Smart Grid and Renewable Energy

Smart Grid and Renewable Energy

ISSN Print: 2151-481X
ISSN Online: 2151-4844
www.scirp.org/journal/sgre
E-mail: sgre@scirp.org
"Comparison and Simulation of Building Thermal Models for Effective Energy Management"
written by Fatima Amara, Kodjo Agbossou, Alben Cardenas, Yves DubĂŠ, Sousso Kelouwani,
published by Smart Grid and Renewable Energy, Vol.6 No.4, 2015
has been cited by the following article(s):
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[2] Parameter identification framework of thermal network model for ventilated heating floor
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[3] Accuracy of Peak Demand Estimates for Office Buildings Using eQUEST
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[6] Real building implementation of a deep reinforcement learning controller to enhance energy efficiency and indoor temperature control
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[7] Demand-side energy flexibility estimation for day-ahead models
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[8] Development of a white-box dynamic building thermal model integrated with a heating system
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[9] Development of thin surface virtual sensors for predictive maintenance
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[10] Study of electrical consumption flexibility offered by HVAC system based on rooms thermal modelling-tertiary building case study
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[11] TRNSYS 컴포넌트를 활용한 Grey-box 건물부하 모델 개발
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[12] AN OPTIMAL ENERGY MANAGEMENT SYSTEM FOR SUSTAINABLE CITY BASED ON RENEWABLE ENERGY SOURCES
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[13] Economic potential of Demand Response for office buildings in the Netherlands
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[14] Dynamic simulation of Swedush residential building renovations and its impact on the district heating network
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[15] Internet-of-Things-enabled smart local energy management system
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[16] Machine Learning-Enabled Predictive Modeling of Building Performance for Electricity Optimization
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[17] Evaluation of Digital Twin Approaches for Thermal Modeling and Energy Optimization for Existing Buildings
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[18] Data-driven modelsfor estimating heatpump powerconsumption
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[19] Toward a Fast but Reliable Energy Performance Evaluation Method for Existing Residential Building Stock
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[20] A physics-based domain adaptation framework for modeling and forecasting building energy systems
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[21] Variable Structure-Based Control for Dynamic Temperature Setpoint Regulation in Hospital Extreme Healthcare Zones
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[22] Component model calibration using typical AHU data for improved prediction of daily heat source energy consumption
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[23] Building Performance Simulation for Energy Rationalization
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[24] A mixed integer linear programming-based simple method for optimizing the design and operation of space heating and domestic hot water hybrid systems in …
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[25] Energy modeling and predictive control of environmental quality for building energy management using machine learning
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[28] A transfer learning framework for predictive energy-related scenarios in smart buildings
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[31] Comprehensive experimental validation and performance analysis of a data-driven model for two brine-to-water heat pumps
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[32] ModÊlisation adaptative des systèmes ÊnergÊtiques rÊsidentiels dans un contexte de gestion transactionnelle de la demande
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[33] Assessing and Monitoring of Building Performance by Diverse Methods
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[34] Demand response strategy applied to planning the operation of an air conditioning system. Application to a medical center
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[35] Quantifying the effect of multiple load flexibility strategies on commercial building electricity demand and services via surrogate modeling
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[36] Associating indoor air temperature with building spatial design and occupancy features: A statistical analysis on university classrooms
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[37] A framework for short-term energy consumption prediction based on room air conditioner group characteristics
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[38] Distributed Stochastic Model Predictive Control for Peak Load Limiting in Networked Microgrids With Building Thermal Dynamics
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[39] Understanding and Reducing HVAC Power Consumption Post Evacuation Events in Commercial Buildings
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[40] Predictive management of the hybrid generation dispatch and the dispatchable demand response in microgrids with heating, ventilation, and air-conditioning (HVAC) …
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[41] An innovative approach to check buildings insulation efficiency using thermal cameras
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[42] A Novel Learning Algorithm Based on Bayesian Statistics: Modelling Thermostat Adjustments for Heating and Cooling in Buildings
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[43] Analysis of Smart Thermostat Thermal Models for Residential Building
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[44] Implementation of Load Demand Prediction Model for a Domestic Load Center Using Different Machine Learning Algorithms—A Comparison
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[45] Hybrid Models for Indoor Temperature Prediction Using Long Short Term Memory Networks—Case Study Energy Center
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[46] An Integrated Hybrid Thermal Dynamics Model and Energy Aware Optimization Framework for Grid-Interactive Residential Building Management
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[47] Real-Time Flexibility Market Participation of Thermostatically Controlled Loads
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[48] Practical Aspects of Active Distribution Networks
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[49] Simulation-based assessment of energy use in factories
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[50] Optimizacion del Costo ElĂŠctrico de Grandes Demandas en Argentina por Medio de la GestiĂłn Predictiva del Sistema de Climatizacion
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[51] Advancing Industrial Participation in Demand Response within National Electricity Grids through Systematic Asset Selection, Risk Assessment and Modelling …
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[52] Life-cycle Greenhouse Gas Emissions of Commercial Buildings: An Analysis for Green-building Implementation Using a Green Star Rating System
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[53] A Comparative study on state of charge estimation techniques for Lithium-ion Batteries
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[54] Killing two birds with one stone: improving building energy efficiency and occupant comfort
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[55] A data-Driven approach for guiding the occupant's actions to achieve better comfort in buildings
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[56] Dynamic Simulation-Based Surrogate Model for the Dimensioning of Building Energy Systems
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[57] Optimizing Occupant Actions to Enhance His Comfort While Reducing Energy Demand in Buildings
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[58] Optimale Gebäudesteuerung mittels Systemlinearisierung auf Basis eines verallgemeinerten physikalischen Modells Optimal building control using system …
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[59] Modeling and Scheduling Home Appliances using Nature Inspired Algorithms for Demand Response Purpose
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[60] D2. 3–Aggregation of large-scale and small-scale assets connected to the electricity network
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[61] Achieving Thermal Comfort Using Intelligent Windows in Buildings
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[62] Feature assessment frameworks to evaluate reduced-order grey-box building energy models
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[63] Quantifying the effect of multiple demand response actions on electricity demand and building services via surrogate modeling
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[64] Solar Chimney and Turbine-Assisted Ventilation System
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[65] Modelli ibridi per la predizione della temperatura indoor: case study Energy Center= Hybrid models for indoor temperature prediction: case study Energy Center
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[66] Aggregation of large-scale and small-scale assets connected to the electricity network
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[67] CNN-LSTM architecture for predictive indoor temperature modeling
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[68] Assessment of life cycle embodied energy and material cost in Australian shopping centres: Implications for material selection
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[69] Multi-Building Systems Thermal and Energy Management via Geothermal Heat Pump
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[70] Control Predictivo Conjunto del Despacho de GeneraciĂłn HĂ­brida y de la Demanda Incluyendo ClimatizaciĂłn en Microrredes
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[71] Coordinated planning of distributed WT, shared BESS and individual VESS using a two-stage approach
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[72] Energy saving potentials of a photovoltaic assisted heat pump for hybrid building heating system via optimal control
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[73] Structured modelling from data and optimal control of the cooling system of a large business center
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[74] Data-driven predictive control for unlocking building energy flexibility: A review
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[75] Reinforcement learning for whole-building HVAC control and demand response
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[76] First results of remote building characterisation based on smart meter measurement data
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[77] An Online Grey-Box Model Based on Unscented Kalman Filter to Predict Temperature Profiles in Smart Buildings
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[78] A Comparative Analysis of Machine Learning Approaches for Short-/Long-Term Electricity Load Forecasting in Cyprus
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[79] Incorporating observed data into early design energy models for life cycle cost and carbon emissions analysis of campus buildings
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[80] Buildings Energy Efficiency Analysis and Classification Using Various Machine Learning Technique Classifiers
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[81] Prognoseregulering av kjølesystemer for norske kontorbygg
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[82] Automatic verification of stochastic processes: certification of building automation systems
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[83] Forecasting summer-time overheating in UK homes using time series models
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[84] Smart Integrated Optimization Technique for Large Chilled Water Systems
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[85] Forecasting Indoor Temperatures During Heatwaves: Do More Complex Models Provide Better Predictions?
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[86] Integrated Machine Learning Modeling and Fault Detection Approach for Chilled Water Systems
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[87] Home Appliance Modelling and Control for Demand Response Applications
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[88] A Network of BIMGs Participating in Demand Response Using EVs and HVAC Units
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[89] Scalable Smart Building Simulation
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[90] Building Envelope Component to Control Thermal Indoor Environment in Sustainable Building: a Review
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[91] Overview of the use of artificial neural networks for energy‐related applications in the building sector
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[92] Bond Graph Modeling and Control of A Single-Zone Building in a Semi-Arid Region for Thermal Comfort
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[93] A novel energy scheduling framework for reliable and economic operation of islanded and grid-connected microgrids
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[94] A Grey-box Model Based on Unscented Kalman Filter to Estimate Thermal Dynamics in Buildings
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[95] Artificial neural network prediction models of stratified thermal energy storage system and borehole heat exchanger for model predictive control
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[96] Can semi-parametric additive models outperform linear models, when forecasting indoor temperatures in free-running buildings?
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[97] Demand Response Strategy Applied to Residential Electric Water Heaters Using Dynamic Programming and K-Means Clustering
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[98] HOME ENERGY MANAGEMENT SYSTEM FOR DEMAND RESPONSE PURPOSES
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[99] Smart Integrated Optimization Technique for Large Chilled Water Systems.
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[100] Energy Performance Modelling and Consumption Forecasting in Built Environments
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[101] Identification de modèle thermique de bâtiment dans un environnement d'objets connectÊs
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[102] Application of model predictive control for the optimization of thermo-hygrometric comfort and energy consumption of buildings.
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[104] Building identification within a connected object ecosystem
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[105] Reduced-Order Energy Modeling for Advanced Setpoint Controls of Residential Buildings with Time-of-Use Rates
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[106] A review of data-driven building energy consumption prediction studies
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[107] Reduced Order Modeling for Virtual Building Commissioning
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[108] Description and ASSESSMENT of the BUILDING SURFACE TEMPERATURE modellING IN LASER/F
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[109] On the Evolution and Application of the Thermal Network Method for Energy Assessments in Buildings
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[110] Forecasting indoor temperatures during heatwaves using time series models
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[111] Prediction of Internal Temperatures During Hot Summer Conditions with Time Series Forecasting Models
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[112] Izgradnja linearnih regresijskih modelov za napovedovanje toplotnega odziva stavbe
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[114] Building Modelling Methodology Combined to Robust Identification for the Temperature Prediction of a Thermal Zone in a Multi-zone Building
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[115] Online model estimation for predictive control of air conditioners in buildings.
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[116] Development of thermal network to simulate light structured buildings and comparison with heavy structured buildings
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[117] Selecting the Most Effective Energy Modeling Tool Based on a Project Requirement
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[118] Impact of the uses of various technologies on the thermal performance and energy efficiency of UK hotel buildings: application to Hilton hotels in the UK
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[119] A TEST CELL TO INFER THERMAL RESPONSE OF BUILDING COMPONENTS FOR MODEL PREDICTIVE CONTROL USING BUILDING AUTOMATION …
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[120] Application of model predictive control for the optimization of thermo-hygrometric comfort and energy consumption of buildings
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[121] Analyse des stratÊgies de contrôle pour un système de chauffage ventilation et conditionnement de l'air (CVCA) complexe à l'aide d'un modèle calibrÊ
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[122] IKON-Intelligente Betriebsfßhrung durch Kommunikation von Produktion und Gebäudetechnik mit einem kßnstlichen neuronalen Netz
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[123] Identification of a thermal building model by learning the dynamics of the solar flux
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[124] The adjacent walls effects in simplified thermal model of buildings
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[125] Model based control of a hybrid heat pump system for building heating
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[127] Parametric system identification using deep convolutional neural networks
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[128] A generalization approach for reduced order modelling of commercial buildings
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[129] Energy Conservation with Fuzzy Logic Controller Towards Green Telecommunication
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[130] Predicting Building Energy Consumption using Engineering and Data Driven Approaches: A Review
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[131] A Self-Learning Algorithm for Estimating Solar Heat Gain and Temperature Changes in a Single-Family Residence
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[132] A Data Driven Pre-cooling Framework for Energy Cost Optimization in Commercial Buildings
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[134] Toward building energy management: Electric analog modeling for thermal behavior simulation
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[135] Integrated Performance Based Design of Communities and Distributed Generation
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[136] Unlocking the value of distributed energy resources in electric distribution networks: exploring the role of locational tariffs
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[137] Estimation of temperature correlation with household electricity demand for forecasting application
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[138] A Simplified Thermal Model to Control the Energy Fluxes and to Improve the Performance of Buildings
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[139] Hourly Calculation Method of Air Source Heat Pump Behavior
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[140] Application of building-dynamics-based control strategies to improve air-conditioning performance in educational buildings
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[142] Coupling building thermal network and control system, the first step to smart buildings
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[143] Modeling of residential centralized and baseboard space heating systems
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[144] Energy Conservation for Base Transceiver Station Cooling System with Energy Plus Software
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[145] MÊthodologie pour estimer la consommation d'Ênergie dans les bâtiments en utilisant des techniques d'intelligence artificielle
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[146] Methodology to estimate building energy consumption using artificial intelligence
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[148] Software Models for Operating a Smart Grid Demonstrator with Respect to Load Optimization
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[149] Signature redacted_ _
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[150] An ANN-GA Semantic Rule-Based System to Reduce the Gap Between Predicted and Actual Energy Consumption in Buildings
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[151] Predictive thermal control with different sensor configurations
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