Optimizing Demand Response in Distribution Network with Grid Operational Constraints

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

1 Scopus Citations
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Author(s)

  • Tianyu Zhao
  • Yanfang Mo
  • Jason Min Wang
  • Jun Luo
  • Xiang Pan

Related Research Unit(s)

Detail(s)

Original languageEnglish
Title of host publicatione-Energy '23 - Proceedings of the 2023 The 14th ACM International Conference on Future Energy Systems
Place of PublicationNew York, NY
PublisherAssociation for Computing Machinery, Inc
Pages299-313
ISBN (print)9798400700323
Publication statusPublished - 2023

Publication series

Namee-Energy - Proceedings of the ACM International Conference on Future Energy Systems

Conference

Title14th ACM International Conference on Future Energy Systems (ACM e-Energy 2023)
PlaceUnited States
CityOrlando
Period20 - 23 June 2023

Abstract

Despite the extensive studies on end-user participation in distribution networks, incorporating grid operational constraints and the incentive/dynamic pricing in demand response (DR) is still a challenging and open problem. To fill this gap, we propose a novel three-stage game framework to enable the DR among the utility company, distribution system operator (DSO), and prosumers. In Stage I, utility determines the incentive price to DSO for social welfare maximization. In Stage II, DSO decides the dynamic prices to prosumers and respects grid operational constraints. In Stage III, each prosumer adjusts the local generation and demand on its behalf. We show that the DR game admits an equilibrium that maximizes social welfare and DSO/prosumers' benefits while satisfying operational constraints. We prove the uniqueness of the optimal power supply of utility and the demand-generation adjustments and derive the explicit form of optimal incentive/dynamic price-setting at equilibrium. We further develop a robustness-enhanced design against DSO/prosumers' fault information and explore the impact of renewable/uncontrollable load uncertainty. Meanwhile, we develop an efficient distributed algorithm to help DR participants cooperatively reach equilibrium. Simulations show that the proposed scheme improves social welfare by 20.1% and DSO/prosumers' benefit by 32.5% on IEEE 30/118-bus systems while respecting all grid operational constraints. © 2023 ACM.

Research Area(s)

  • Demand response, Multi-stage optimization and game, Pricing design, System operational constraints

Citation Format(s)

Optimizing Demand Response in Distribution Network with Grid Operational Constraints. / Zhao, Tianyu; Zhou, Min; Mo, Yanfang et al.
e-Energy '23 - Proceedings of the 2023 The 14th ACM International Conference on Future Energy Systems. New York, NY: Association for Computing Machinery, Inc, 2023. p. 299-313 (e-Energy - Proceedings of the ACM International Conference on Future Energy Systems).

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review