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Wang, Kunpeng (2022) A modular co-simulation approach for urban energy systems. PhD thesis, University of Nottingham.

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Abstract

Cities are the main site of energy consumption, which result in approximately 71% of global CO2 emissions. Therefore, energy planning in cities can play a critical role in climate change mitigation by improving the efficiency of urban energy usage. The energy characteristics of cities are complex as they involve interactions of multiple domains, such as energy resources, distribution networks, storage and demands from various consumers. Such complexity makes urban energy planning a challenging task, which requires an accurate simulation of the interactions and flows between different urban energy subsystems. Co-simulation has been adopted by a number of researchers to simulate dynamic interactions between subsystems. However, the research has been domain specific and could only be used in limited areas. There was no generic approach to tackle the interoperability challenge of a comprehensive simulation for urban energy systems.

To address such a gap, the aim of this thesis is to develop a generic and scalable urban energy co-simulation approach to comprehensively model the dynamic, complex and interactive nature of urban energy systems. This was achieved through the development of a generic and scalable urban energy co-simulation architecture and approach for the integration and orchestration of urban energy simulation tools, also called simulators, from different domains.

Nine requirements were identified through a literature review of co-simulation, its approaches, standards, middleware and simulation tools. A conceptual co-simulation architecture was proposed that can address the requirements. The architecture has a modular design with four layers. The simulator layer wraps the simulation tools; the interconnection layer enables the communication between tools programmed in different programming languages; the interoperability layer provides a mechanism for the tool composition and orchestration; and the control layer controls the overall simulation sequence and how data is exchanged.

Based on the architecture, a Co-simulation Platform for Ecological-urban (COPE) was developed. Suitable co-simulation software libraries were adopted and mapped together to fulfil the requirements of each layer of COPE to achieve the research objectives. For different simulation purposes, subsystem simulation tools from different domains could be selected and integrated into the platform. A master algorithm could then be developed to orchestrate and synchronise the tools by controlling how the tools are run and how data are exchanged among the tools.

In order to evaluate COPE’s fundamental functionality and demonstrate its application, two case studies are presented in the thesis: simulating multiple application domains for a single building and multiple (interacting) buildings respectively. From the case studies, it was observed that COPE can successfully synchronise and manage interactions between the co-simulation platform and integrated simulation tools. The simulation results are validated by comparing the results obtained from the direct coupling approach. The applicability of COPE is demonstrated by simulating energy flows in urban energy systems in a neighbourhood context. Computing performance diagnostics also showed that this functionality is achieved with modest overhead.

The layered modular co-simulation approach and COPE presented in this thesis provide a generic and scalable approach to simulating urban energy systems. It could be used for decision making to improve urban energy efficiency.

Item Type:	Thesis (University of Nottingham only) (PhD)
Supervisors:	Siebers, Peer-Olaf Mao, Yong Robinson, Darren
Keywords:	Urban Energy Systems; Co-Simulation; Modular software architecture; Functional Mock-up Interface; Functional Mock-up Unit
Subjects:	H Social sciences > HT Communities. Classes. Races T Technology > TJ Mechanical engineering and machinery
Faculties/Schools:	UK Campuses > Faculty of Engineering
Item ID:	71775
Depositing User:	Wang, Kunpeng
Date Deposited:	28 Feb 2023 11:43
Last Modified:	28 Feb 2023 11:43
URI:	https://eprints.nottingham.ac.uk/id/eprint/71775

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