☆ 4.7 Review

Model predictive control of heating, ventilation, and air conditioning (HVAC) systems: A state-of-the-art review

JOURNAL OF BUILDING ENGINEERING (2022)

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Article Energy & Fuels

Machine-learning-based model predictive control with instantaneous linearization-A case study on an air-conditioning and mechanical ventilation system

Shiyu Yang et al.

Summary: This study introduces a ML-based MPC with an instantaneous linearization scheme, which significantly reduces computation time while improving indoor thermal comfort. The system achieved reductions in cooling energy consumption and demonstrated no obvious performance degradation, showing the potential for efficient and effective building energy management using machine learning.

APPLIED ENERGY (2022)

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Article Construction & Building Technology

Interpreting the neural network model for HVAC system energy data mining

Man Wang et al.

Summary: This study proposes a method to interpret neural network models using gradients, quantifying the influence of inputs on outputs. The method reduces calculation time and provides reasonable and informative feature importance compared to other models.

BUILDING AND ENVIRONMENT (2022)

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Article Construction & Building Technology

Model predictive control under weather forecast uncertainty for HVAC systems in university buildings

Juan Hou et al.

Summary: This study aimed to improve the performance of model predictive control (MPC) under weather forecast uncertainty by introducing an error model. The results showed that the MPC with the error model achieved significant energy cost savings and improved thermal comfort, especially under low error conditions.

ENERGY AND BUILDINGS (2022)

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Article Construction & Building Technology

Cooling seasonal performance of inverter air conditioner using model prediction control for demand response

Cuiling Wang et al.

Summary: The supply-demand imbalance in smart grids poses challenges to power consumption and grid safety. Demand response control, particularly as applied to air conditioners, can help reduce peak energy consumption and save energy. Model predictive control (MPC) has been proven effective in this regard. This study examines the cooling performance of an inverter AC with MPC and demonstrates its superior performance compared to traditional control methods.

ENERGY AND BUILDINGS (2022)

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Article Construction & Building Technology

Experimental demonstration of grid-supportive scheduling of a polygeneration system using economic-MPC

Parantapa Sawant et al.

Summary: This study demonstrates the optimal scheduling of a building energy system based on economic-MPC, showing improved performance compared to a traditional controller. With the MPC, both quantitative benefits in terms of cost savings and qualitative benefits in controller adaptability are identified, as well as further research potential for improving stability, minimizing constraint violations, and enhancing inter-system communication.

ENERGY AND BUILDINGS (2022)

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Article Computer Science, Information Systems

Pandemic-Aware Day-Ahead Demand Forecasting Using Ensemble Learning

Ali Arjomandi-Nezhad et al.

Summary: This study uses ensemble-based machine learning models to forecast country-level electricity demand, especially during the Covid-19 pandemic. The results show that ensemble models are capable of accurately predicting demand, and most models are robust against missing pandemic policy data. It is also found that utilizing pandemic policy data as features significantly improves forecasting accuracy. The probabilistic quantile regression demonstrates high accuracy in this case study.

IEEE ACCESS (2022)

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Article Construction & Building Technology

A novel probabilistic regression model for electrical peak demand estimate of commercial and manufacturing buildings

Saman Taheri et al.

Summary: This study develops probabilistic demand estimation models using a probabilistic Bayesian regression framework. The results show that the proposed algorithm achieves accurate future demand estimation and can be updated with new information. The algorithm outperforms other machine learning methods in terms of mean absolute error and mean absolute percentage error in two real-world case studies.

SUSTAINABLE CITIES AND SOCIETY (2022)

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Article Construction & Building Technology

Comparison of online and offline deep reinforcement learning with model predictive control for thermal energy management

Silvio Brandi et al.

Summary: This paper compares the application of online and offline Deep Reinforcement Learning (DRL) with a Model Predictive Control (MPC) architecture in energy management. The results show that although the initially trained DRL agent performs relatively poorly, it is able to converge to a control policy that is almost as effective as the model-based strategies. This provides a promising solution to overcome the modelling requirement barriers of MPC and offline-trained DRL approaches.

AUTOMATION IN CONSTRUCTION (2022)

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Article Construction & Building Technology

Investigation on pre-cooling potential of UFAD via model-based predictive control

Jaewan Joe

Summary: This study explores the potential for cost-saving in operating an underfloor air distribution (UFAD) system using model-based predictive control (MPC). By constructing a grey-box building model based on real building measurements, the study quantifies the energy-saving potential of MPC compared to feedback control through simulation. The results show that MPC can achieve energy savings of over 30% in the cooling season and around 20% in the intermediate season. Higher savings are observed when the outdoor air temperature and solar radiation are high. The size of the plenum does not significantly affect the energy savings, as the major savings are achieved through precooling using off-peak electricity and more efficient HVAC equipment.

ENERGY AND BUILDINGS (2022)

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Article Construction & Building Technology

Development of a prediction model tuning method with a dual-structured optimization framework for an entire heating, ventilation and air-conditioning system

Yuki Matsuda et al.

Summary: This study proposes a new modeling method based on dual-structured optimization process to create a prediction model that accurately predicts temperature changes within 24 hours, suitable for small-scale office buildings.

SUSTAINABLE CITIES AND SOCIETY (2022)

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Article Construction & Building Technology

Experimental analysis of artificial intelligence-based model predictive control for thermal energy storage under different cooling load conditions

Doyun Lee et al.

Summary: This study proposed an artificial intelligence-based model predictive control (MPC) scheme to optimize the operation of a thermal energy storage (TES) system. Experimental analysis showed that the AI-based MPC was able to flexibly manage the system under different load levels and reduce operating costs.

SUSTAINABLE CITIES AND SOCIETY (2022)

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Article Construction & Building Technology

Investigating the flexibility of a novel multi-zone air heating and ventilation system using model predictive control

Mahmood Khatibi et al.

Summary: This paper investigates the flexibility of a novel multi-zone air heating and ventilation (MZHV) system by comparing it with the conventional variable air volume (VAV) systems. Model predictive control (MPC) is used to control the real-time power consumption of a multi-zone building. The results show that the MZHV system provides significant flexibility in terms of energy usage, without compromising on comfort levels.

JOURNAL OF BUILDING ENGINEERING (2022)

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Article Construction & Building Technology

MPC solution for optimal load shifting for buildings with ON/OFF staged packaged units: Experimental demonstration, and lessons learned

Donghun Kim et al.

Summary: This paper presents a hierarchical MPC solution for load shifting in small and medium-sized commercial buildings. The solution coordinates compressor stages to eliminate unnecessary peaks and shifts the electrical load based on the electric price signal, resulting in cost savings. Laboratory tests demonstrate the trade-offs between energy efficiency and load flexibility, providing insights for applying MPCs in this context.

ENERGY AND BUILDINGS (2022)

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Article Energy & Fuels

Energy efficient thermal comfort predictive control for household heat metering room

Xucheng Chang et al.

Summary: This article presents the application of the EETCMPC method in household heat metering buildings, which can effectively reduce energy consumption and provide thermal comfort control.

ENERGY REPORTS (2022)

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Article Construction & Building Technology

Real-world implementation and cost of a cloud-based MPC retrofit for HVAC control systems in commercial buildings

Max Bird et al.

Summary: This paper presents a case study on improving the energy and carbon usage of a food-retail building through the use of a generalisable model predictive control (MPC) framework. The study shows that the MPC approach can achieve a lower overall cost for the HVAC system while ensuring thermal comfort of occupants.

ENERGY AND BUILDINGS (2022)

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Review Green & Sustainable Science & Technology

Smart design and control of thermal energy storage in low-temperature heating and high-temperature cooling systems: A comprehensive review

Amirmohammad Behzadi et al.

Summary: This article presents the latest technology on the smart design of thermal energy storage (TES) integrated with low-temperature heating (LTH) and high-temperature cooling (HTC) systems. It discusses the basic concepts and classification of TES, reviews the literature on control approaches and optimization methods, and explores the specifications and advantages and disadvantages of LTH and HTC systems. The article also investigates the smart design of TES integrated with LTH and HTC systems based on control approach/strategy, optimization method, building type, and energy supplier to find the newest technology, ideas, and features and detect existing gaps.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2022)

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Review Materials Science, Multidisciplinary

Recent Advances on Capacitive Proximity Sensors: From Design and Materials to Creative Applications

Reza Moheimani et al.

Summary: This article provides a comprehensive overview of capacitive proximity sensors (CPSs), including their applications, design characteristics, and current construction methods. The evaluation of various nanocomposites and detection approaches is emphasized. Understanding CPSs is essential for addressing issues and driving technological advancements.

C-JOURNAL OF CARBON RESEARCH (2022)

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Article Thermodynamics

Reliability-based energy scheduling of active buildings subject to renewable energy and demand uncertainty

Saman Taheri et al.

Summary: This article proposes a probabilistic-based optimization approach to address the energy supply reliability challenge in active buildings with on-site renewable energy sources, taking into account the uncertainty associated with photovoltaic production and demand fluctuations. Empirical research shows that this method can increase energy supply reliability by 60% compared to traditional deterministic methods.

THERMAL SCIENCE AND ENGINEERING PROGRESS (2022)

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Article Thermodynamics

Adaptiveness of a model predictive controller for a thermal-electrical renewable energy system in four different German single-family house energy standards

Muthalagappan Narayanan et al.

Summary: The study shows that whitebox MPC can be applied to different types of residential buildings and demonstrates good adaptability in increasing renewable energy fraction and self-consumption. Significant reductions in heating demand and increases in solar thermal and PV supply are achieved in new buildings; however, whitebox MPC still faces challenges in real-time implementation due to long optimization times.

CASE STUDIES IN THERMAL ENGINEERING (2021)

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Review Construction & Building Technology

Heating energy-saving potentials in HVAC system of swimming halls: A review

Xiaolei Yuan et al.

Summary: Swimming halls, as a special building sector, are significant energy users and carbon producers. The high energy saving potentials mainly lie in the heating system, with renewable energy sources like solar energy being applied, along with energy management strategies for waste heat utilization and demand response potentials.

BUILDING AND ENVIRONMENT (2021)

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Article Construction & Building Technology

Learning-based CO2 concentration prediction: Application to indoor air quality control using demand-controlled ventilation

Saman Taheri et al.

Summary: Concerns over indoor air quality have grown due to the negative health effects of high bio-effluents levels on occupants. Implementing efficient HVAC systems is crucial for improving air quality. Using machine learning algorithms to forecast CO2 concentrations can enhance indoor air quality and reduce energy consumption. Real-time adjustment of ventilation rates based on specific needs can effectively provide ventilation.

BUILDING AND ENVIRONMENT (2021)

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Article Construction & Building Technology

Research on a forecasted load-and time delay-based model predictive control (MPC) district energy system model

Jing Zhao et al.

Summary: This paper proposes a load- and time delay-based model predictive control district energy system model, validates its superiority through experiments, and demonstrates the reduction in energy consumption.

ENERGY AND BUILDINGS (2021)

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Article Construction & Building Technology

A simple building energy model in form of an equivalent outdoor temperature

Tomasz Cholewa et al.

Summary: The authors propose a new simplified method for generating energy characteristics of buildings and their heating systems. The method only requires inputs of actual heat supplied to the heating system and local outdoor weather conditions, and outputs a building energy model in terms of an equivalent outdoor temperature. This method can accurately determine the duration and amount of heat power supplied to a building while minimizing the impact of occupants and internal heat gains.

ENERGY AND BUILDINGS (2021)

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Article Engineering, Chemical

Budget-constrained economic model predictive control: A user-friendly proposal for HVAC

Bruno F. Santoro et al.

Summary: The cost optimization of HVAC systems in buildings has been achieved through the use of economic nonlinear model predictive control, allowing building managers to balance operational costs with thermal comfort, while also providing a user-friendly interface for non-expert users.

CHEMICAL ENGINEERING RESEARCH & DESIGN (2021)

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Article Computer Science, Interdisciplinary Applications

Bayesian optimization with reference models: A case study in MPC for HVAC central plants

Qiugang Lu et al.

Summary: The article introduces a Bayesian optimization framework that exploits reference models to accelerate the tuning process of closed-loop controllers, reducing computation time by introducing reference models and efficiently navigating parameter space.

COMPUTERS & CHEMICAL ENGINEERING (2021)

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Article Thermodynamics

Model predictive control for optimal energy management of connected cluster of microgrids with net zero energy multi- greenhouses

Ahmed Ouammi

Summary: This paper presents a cooperative control framework for a connected cluster of microgrids with multi-smart greenhouses in the context of smart grids. The framework aims to optimize the operation of the microgrids and manage power flow exchange to ensure high quality of service. An optimization algorithm is developed to effectively control the operation of clustered microgrids and enhance energy efficiency by manipulating micro-climate variables.

ENERGY (2021)

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Article Construction & Building Technology

Development and evaluation of data-driven controls for residential smart thermostats

Brent Huchuk et al.

Summary: The study compared three different HVAC control methods and found that MPC control had the lowest average cost, better linear model predictive capability, and did not subject occupants to the discomfort of system exploration compared to the other methods.

ENERGY AND BUILDINGS (2021)

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Article Construction & Building Technology

Fault detection diagnostic for HVAC systems via deep learning algorithms

Saman Taheri et al.

Summary: Deep learning algorithms, particularly deep recurrent neural networks (DRNNs), have gained attention for fault detection diagnostic in HVAC systems due to their high detection accuracy. Challenges include exploring bespoke DRNN configurations and optimizing hyperparameters, but the study successfully introduces and compares different configurations to achieve high performance. The final DRNN model outperforms other advanced data-driven techniques such as random forest and gradient boosting, showcasing its effectiveness in fault detection for HVAC systems.

ENERGY AND BUILDINGS (2021)

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Article Green & Sustainable Science & Technology

Energy utilization assessment of a semi-closed greenhouse using data-driven model predictive control

Farhat Mahmood et al.

Summary: With the global increase in food demand, closed and controlled greenhouses have become an essential source for year-round crop production. This study proposes a data-driven model predictive control approach for temperature control and energy reduction in semi-closed greenhouses, demonstrating better performance compared to traditional adaptive control systems.

JOURNAL OF CLEANER PRODUCTION (2021)

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Article Automation & Control Systems

Coordinated control for Air Handling Unit and Variable Air Volume boxes in multi-zone HVAC system

Shunjian Ma et al.

Summary: This paper proposes a coordinated strategy of distributed model predictive control (DMPC) to regulate Variable Air Volume (VAV) boxes and Air Handling Unit (AHU) in a multi-zone HVAC system. By implementing equivalent local cooling cost and total-air-mass-rate penalty term, the operational cost of the HVAC system can be reduced with coordination from both DMPC and the upper layer.

JOURNAL OF PROCESS CONTROL (2021)

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Article Construction & Building Technology

Building HVAC control with reinforcement learning for reduction of energy cost and demand charge

Zhanhong Jiang et al.

Summary: Researchers have developed a Deep Q-Network (DQN) and reward shaping technique to address energy efficiency optimization in building control, demonstrating that the customized DQN outperforms baseline policies by saving close to 6% of total cost with demand charges and close to 8% without demand charges.

ENERGY AND BUILDINGS (2021)

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Article Automation & Control Systems

Performance improvement of an air-to-water heat pump through linear time-varying MPC with adaptive COP predictor

Soroush Rastegarpour et al.

Summary: This paper discusses how to optimize the performance of air-to-water heat pumps by controlling the COP, which depends on external temperature and load water temperature. An adaptive time-varying predictive model is developed to tackle the nonlinear optimization problem, and it is validated on a real case study, demonstrating the accuracy and potential of the method.

JOURNAL OF PROCESS CONTROL (2021)

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Article Energy & Fuels

Experiment study of machine-learning-based approximate model predictive control for energy-efficient building control

Shiyu Yang et al.

Summary: This study proposes an approximate MPC method that mimics the dynamic behaviors of MPC using recurrent neural networks, with implementation in two testbeds showing similar control performance to MPC and significantly reduced computational load.

APPLIED ENERGY (2021)

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Article Automation & Control Systems

Accelerated distributed model predictive control for HVAC systems

Liangliang Chen et al.

Summary: This paper investigates the accelerated distributed model predictive control (MPC) strategy for HVAC systems with local and global power input constraints. The problems are formulated and converted into a quadratic programming problem in the distributed MPC framework. Thermal couplings between neighboring zones and unknown thermal disturbances are considered, and a distributed fast MPC protocol is designed considering electricity cost and occupant comforts.

CONTROL ENGINEERING PRACTICE (2021)

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Review Green & Sustainable Science & Technology

A review on available energy saving strategies for heating, ventilation and air conditioning in underground metro stations

Yanzhe Yu et al.

Summary: This paper discusses strategies for HVAC energy saving in underground stations, including summarizing design features, identifying issues, introducing energy-saving strategies, classifying and comparing strategies, and proposing future challenges.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2021)

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Article Chemistry, Analytical

Instantaneous Differentiation of Functional Isomers via Reactive Flowing Atmospheric Pressure Afterglow Mass Spectrometry

Dong Zhang et al.

Summary: A novel reactive flowing atmospheric-pressure afterglow mass spectrometry source was developed for rapid isomer differentiation in real time, successfully distinguishing two functional isomers of valproic acid metabolites, and improving detection sensitivity for some larger analyte types.

ANALYTICAL CHEMISTRY (2021)

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Article Energy & Fuels

Model predictive control for integrated control of air-conditioning and mechanical ventilation, lighting and shading systems

Shiyu Yang et al.

Summary: The research proposed a MPC system with multiobjective MPC scheme to enable coordinated control of multiple building services for optimized energy efficiency, indoor thermal comfort, and visual comfort. Experimental comparison showed that the MPC system achieved significant energy savings and improved indoor comfort and visual comfort compared to a conventional BMS.

APPLIED ENERGY (2021)

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Article Automation & Control Systems

Adaptive Stochastic MPC Under Time-Varying Uncertainty

Monimoy Bujarbaruah et al.

Summary: This article presents an adaptive model-predictive control strategy for constrained uncertain systems, refining the feasible parameter set using known bounds on process noise to satisfy constraints and demonstrating the feasibility and stability of the algorithm.

IEEE TRANSACTIONS ON AUTOMATIC CONTROL (2021)

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Article Engineering, Electrical & Electronic

Long-term planning of integrated local energy systems using deep learning algorithms

Saman Taheri et al.

Summary: This study focuses on the application of deep recurrent neural networks in medium to long-term energy consumption prediction, optimizing models for heating and electricity consumption through tuning and comparing different DRNN variants and outperforming other machine learning techniques in terms of accuracy. Additionally, an optimization framework is proposed to enhance the efficiency of EH planning by utilizing deep learning algorithms.

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS (2021)

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Article Energy & Fuels

Sensor impacts on building and HVAC controls: A critical review for building energy performance

Yeonjin Bae et al.

Summary: This paper provides a comprehensive literature review on sensor systems in building/HVAC systems, focusing on their impacts on energy efficiency and thermal comfort in the context of controls. The study aims to understand past and current research while identifying future research opportunities. Through interviews and literature review, the researchers summarized key aspects of sensors and collected insights from industry experts and practitioners.

ADVANCES IN APPLIED ENERGY (2021)

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Proceedings Paper Automation & Control Systems

Virtual Storage Plant Aggregating Electrical Energy Storages and HVAC Systems Providing Regulating Reserve and Voltage Regulation

Xiao Wang et al.

Summary: This paper presents a distributed predictive control framework coordinating battery energy storage systems and HVAC systems in the distribution network for the provision of ancillary services to the power grid, while maintaining indoor thermal comfort and network voltage within acceptable limits. The optimization problem formulated for coordinating virtual storage plants (VSPs) is solved in a distributed manner using the ADMM method, demonstrating the effectiveness of the proposed approach in delivering the required services under system constraints.

IFAC PAPERSONLINE (2021)

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Article Automation & Control Systems

From linear to nonlinear MPC: bridging the gap via the real-time iteration

Sebastien Gros et al.

INTERNATIONAL JOURNAL OF CONTROL (2020)

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Article Green & Sustainable Science & Technology

Stochastic framework for planning studies of energy systems: a case of EHs

Saman Taheri et al.

IET RENEWABLE POWER GENERATION (2020)

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Article Green & Sustainable Science & Technology

Integration of weather forecast and artificial intelligence for a short-term city-scale natural gas consumption prediction

Aleksandar S. Andelkovic et al.

JOURNAL OF CLEANER PRODUCTION (2020)

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Article Energy & Fuels

Optimal rule-based control for the management of thermal energy storage in a Canadian solar district heating system

E. Saloux et al.

SOLAR ENERGY (2020)

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Article Construction & Building Technology

Robust model predictive control of HVAC systems with uncertainty in building parameters using linear matrix inequalities

Himanshu Nagpal et al.

ADVANCES IN BUILDING ENERGY RESEARCH (2020)

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Article Construction & Building Technology

Comparative assessment of HVAC control strategies using personal thermal comfort and sensitivity models

Wooyoung Jung et al.

BUILDING AND ENVIRONMENT (2019)

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Article Energy & Fuels

Comparison of four rule-based demand response control algorithms in an electrically and heat pump-heated residential building

Behrang Alimohammadisagvand et al.

APPLIED ENERGY (2018)

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Review Energy & Fuels

Model Predictive Control (MPC) for Enhancing Building and HVAC System Energy Efficiency: Problem Formulation, Applications and Opportunities

Gianluca Serale et al.

ENERGIES (2018)

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Article Construction & Building Technology

Parametric analysis of external and internal factors influence on building energy performance using non-linear multivariate regression models

Inna Bilous et al.

JOURNAL OF BUILDING ENGINEERING (2018)

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Article Construction & Building Technology

Supervisory model predictive controller (MPC) for residential HVAC systems: Implementation and experimentation on archetype sustainable house in Toronto

Abdul Afram et al.

ENERGY AND BUILDINGS (2017)

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Review Construction & Building Technology

Artificial neural network (ANN) based model predictive control (MPC) and optimization of HVAC systems: A state of the art review and case study of a residential HVAC system

Abdul Afram et al.

ENERGY AND BUILDINGS (2017)

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Article Energy & Fuels

Simulation-based optimization of an integrated daylighting and HVAC system using the design of experiments method

Wonuk Kim et al.

APPLIED ENERGY (2016)

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Article Energy & Fuels

Occupancy-based demand response and thermal comfort optimization in microgrids with renewable energy sources and energy storage

Christos D. Korkas et al.

APPLIED ENERGY (2016)

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Article Construction & Building Technology

The IMBPC HVAC system: A complete MBPC solution for existing HVAC systems

Antonio E. Ruano et al.

ENERGY AND BUILDINGS (2016)

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Review Construction & Building Technology

Occupancy behavior based model predictive control for building indoor climate-A critical review

Amin Mirakhorli et al.

ENERGY AND BUILDINGS (2016)

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Article Construction & Building Technology

Simulation-based model predictive control by the multi-objective optimization of building energy performance and thermal comfort

Fabrizio Ascione et al.

ENERGY AND BUILDINGS (2016)

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Article Automation & Control Systems

A Computationally Efficient Model Predictive Control Strategy for Linear Systems With Integer Inputs

Petros Karamanakos et al.

IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY (2016)

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Article Energy & Fuels

Experimental study of occupancy-based control of HVAC zones

Siddharth Goyal et al.

APPLIED ENERGY (2015)

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Article Thermodynamics

Predictive modeling and optimization of a multi-zone HVAC system with data mining and firefly algorithms

Yaohui Zeng et al.

ENERGY (2015)

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Article Thermodynamics

Multi-objective optimization of the HVAC (heating, ventilation, and air conditioning) system performance

Xiupeng Wei et al.

ENERGY (2015)

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Article Construction & Building Technology

Energy-efficient control of under-actuated HVAC zones in commercial buildings

Jonathan Brooks et al.

ENERGY AND BUILDINGS (2015)

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Article Construction & Building Technology

Model predictive control for indoor thermal comfort and energy optimization using occupant feedback

Xiao Chen et al.

ENERGY AND BUILDINGS (2015)

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Article Thermodynamics

Application of adaptive neural predictive control for an automotive air conditioning system

Boon Chiang Ng et al.

APPLIED THERMAL ENGINEERING (2014)

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Review Construction & Building Technology

Theory and applications of HVAC control systems - A review of model predictive control (MPC)

Abdul Afram et al.

BUILDING AND ENVIRONMENT (2014)

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Article Construction & Building Technology

Model predictive HVAC control with online occupancy model

Justin R. Dobbs et al.

ENERGY AND BUILDINGS (2014)

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Article Construction & Building Technology

CO2 sensors for occupancy estimations: Potential in building automation applications

Mattias Gruber et al.

ENERGY AND BUILDINGS (2014)

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Article Construction & Building Technology

Model-based controllers for indoor climate control in office buildings - Complexity and performance evaluation

Mattias Gruber et al.

ENERGY AND BUILDINGS (2014)

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Article Construction & Building Technology

Performance optimization of HVAC systems with computational intelligence algorithms

Xiaofei He et al.

ENERGY AND BUILDINGS (2014)

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Article Construction & Building Technology

Trial results from a model predictive control and optimisation system for commercial building HVAC

Samuel R. West et al.

ENERGY AND BUILDINGS (2014)

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Article Thermodynamics

Minimization of energy consumption in HVAC systems with data-driven models and an interior-point method

Andrew Kusiak et al.

ENERGY CONVERSION AND MANAGEMENT (2014)

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Article Thermodynamics

Implementation of model predictive control for an HVAC system in a mid-size commercial building

Sorin C. Bengea et al.

HVAC&R RESEARCH (2014)

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Article Engineering, Electrical & Electronic

Genetic-Algorithm-Based Optimization Approach for Energy Management

A. Arabali et al.

IEEE TRANSACTIONS ON POWER DELIVERY (2013)

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Article Engineering, Chemical

Real-Time Optimization Strategies for Building Systems

Victor M. Zavala

INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH (2013)

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Article Engineering, Chemical

Demand reduction in building energy systems based on economic model predictive control

Jingran Ma et al.

CHEMICAL ENGINEERING SCIENCE (2012)

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Article Construction & Building Technology

Optimization of Predicted Mean Vote index within Model Predictive Control framework: Computationally tractable solution

Jiri Cigler et al.

ENERGY AND BUILDINGS (2012)

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Article Construction & Building Technology

Neural networks based predictive control for thermal comfort and energy savings in public buildings

P. M. Ferreira et al.

ENERGY AND BUILDINGS (2012)

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Article Engineering, Electrical & Electronic

Reducing Transient and Steady State Electricity Consumption in HVAC Using Learning-Based Model-Predictive Control

Anil Aswani et al.

PROCEEDINGS OF THE IEEE (2012)

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Article Energy & Fuels

Experimental analysis of model predictive control for an energy efficient building heating system

Jan Siroky et al.

APPLIED ENERGY (2011)

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Article Construction & Building Technology

Application of model based predictive control for water-based floor heating in low energy residential buildings

Henrik Karlsson et al.

BUILDING AND ENVIRONMENT (2011)

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Article Automation & Control Systems

Model predictive control of VAV zone thermal systems concerning bi-linearity and gain nonlinearity

Gongsheng Huang

CONTROL ENGINEERING PRACTICE (2011)

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Article Thermodynamics

Multi-objective optimization of HVAC system with an evolutionary computation algorithm

Andrew Kusiak et al.

ENERGY (2011)

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Article Thermodynamics

Optimization of an HVAC system with a strength multi-objective particle-swarm algorithm

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ENERGY (2011)

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