Dynamic energy flow analysis of the heat-electricity integrated energy systems with a novel decomposition-iteration algorithm

Yao, Shuai, Gu, Wei, Wu, Jianzhong ORCID: https://orcid.org/0000-0001-7928-3602, Lu, Hai, Zhang, Suhan, Zhou, Yue and Lu, Shuai 2022. Dynamic energy flow analysis of the heat-electricity integrated energy systems with a novel decomposition-iteration algorithm. Applied Energy 322 , 119492. 10.1016/j.apenergy.2022.119492

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Abstract

Simulation and operation optimization studies on the integrated energy system have received extensive attention recently for its potential in improving energy efficiency and increasing grid integration of renewable energy, where the task of energy flow calculation serves as a fundamental tool to determine the network states. This paper investigates the models and methods for dynamic energy flow analysis of two strongly coupled networks in the integrated energy systems — the power grid and the heating network. First, the complicated coupling mechanisms of power grid and heating network are thoroughly analyzed and classified into four representative coupling modes. On this basis, the detailed dynamic energy flow analysis method for each coupling mode is developed. Second, a refined difference scheme is applied to discretize the partial differential equations describing the long-lasting temperature dynamics in the heating network. The high-dimensional dicretized model is then solved by a novel decomposition-iteration algorithm. Compared with existing methods, this algorithm avoids deriving the gigantic coefficient matrix of network equations and can improve the accuracy of energy flow results. Finally, considering the systematical error caused by neglecting the inertial and adjusting constraints of heat sources, a revision stage is firstly introduced to correct the heat power output of the slack source and help obtain more accurate energy flow results. Case study shows that the proposed methods take 3.21 s to obtain the dynamic energy flows of a coupled system consisting of a 118-node power grid and eight 35-node district heating networks over a 300-minutes simulation course, which is qualified to provide support for simulation and optimization related applications in practice.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Engineering
Publisher:	Elsevier
ISSN:	0306-2619
Date of First Compliant Deposit:	19 July 2022
Date of Acceptance:	15 June 2022
Last Modified:	17 Nov 2024 03:15
URI:	https://orca.cardiff.ac.uk/id/eprint/151224

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