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  • Publication DateJan 2016
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Development of calibrated operational models of existing buildings for real-time

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Development of calibrated operational models of existing buildings for real-time

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Development of calibrated operational models of existing buildings for real-time decision support and performance optimisation

Session 3 Paper 1, Heriot-Watt University Edinburgh, 14-15 April 2016

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Building simulation tools are commonly used in design for performance appraisal and optimisation. However, numerous studies have found that actual building performance often deviates significantly from simulation predictions. This paper proposes a detailed framework to produce calibrated operational models, which can support operational decision-making, and real-time control optimisation. The approach centres around a three-tier calibration process: Tier 1 focuses on Buildinglevel (Demand-side) variables (e.g. occupancy, equipment, infiltration). Tier 2 focuses on system-level (HVAC) model components (e.g. heating / cooling coil capacities). In this phase, we use detailed building data combined with genetic optimisation techniques to calibrate relevant input parameters. In the case where system performance modelling is not necessary, we use free-form profiles (i.e. measured building data) to supplement these model components. Once system-level noise has been eliminated, in Tier 3 we calibrate the remaining plant-level parameters (e.g. central plant, electricity consumption, etc.). The approach is supported by two novel developments: (1) Free-form profiles: These are actual historic trends from existing building controllers, which are used to supplement model components where appropriate; (2) Genetic Optimisation algorithms are utilised to efficiently navigate the solution space to reduce discrepancies between the model and actual system performance. The proposed calibration approach builds upon prior research efforts to standardise the calibration process using evidence-based model development, combined with sensitivity and uncertainty analysis.