Author : Nutan Y. Attarde 1
Date of Publication :7th November 2015
Abstract: The most important features of the smart grid is the meter data management system (MDMS)which collects, exchanges, and processes the meter data with an objective of minimizing the power consumption and supply. Currently, the electricity consumption is not efficient .This results in the waste of a large amount of natural resources. This leads to arising different needs such as plug-in hybrid electric vehicles (PHEVs), which can potentially double the average load, It has increased the need of developing new methods for demand side management (DSM).We consider a smart power infrastructure, where several subscribers share a common energy source. Each subscriber is equipped with an energy consumption controller (ECC) unit as part of its smart meter. Each smart meter is connected to not only the power grid but also a communication infrastructure such as a local area network. This allows two-way communication among smart meters .Considering the importance of energy pricing as an essential tool to develop efficient demand side management strategies. We propose a novel real-time pricing algorithm for the future smart grid. We focus on the interactions between the smart meters and the energy provider through the exchange of control messages which contain subscribers’ energy consumption and the real-time price information. We analytically model the subscribers’ preferences and their energy consumption patterns in form of carefully selected utility functions based on concepts from microeconomics. Then we propose a distributed algorithm which automatically manages the interactions among the ECC units at the smart meters and the energy provider. The algorithm finds the optimal energy consumption levels for each subscriber to maximize the aggregate utility of all subscribers in the system in a fair and efficient fashion. After that we will show that the energy provider can encourage some desirable consumption patterns among the subscribers by means of the proposed real-time pricing interactions.
Reference :
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