Lumped Parameter Building Model Calibration using Particle Swarm Optimization

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Title: Lumped Parameter Building Model Calibration using Particle Swarm Optimization
Authors: Andrade-Cabrera, Carlos
Turner, William J. N.
Burke, Daniel J.
Neu, Olivier
Finn, Donal
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Date: 29-Nov-2016
Abstract: This paper presents a methodology for the automated calibration of deterministic lumped parameter models in building energy simulation using optimization methods. A heterogeneous model topology is proposed to represent a residential building archetype developed in the EnergyPlus simulation environment. The archetype model has previously been used to characterize the domestic building stock in Ireland. The automated calibration problem is solved as a least squares error problem solved using a local optimization method (Sequential Quadratic Programming) and two heuristics methods (Particle Swarm Optimization and Genetic Algorithm). It is shown that Particle Swarm Optimization provides the best performance for this particular problem and provides an inherent robustness under model uncertainty.
Funding Details: European Commission Horizon 2020
Type of material: Conference Publication
Keywords: Lumped parameter building modelParticle swarm optimizationModel calibration
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Language: en
Status of Item: Peer reviewed
Conference Details: 3rd Asia conference of International Building Performance Simulation Association (ASim2016), Jeju island, Korea, 27-29 November 2016 2017-01-20T13:43:45Z
Appears in Collections:Mechanical & Materials Engineering Research Collection
ERC Research Collection
Energy Institute Research Collection

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