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This is the final published version of a conference proceedings (inc. abstract) that has been published in its final definitive form by Association for Computing Machinery, 2020.
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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.
Author(s): Zhao P, Gu C, Cao Z, Xiang Y, Yan X, Huo D
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: Ubicomp 2020 Workshop
Year of Conference: 2020
Pages: 588-595
Online publication date: 12/09/2020
Acceptance date: 13/07/2020
Date deposited: 21/10/2020
Publisher: Association for Computing Machinery
URL: https://doi.org/10.1145/3410530.3414587
DOI: 10.1145/3410530.3414587
Library holdings: Search Newcastle University Library for this item
ISBN: 9781450380768