A Hybrid Genetic Algorithm for the Interaction of Electricity Retailers with Demand Response

In this paper a bilevel programming model is proposed for modeling the interaction between electricity retailers and consumers endowed with energy management systems capable of providing demand response to variable prices. The model intends to determine the optimal pricing scheme to be established b...

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Bibliographic Details
Published inApplications of Evolutionary Computation pp. 459 - 474
Main Authors Alves, Maria João, Antunes, Carlos Henggeler, Carrasqueira, Pedro
Format Book Chapter
LanguageEnglish
Published Cham Springer International Publishing 2016
SeriesLecture Notes in Computer Science
Subjects
Bilevel problem
Demand response
Electricity retail market
Genetic algorithm
Mixed-integer linear programming
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ISBN3319312030
9783319312033
ISSN0302-9743
1611-3349
DOI10.1007/978-3-319-31204-0_30

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Summary:In this paper a bilevel programming model is proposed for modeling the interaction between electricity retailers and consumers endowed with energy management systems capable of providing demand response to variable prices. The model intends to determine the optimal pricing scheme to be established by the retailer (upper level decision maker) and the optimal load schedule adopted by the consumer (lower level decision maker) under this price setting. The lower level optimization problem is formulated as a mixed-integer linear programming (MILP) problem. A hybrid approach consisting of a genetic algorithm and an exact MILP solver is proposed. The individuals of the population represent the retailer’s choices (electricity prices). For each price setting, the exact optimal solution to the consumer’s problem is obtained in a very efficient way using the MILP solver. An illustrative case is analyzed and discussed.
ISBN:3319312030
9783319312033
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-319-31204-0_30