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Time shift: The peak reduction potential of demand response with simple time-of-use pricing

Time shift: The peak reduction potential of demand response with simple time-of-use pricing

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Authors

Baxter Kamana-Williams , R. J. Hooper, Daniel Gnoth, J. Geoffrey Chase

Abstract

Increasing electrification of energy systems, required for greenhouse gas emissions reductions, poses challenges for electricity systems from increased peak demand. Demand response can reduce peak demand, but acceptability is limited by consumer concerns about effort, complexity, and lack of control. This study assesses the potential of simple demand response programs using existing electricity pricing structures for a median-income residential low-voltage distribution network in Auckland, Aotearoa New Zealand, and draws generalised conclusions applicable across a broad range of circumstances. Using an agent-based model validated against real transformer data, the electricity demand in 50 households is simulated under time-of-use electricity pricing structures, with participation varied between 0% and 100%. Time-of-use schedules without modified demand reduces household electricity costs by 14%, with further reductions of up to 35% through DR participation. Demand response can reduce peak electricity demand by up to 5.7%, but high levels of hot water cylinder (or “water heater”) delayed heating can increase peak demand by up to 32.9%. These findings highlight the need for careful DR program design to avoid unintended peak demand increases and ensure equitable access to DR benefits. Regulators could consider facilitating the adoption of DR-capable technologies to enhance program effectiveness and support the energy transition.

DOI

https://doi.org/10.31223/X57433

Subjects

Engineering, Oil, Gas, and Energy, Sustainability

Keywords

Demand side management, Residential energy use, Agent-based model, Peak electricity demand

Dates

Published: 2025-05-16 01:38

Last Updated: 2025-05-16 01:38

License

CC BY Attribution 4.0 International

Additional Metadata

Data Availability (Reason not available):
Primary data supporting the conclusions of this article are presented in the paper. Additional data, such as code scripts, will be available from the corresponding author on request.