Smart Meter Tariff Design to Minimise Wholesale Risk

doi:10.1016/j.endm.2016.03.004

Electronic Notes in Discrete Mathematics

Volume 52, June 2016, Pages 21-28

https://doi.org/10.1016/j.endm.2016.03.004 Get rights and content

Abstract

Smart metering in electricity markets offers an opportunity to explore more diverse tariff structures. In this article a Genetic Algorithm (GA) is used to design Time of Use tariffs that minimise the wholesale risk to the supplier in residential markets. Residential demand and the System Marginal Price of Ireland's Single Electricity Market are simulated to estimate the wholesale risk associated with each tariff.

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Cited by (1)

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Advanced metering technologies coupled with informatics creates an opportunity to form digital multi-utility service providers. These providers will be able to concurrently collect a customers’ medium-high resolution water, electricity and gas demand data and provide user-friendly platforms to feed this information back to customers and supply/distribution utility organisations. Providers that can install low-cost integrative systems will reap the benefits of derived operational synergies and access to mass markets not bounded by historical city, state or country limits. This paper provides a vision of the required transformative process and features of an integrated multi-utility service provider covering the system architecture, opportunities and benefits, impediments and strategies, and business opportunities. The heart of the paper is focused on demonstrating data modelling processes and informatics opportunities for contemporaneously collected demand data, through illustrative examples and four informative water-energy nexus case studies. Finally, the paper provides an overview of the transformative R&D priorities to realise the vision.

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Smart Meter Tariff Design to Minimise Wholesale Risk

Abstract

Energy

Mixed integer programming model for pricing in telecommunication

Risk-adequate pricing of retail power contracts

The Journal of Energy Markets