Heating and cooling networks: A comprehensive review of modelling approaches to map future directions. (15th December 2022)

• Record Type: Journal Article
• Authors: Brown, Alastair; Foley, Aoife; Laverty, David; McLoone, Seán; Keatley, Patrick
• Is Part Of: Energy. Volume 261:Part B(2022)
• Publication Date: 2022-12-15
• Subjects: Energy system modelling -- Heating and cooling networks -- Interdisciplinary model -- Modelling tools -- Smart energy system; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2022.125060
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: Future energy systems rely on integrating renewable energy resources to decarbonise the heating and cooling sectors and contribute to global net zero targets. Traditional approaches to energy modelling are segregated as focus tends to be on individual objectives such as minimising operational cost. Furthermore, they are limited with respect to computational time, level of precision and scalability. Model complexity is greater for district heating and cooling systems when compared to power systems due to the thermal behaviour and fluid dynamic principles which are present. Prevailing research tends to deliver a detailed analysis of specific elements within the network, but an approach for visualising the whole system is still missing. This study aims to evaluate the current tools and techniques used to model heating and cooling networks and then propose a more up to date hybrid approach that utilises recent technical advancements. A detailed literature review outlines existing modelling methods and assesses the capabilities of available software tools. The results are summarised in a Pugh Matrix using relevant criteria to compare and select the most appropriate methods. The review concludes that energy models must evolve to become interdisciplinary and multi-objective to simulate a smart energy system. Highlights: Modelling approaches to the individual components in a heat network are outlined. Techniques for optimising control, design and planning are discussed. Software tools for heat network simulation are evaluated and scored in a Pugh Matrix. A multi-step approach is suggested for modelling existing networks and assessing new network proposals.