WSEAS Transactions on Power Systems
Print ISSN: 1790-5060, E-ISSN: 2224-350X
Volume 15, 2020
Demand Response Management Algorithm for Distributed Multi-Utility Environment in Smart Grid
Authors: ,
Abstract: Effective usage of Information and Communication Technologies (ICT) has started with a paradigm shift in the energy management and functioning of the conventional power grid. It also aids in the maintenance of the complete information about consumer usage pattern, power storage, supply and regulation. Blending of information and communication technologies with energy management creates a smart grid environment which makes it move to the next horizon. The smart grid environment, uplifts renewable energy sources and brings out novel strategies in the energy market. The new functioning of the energy market attracts more utility companies for decentralized power generation and optimizes the power price for the consumer. The consumer plays an active role in the demand response modelling to maximize the welfare of the utility and to obtain the optimized price for their demand. In this paper, a novel demand response management scheme is proposed for multi-utility environment. The utility companies function in a peer to peer manner to communicate effectively and to select a specific utility from a set of utilities for the power supply. The selection of single utility is based on a non-cooperative game theory algorithm where the demand and generated power should be balanced to maximize the welfare of the utility and the residential consumers. The power price can be updated in an equal interval to allow all the utilities to participate in the Distributed Multi-Utility Demand Response Management (DMDRM) system. The simulated results justify that the distributed non-cooperative game theory algorithm certainly maximizes the welfare of the utility companies and residential consumers.
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Keywords: demand response, smart grid, multi-utility, game theory, distributed environment, energy market
Pages: 230-239
DOI: 10.37394/232016.2020.15.27