Multi-Objective Optimisation for Tuning Building Heating and Cooling Loads Forecasting Models

Saleh Seyedzadeh, Farzad Rahimian, Parag Rastogi, Stephen Oliver, Ivan Glesk, Bimal Kumar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abstract

Machine learning (ML) has been recognised as a powerful method for modelling building energy consumption. The capability of ML to provide a fast and accurate prediction of energy loads makes it an ideal tool for decision-making tasks related to sustainable design and retrofit planning. However, the accuracy of these ML models is much dependant on the selection of the right hyper-parameters for specific building dataset. This paper proposes a method for optimising ML model for forecasting both heating and cooling loads. The technique employs multi-objective optimisation with evolutionary algorithms to search the space of possible parameters. The proposed approach not only tune one model to precisely predict building energy loads but also accelerates the process of model optimisation. The study utilises a simulated building energy data generated in EnergyPlus to demonstrate the efficiency of the proposed method, and compares the outcomes with the regular ML tuning procedure (i.e. grid search). The optimised model provides a reliable tool for building designers and engineers to explore a large space of the available building materials and technologies.
Original languageEnglish
Title of host publicationConstruction and Management in Architecture, Engineering, Construction and Operations (AECO)
Subtitle of host publication36th CIB W78 2019 Conference ICT in Design
PublisherUniversity of Northumbria, Newcastle-upon-Tyne.
Pages964
Number of pages974
ISBN (Electronic)9781861354860
ISBN (Print)9781861354877
Publication statusPublished - 18 Sep 2019
Event36th CIB W78 2019 Conference: ICT in Design, Construction and Management in Architecture, Engineering, Construction and Operations (AECO) - Newcastle, United Kingdom
Duration: 18 Sep 201920 Sep 2019
http://cibw78.northumbria-eee.co.uk/

Conference

Conference36th CIB W78 2019 Conference
CountryUnited Kingdom
CityNewcastle
Period18/09/1920/09/19
Internet address

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    Seyedzadeh, S., Rahimian, F., Rastogi, P., Oliver, S., Glesk, I., & Kumar, B. (2019). Multi-Objective Optimisation for Tuning Building Heating and Cooling Loads Forecasting Models. In Construction and Management in Architecture, Engineering, Construction and Operations (AECO): 36th CIB W78 2019 Conference ICT in Design (pp. 964). University of Northumbria, Newcastle-upon-Tyne..