Title : ( Demand Response Mechanism of a Hybrid Energy Trading Market for Residential Consumers with Distributed Generators )
Authors: Babak Rezaee Khabooshan ,Access to full-text not allowed by authors
Abstract
Smart grid (SG) as a complex advanced electricity system is capable of facing with the growing energy demand, where energy consumers are connected not only to the conventional grid but also to some local energy markets for bidirectional energy trading. In this context, this paper presents an optimization problem the demand response problem where a hybrid energy trading system consisting of a conventional grid, a local trading system, a number of energy consumers, having distributed generators and battery, and some generator companies. In this case, it has been considered that the local trading center (LTC) is a non-profit oriented LTC which aims at benefiting the energy consumers and energy sellers. The optimization model is formulated as a mixed integer Linear Program (MILP) with a bounded number of variables and constraints. Furthermore, the solution can be obtained in polynomial time and provides the optimal scheduling for the problem such that the costs were minimized while the total demand is satisfied.
Keywords
Hybrid energy trading market Demand response mechanism Local trading center Distributed generators Battery bank@inproceedings{paperid:1063772,
author = {Rezaee Khabooshan, Babak},
title = {Demand Response Mechanism of a Hybrid Energy Trading Market for Residential Consumers with Distributed Generators},
booktitle = {International Conference on Management Science and Engineering Management},
year = {2017},
location = {Kanazawa},
keywords = {Hybrid energy trading market Demand response mechanism Local trading center Distributed generators Battery bank},
}
%0 Conference Proceedings
%T Demand Response Mechanism of a Hybrid Energy Trading Market for Residential Consumers with Distributed Generators
%A Rezaee Khabooshan, Babak
%J International Conference on Management Science and Engineering Management
%D 2017