A genetic algorithm approach to the smart grid tariff design problem

Will Rogers; Paula Carroll; James McDermott

doi:10.1007/s00500-017-2971-2

A genetic algorithm approach to the smart grid tariff design problem

Will Rogers
, Paula Carroll
, James McDermott

University College Dublin

Research output: Contribution to a Journal (Peer & Non Peer) › Article › peer-review

4 Citations (Scopus)

Abstract

Smart metering in electricity markets offers an opportunity to explore more diverse tariff structures. In this article residential electricity demand and the System Marginal Price of Ireland’s Single Electricity Market are simulated to estimate the wholesale risk associated with possible tariffs. A genetic algorithm (GA) with a stochastic fitness function is proposed to search for time-of-use tariffs that minimise wholesale risk to the supplier in residential markets. Alternative search algorithms and fitness functions are investigated in detail, as well as trade-offs in GA and simulation parameter settings.

Original language	English
Pages (from-to)	1393-1405
Number of pages	13
Journal	Soft Computing
Volume	23
Issue number	4
DOIs	https://doi.org/10.1007/s00500-017-2971-2
Publication status	Published - 27 Feb 2019
Externally published	Yes

Keywords

Genetic algorithm
Smart grid tariff design
Stochastic fitness function

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10.1007/s00500-017-2971-2

Cite this

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KW - Smart grid tariff design

KW - Stochastic fitness function

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A genetic algorithm approach to the smart grid tariff design problem

Abstract

Keywords

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