Optimal Energy Scheduling and Sensitivity Analysis for Integrated Power–Water–Heat Systems

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

6 Scopus Citations
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Author(s)

Detail(s)

Original languageEnglish
Pages (from-to)5176-5187
Journal / PublicationIEEE Systems Journal
Volume16
Issue number4
Online published2 Dec 2021
Publication statusPublished - Dec 2022
Externally publishedYes

Abstract

The conventionally independent power, water, and heating networks are becoming more tightly connected, which motivates their joint optimal energy scheduling to improve the overall efficiency of an integrated energy system. However, such a joint optimization is known as a challenging problem with complex network constraints and couplings of electric, hydraulic, and thermal models that are nonlinear and nonconvex. We formulate an optimal power–water–heat flow (OPWHF) problem and develop a computationally efficient heuristic to solve it. The proposed heuristic decomposes OPWHF into subproblems, which are iteratively solved via convex relaxation and convex–concave procedure. Simulation results validate that the proposed framework can improve operational flexibility and social welfare of the integrated system, wherein the water and heating networks respond as virtual energy storage to time-varying energy prices and solar photovoltaic generation. Moreover, we perform sensitivity analysis to compare two modes of heating network control: by flow rate and by temperature. Our results reveal that the latter is more effective for heating networks with a wider space of pipeline parameters.

Research Area(s)

  • Cogeneration, Decomposed optimization, district heating, Hydraulic systems, Junctions, municipal water, Peer-to-peer computing, power distribution, Reservoirs, Resistance heating, sensitivity analysis, Water heating

Bibliographic Note

Publisher Copyright: IEEE

Citation Format(s)

Optimal Energy Scheduling and Sensitivity Analysis for Integrated Power–Water–Heat Systems. / Fang, Sidun; Wang, Chenxu; Lin, Yashen et al.
In: IEEE Systems Journal, Vol. 16, No. 4, 12.2022, p. 5176-5187.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review