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.
|Permanent link:||http://hdl.handle.net/10197/8292||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 model; Particle swarm optimization; Model calibration||Other versions:||http://www.ibpsa.kr/asim2016/main.html||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||metadata.dc.date.available:||2017-01-20T13:43:45Z|
|Appears in Collections:||Mechanical & Materials Engineering Research Collection|
ERC Research Collection
Energy Institute Research Collection
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