An optimization framework for the network design of advanced district thermal energy systems. (15th August 2022)

• Record Type: Journal Article
• Authors: Allen, Amy; Henze, Gregor; Baker, Kyri; Pavlak, Gregory; Murphy, Michael
• Is Part Of: Energy conversion and management. Volume 266(2022)
• Publication Date: 2022-08-15
• Subjects: District thermal energy systems -- Ambient loops -- Topology optimization -- Particle swarm optimization; 0000 -- 1111; Direct energy conversion -- Periodicals; Energy storage -- Periodicals; Energy transfer -- Periodicals; Énergie -- Conversion directe -- Périodiques; Direct energy conversion; Periodicals; 621.3105
• DOI: 10.1016/j.enconman.2022.115839
• Languages: English
• ISSNs: 0196-8904

Abstract

Highlights: District energy systems operating at near-ambient temperatures face design challenges. Framework identifies optimal networks for advanced district thermal energy systems. Solutions identified offer significant cost savings relative to common approaches. Abstract: In this work, a topology optimization framework for district thermal energy systems is presented. The framework seeks to address the questions, for a given district, "What is the best subset of buildings to connect to a district thermal energy system, and by what network should they be connected, to minimize life cycle cost?" A particle swarm optimization approach is validated to address the selection of the subset of buildings, and a graph theory-based heuristic is validated for selection of the network topology for any candidate subset of buildings. The framework is applied to a prototypical urban district for illustrative purposes. Modeling of prototypical districts revealed reductions in source energy use intensity for heating and cooling of 21–25% through the use of advanced district energy systems relative to code-compliant, building level systems. The framework identifies solutions with life cycle cost values 14% to 72% lower than that of base case scenarios based on conventional design approaches, depending on the base case scenario selected. Analysis of the search space indicates that topology optimization facilitates reductions in life cycle cost, source energy use intensity, and carbon emissions.