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A two-stage data-driven multi-energy management considering demand response

Published: 12 September 2020 Publication History

Abstract

This paper proposes an innovative two-stage data-driven optimization framework for a multi-energy system. Enormous energy conversion technologies are incorporated in the system to enhance the overall energy utilization efficiency, i.e., combined heat and power, power-to-gas, gas furnace, and ground source heat pump. Furthermore, a demand response program is adopted for stimulating the load shift of customers. Accordingly, both the economic performance and system reliability can be improved. The endogenous solar generation brings about high uncertainty and variability, which affects the decision making of the system operator. Therefore, a two-stage data-driven distributionally robust optimization (TSDRO) method is utilized to capture the uncertainty. A tractable semidefinite programming reformulation is obtained based on the duality theory. Case studies are implemented to demonstrate the effectiveness of applying the TSDRO on energy management.

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Cited By

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  • (2023)Operation and Planning of Energy Hubs Under Uncertainty—A Review of Mathematical Optimization ApproachesIEEE Access10.1109/ACCESS.2023.323764911(7208-7228)Online publication date: 2023
  • (2022)Integrated Energy System: A Low‐Carbon Future EnablerThe 4Ds of Energy Transition10.1002/9783527831425.ch9(207-238)Online publication date: 15-Jul-2022

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cover image ACM Conferences
UbiComp/ISWC '20 Adjunct: Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers
September 2020
732 pages
ISBN:9781450380768
DOI:10.1145/3410530
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 12 September 2020

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Author Tags

  1. demand response
  2. energy hub systems
  3. multi-energy systems

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View all
  • (2023)Operation and Planning of Energy Hubs Under Uncertainty—A Review of Mathematical Optimization ApproachesIEEE Access10.1109/ACCESS.2023.323764911(7208-7228)Online publication date: 2023
  • (2022)Integrated Energy System: A Low‐Carbon Future EnablerThe 4Ds of Energy Transition10.1002/9783527831425.ch9(207-238)Online publication date: 15-Jul-2022

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