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Navid Rezaei

Navid Rezaei

Academic rank: Associate Professor
ORCID:
Education: PhD.
ScopusId: 9870
HIndex:
Faculty: Faculty of Engineering
Address: Basdaran Bolvar, Kuridstan University, Faculty of Engineering, Electrical Engineering Department, Room 206
Phone: 087-33660073

Research

Title
A game theory based demand-side management in a smart microgrid considering price-responsive loads via a twofold sustainable energy justice portfolio
Type
JournalPaper
Keywords
Demand-side integration Mixed integer nonlinear programming, Nash Bargaining Game, Pre-paid Energy Consumption, Smart microgrid,
Year
2022
Journal Sustainable Energy Technologies and Assessments
DOI
Researchers Navid Rezaei ، Abbas Fattahi Meyabadi ، Mohammadhossein Deihimi

Abstract

This paper introduces a demand-side integration (DSI) framework that upholds the efficacious electrical energy consumption to attain the aims of smart grid as well as the customers’ requirement. The proposed DSI framework is based on a pre-paid orderly energy consumption strategy for a smart microgrid. The interaction between aggregators and end-use customers is captured as a Nash Bargaining Game. A dynamic electricity pricing scheme is implemented to derive the profitable daily electricity tariffs considering an elasticity-based model of price- responsive load. The resources caused by proper response of small-scale consumers are integrated into day- ahead energy scheduling problem. In order to cope the real-time deviations, the DSI program is accompanied by a supplementary pay-off module. The DSI framework is formulated as a stochastic optimization problem in the form of mixed integer nonlinear programming involving probabilistic representation of uncertainty in generation pattern of renewable energy resources. According to the simulation results, in contrast with the normal con- sumption paradigm, the load factor improves at least 1.36%, the net profit of unified entity enhances 0.27%, and the total gas emissions are mitigated about 10.9%. The outcomes demonstrate the accuracy and merit of the proposed method.