year - 2021
Publication title -
international journal of engineering, science and technology andb. lagos
Language(s) - English
Resource type - Journals
ISSN - 2141-2839
DOI - 10.4314/ijest.v13i2.1
Subject(s) - microgrid , demand response , computer science , grid , mathematical optimization , renewable energy , smart grid , operator (biology) , electricity , engineering , electrical engineering , mathematics , biochemistry , chemistry , geometry , repressor , transcription factor , gene
The paradigm shifts in the electrical industry from demand-driven generation to supply-driven generation due to the incorporation of renewable generating sources is a growing research field. Implementing demand response in present-day distribution schemes is anattractive approach often adopted by microgrid (MiG) operator.This paper incorporates an incentivebased demand response (IBDR) method in a grid-connected microgrid (MiG) comprising of conventional generators (CGs), wind turbines (WTs), and solar PV units. The main aim is to collectively minimize the fossil fuel cost of CGs, lower the transaction cost of portable power from the grid, and maximize theMiG operator's profitafter implementing demand response. This multi-objective problem combining optimal economic load dispatch of MiG with an efficient demand-side response is solved using a proposed Quasi-opposed Grey Wolf Optimizer (QOGWO) algorithm. The effect of the proposed algorithm on demand-side management (DSM) is analyzed for two cases, (i) varying the value of power interruptibility (ii) varying the maximum limit of curtained power. Performance of QOGWO is compared with original GWO and a variant of GWO, Intelligent Grey Wolf Optimizer (IGWO). Results show the superior global search capability and complex constrained handling capability of QOGWO.