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A genetic algorithm approach to the smart grid tariff design problem

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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.

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Authors and Affiliations

  1. School of Business, University College Dublin, Dublin, Ireland

    Will Rogers, Paula Carroll & James McDermott

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  1. Will Rogers
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  2. Paula Carroll
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  3. James McDermott
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Corresponding author

Correspondence to Paula Carroll.

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Conflict of interest

Will Rogers worked for Bord Gáis (an Irish electricity supply company) and declares that he has no conflict of interest. Paula Carroll and James McDermott declare that they have no conflict of interest.

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Communicated by V. Loia.

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Rogers, W., Carroll, P. & McDermott, J. A genetic algorithm approach to the smart grid tariff design problem. Soft Comput 23, 1393–1405 (2019). https://doi.org/10.1007/s00500-017-2971-2

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