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Demand response programs: Comparing price signals and direct load control

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  • Miri, Mohammad
  • McPherson, Madeleine

Abstract

Canada's electric power system is responsible for approximately 9 % of national emissions, 53 % of which occur in the province of Alberta. Integrating new variable renewable energy resources is a key part of the supply-side decarbonization pathway, while end-use electrification unlocks further opportunities on the demand side. The inherent variability of variable renewable energy output necessitates network flexibility. Supply-side flexibility solutions require significant investment, but demand-side management programs have potential to deliver network flexibility at a lower cost. An integrated framework consisting of demand and supply models investigates the efficacy of demand response programs for improving network flexibility in Alberta's power system, as measured by multiple operational metrics. The framework is applied to two demand response programs: real-time pricing and direct load control. These programs are assessed for two generation capacity mixes derived from an expansion planning model. Results indicate that substantial network flexibility benefits are achievable in a zero-emission power system via both programs resulting in avoided wind curtailment by 7.7 %. Improvement in operational costs, up to 1.4 % of the base output, is also observed in all scenarios accompanied by savings in household power bill expenditure by up to 15 %. These improvements, however, are only achieved fully when sufficient flexible load is provided.

Suggested Citation

  • Miri, Mohammad & McPherson, Madeleine, 2024. "Demand response programs: Comparing price signals and direct load control," Energy, Elsevier, vol. 288(C).
  • Handle: RePEc:eee:energy:v:288:y:2024:i:c:s0360544223030670
    DOI: 10.1016/j.energy.2023.129673
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    References listed on IDEAS

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    1. Madeleine McPherson & Theofilos Sotiropoulos-Michalakakos & LD Danny Harvey & Bryan Karney, 2017. "An Open-Access Web-Based Tool to Access Global, Hourly Wind and Solar PV Generation Time-Series Derived from the MERRA Reanalysis Dataset," Energies, MDPI, vol. 10(7), pages 1-14, July.
    2. Max Albert & Hartmut Kliemt, 2022. "Albert@100 ‒ Special Issue in Honor of Hans Albert," Homo Oeconomicus: Journal of Behavioral and Institutional Economics, Springer, vol. 39(1), pages 1-2, October.
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    Cited by:

    1. Morovat, Navid & Athienitis, Andreas K. & Candanedo, José Agustín & Nouanegue, Hervé Frank, 2024. "Heuristic model predictive control implementation to activate energy flexibility in a fully electric school building," Energy, Elsevier, vol. 296(C).
    2. Chen, Mengxiao & Cao, Xiaoyu & Zhang, Zitong & Yang, Lun & Ma, Donglai & Li, Miaomiao, 2024. "Risk-averse stochastic scheduling of hydrogen-based flexible loads under 100% renewable energy scenario," Applied Energy, Elsevier, vol. 370(C).

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