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Table 1 Summary of machine learning techniques for prediction of building energy consumption and performance

From: Machine learning for estimation of building energy consumption and performance: a review

Target ML Prediction term Building case and data Features Ref
Energy Performance ANN Month schools in England and Wales (120,253 DEC records) Construction year, Phase of education, Number of pupils,Internal environmental conditioning, Site exposure, Orientation, North facade adjacency, South facade adjacency, East facade adjacency, West facade adjacency, Floor area, Building depth ratio, Compactness ratio, Surface exposure ratio, North glazing ratio, South glazing ratio, East glazing ratio, West glazing ratio, Glazing type, Roof shape, Roof glazing, Heating degree-days, Cooling degree-days Hong et al. (2014a)
  ANN - Educational building (previous preliminary energy assessments (PEA) reports for over 60 buildings in Hawaii) Operation hours, Age, Square feet area, Yearly electricity usage, Percentage electricity used for lighting, air conditioning, plug loads Yalcintas (2006)
  ANN Year Office buildings in Italy (8800 building stock simulated using EnergyPlus) geometry(9), envelope(30), operation (6) and HVAC (3) Ascione et al. (2017)
  ANN Year Schools in UK (120,253 DEC records) North glazing ratio, South glazing ratio, East glazing ratio, West glazing ratio, Glazing type, Roof shape, Roof glazing, Heating degree days, Cooling degree days Hong et al. (2014)
  ANN - Residential buildings (the online CENED database) Degree days, Net volume, Net floor area, Dispersant surface, Opaque to glazed ratio, Year of construction, Thermal conductivity, Average floor height, Opaque surface area, Glazed surface area, Construction period, Non-linear features Khayatian et al. (2016)
  ANN Day An generic reference office building in Hong Kong (8760 hourly records calculated using EnergyPlus) External weather conditions (daily average dry-bulb temperature, daily average wet-bulb tempera-ture, daily global solar radiation and daily average clearness index), Building envelope designs (solar aperture, daylight aperture, overhang and side-fins projections), Day type Wong et al. (2010)
  Clustering - 5215 commercial building samples (CBECS database) Area, Percent heated, Percent cooled, Wall materials, Roof materials, Window materials, Window percent, Shape, Number of floors, Construction year, Weekly operation hours, Occupants, Variable air volume, Heating unit, Cooling unit, Economizer, Refrigerators, Number of servers, Office equipment, Heating and cooling degree day Gao and Malkawi (2014)
  Clustering - 1100 school in Greece (data gathered over one) Heated surfac, Age of the building, Insulation of the building, Number of classrooms, Number of students, School’s operating hours per day, Age of the heating system, Energy consumption per unit Gaitani et al. (2010)
  Clustering - 320 schools in Greece (Energy data have been collected for a three years) Temperature, Solar radiation, Energy consumption per unit, Operational period, Number of students, Construction characteristics, Installed equipment Santamouris et al. (2007)
  Clustering - 60 schools in Italy (data collected over 5 years) Area of the floor in thermal contact with the ground, Opaque envelope area, Transparent envelope area, Windows tp vertical walls ratio, Windows to floor area ratio, Transparent to opaque envelope ratio, Envelope average thermal transmittance, Shape, Heating system Capacity Arambula Lara et al. (2015)
HVAC Loads GPR Day An office building in Chicago (Loads calculated using simulation) Weather, Occupancy count Burkhart et al. (2014)
  GPR, GMM, ANN Day Office building (three months data collected) Outside dry bulb air temperature, Day Zhang et al. (2015b)
Heating & Cooling Loads ANN Year Model house with 9 combination of wall and roof type (loads are calculated using TRNSYS simulation) Wall and Roof type, Maximum and mean daily direct and global radiation, Maximum and mean temperature of the day, Mean wind speed and direction (degrees) Kalogirou et al. (2001)
  GPR Hour Office building in Philadelphia Outdoor temperature Zhang et al. (2013)
  GPR Year Typical buildings in the US (loads calculated using EnergyPlus) Building characteristics, Climate data (28 features) Rastogi et al. (2017)
  GPR Month Retrofitted office building (Actual measurements and simulation) Building envelope characteristics, Solar shading control system Manfren et al. (2013)
Heating Loads ANN Hour Simulation models (Data collected from a District Heating Company of the city of Iasi) Solar radiation, Wind speed, Outside temperature of previous 24h, Mass flow rate of hot water of previous 24h, Hot water temperature exit from plant system Popescu et al. (2009)
  ANN Hour Schools in UK (120,253 DEC records) Glazing ratio in all cardinal directions, Roof shape and glazing, Heating and cooling degree days Hong et al. (2014)
  ANN Day Six single-family buildings, constructed in Stockholm (The measurements performed before and after retrofitting) Construction year, Stories, Framework, Floor area, Number of inhabitants, Ventilation system Olofsson and Andersson (2001)
  ANN Hour An institutional building in Nantes (The data is taken from data acquisition system for 1.5 months) Climate and heating energy data, Occupancy profile Paudel et al. (2014)
  SVM Day Single-story mass-built buildings (Simulated using EnergyPlus) Outdoor dry bulb and relative humidity, Wind speed, Direct solar, Ground temperature, Outdoor air density, Water mains temperature, Number of occupants, Total heat gain of lights, electric equipment and window, Heat loss for walls, Mean air temperature, Infiltration volume, Heating outlet temp Zhao and Magoulès (2012a)
  ANN Month Three sample buildings (Heating loads demand calculated using finite difference approach of transient state) Transparency ratio, Insulation thickness, Building form factors Ekici and Aksoy (2009)
Cooling Loads ANN Hour Parking space (data gathers over 23 weekdays) Temperature, Relative humidity Yokoyama et al. (2009)
  ANN Day Public office building in Kuwait (data for three building types) External temperature Ben-Nakhi and Mahmoud (2004)
  ANN, SVM Hour A model building in China (measurements from an existing HVAC system) Temperature, Relative humidity Hou et al. (2006); Hou and Lian (2009); Xuemei et al. (2009)
  ANN Day Three institutional buildings (The energy data is obtained through the facility management office) Five previous day Deb et al. (2016)
  GPR Hour office building in Lemont city (data obtained from baselining and post-retrofit days) Outdoor temperature Heo et al. (2012)
  GPR Day An School building in Stanford city (data obtained from baselining and post-retrofit days) Outdoor temperature Noh and Rajagopal (2013)
Energy Demand ANN Hour holiday home which is used only during weekends (forty cases generated by the program ZID) Season, Insulation, Wall thickness, Time of day, Energy calculating function Kalogirou and Bojic (2000)
  ANN Hour Two datasets (Great Building Energy Predictor Shootout I (5 months), office building located in Athens, Greece (one year)) Temperature, Solar radiation, Humidity ratio, Wind speed, Day Karatasou et al. (2006)
  ANN Year the US domestic buildings (energy consumption is taken from U.S. Energy Information Administration) Population, Gross domestic product, House size, Median household income, Cost of residential electricity, Natural gas and oil Kialashaki and Reisel (2013)
  ANN Day An office building in University of Sao Paulo Daily maximum and minimum external dry-bulb temperatures Neto and Fiorelli (2008)
  SVM Month Four office buildings in Singapore (energy consumption is obtained from utility bills over 4 years) Dry bulb temperature, Relative humidity, Global solar radiation Dong et al. (2005)
  SVM Hour Multi-family domestic building in New York City (data from the Great Energy Predictor Shootout) Temperature, Humidity, Wind speed Jain et al. (2014)
Electricity Demand ANN Hour An institutional facility in Calgary (data collected over 15 month) Outside temperature and relative humidity, Boiler outlet water temperature and flow-rate, Chiller outlet water temperature and flow-rate, Supply air temperatures for hot, cold duct, Supply and return control settings, Indoor air temperatures of 2 different zones Platon et al. (2015)
  ANN Hour A building in Athens (time series of hourly values are collected over 6 years) Air temperature, Solar radiation Mihalakakou et al. (2002)
  SVM, ANN Month, Day A residential building in Japan (data is collected over one year) Date, Outdoor temperature, Bedroom temperature, Living temperature, Living humidity, Bedroom humidity, Outdoor humidity, Water temperature Li et al. (2009a)
  SVM, ANN Year 59 residential buildings in China Mean heat transfer coefficient of building walls, Mean thermal inert index of building walls, Roof heat transfer coefficient, Building size coefficient, Absorption coefficient for solar radiation of exterior walls, Window to wall ratio in four directions, Mean window to wall ratio, Shading coefficient of window in four directions, Integrated shading coefficient Li et al. (2010)
  SVM, ANN Hour A university office building (electrical load data is collected with a power meter) Outdoor/indoor temperature and humidity, Indoor illumination, Solar radiation, Calendar nominal attributes Massana et al. (2015) Li et al. (2010)
  GMM Day DoE super market reference model (climate data from Chicago) Outside dry-bulb air temperature and humidity ratio, Direct solar radiation Srivastav et al. (2013)