Due to the power crisis in Pakistan there is a growing market of small household generators rangi... more Due to the power crisis in Pakistan there is a growing market of small household generators ranging from 2-3 KVA which can handle the load of a small house comprising of a few fans, lights, a computer and a TV. These generators are cheap and come equipped with a self-start mechanism built into the generator. On the push of a button, the user can start the generator easily. In the cities, normally these generators are used for a short period of time when the power from the grid is not available. When the power from the grid is not available the user starts the generator and connects the load to the generator manually. When the power from the grid becomes available, the user disconnects the generator from the load, turns off the generator and connects the load to the grid manually. Normally this function is performed manually and requires the engagement of the user for turning the generator on and off and shifting the load between the generator and the grid. In this paper we propose a...
In this paper, a comprehensive review of the artificial neural network (ANN) based model predicti... more In this paper, a comprehensive review of the artificial neural network (ANN) based model predictive control (MPC) system design is carried out followed by a case study in which ANN models of a residential house located in Ontario, Canada are developed and calibrated with the data measured from site. A new algorithm called best network after multiple iterations (BNMI) is introduced to help in determining the appropriate ANN architecture. The prediction performance of the developed models using BNMI algorithm was significantly better (between 6% and 59% better goodness of fit for various models) when compared to a previous study carried out by the authors which used the default single iteration ANN training algorithm of MATLAB ®. The ANN models were further used to design the supervisory MPC for the residential HVAC system. The MPC generated the dynamic temperature set-point profiles of the zone air and buffer tank water which resulted in the operating cost reduction of the equipment without violating the thermal comfort constraints. When compared to the fixed set-point (FSP), MPC was able to save operating cost between 6% and 73% depending on the season.
Residential heating, ventilation and air conditioning (HVAC) systems generally employ simple on/o... more Residential heating, ventilation and air conditioning (HVAC) systems generally employ simple on/off controllers to regulate the temperature of water and air in different subsystems. Selection of set-point of a controlled process and dead-band of controller affects the process regulation, energy consumption and actuator switching frequency. This article presents a calibrated model of a residential HVAC system. Temperature of two zones and buffer tank (BT) is regulated using on/off controllers. Non optimum controller settings result in poor regulation, higher energy consumption and higher equipment wear. The purpose of this article is to find optimum set-point and dead-band settings for on/off controllers in order to improve temperature regulation, reduce energy consumption and decrease equipment wear by reducing the switching frequency of HVAC equipment without scarifying thermal comfort of occupants.
Due to the increasing cost of electricity and its variable price structure throughout the day, it... more Due to the increasing cost of electricity and its variable price structure throughout the day, it is of interest to shift the loads to off-peak hours. In this work, the grey-box model of a domestic hot water electric boiler is presented. The developed model is useful for the development of new supervisory controller to help offset the boiler heating load to off peak hours in a smart grid environment. The boiler used in this research is an integral part of the domestic hot water system and residential Heating, Ventilating and Air-Conditioning (HVAC) systems in many Swiss homes. The water stored in the boiler is not well mixed and thus the temperature varies along the height of the boiler. The cold water is entering in the boiler from the bottom and the hot water is drawn at the top. This results in a temperature gradient along the height of the boiler which needs to be predicted to accurately simulate the temperature dynamics of the boiler. The boiler was divided into eight stratified virtual layers and physics-based model was developed by writing the heat balance equation for each layer. Experimental setup consisting of boiler, sensors and data logger was prepared at the Institute of Aerosol and Sensor Technology (IAST), University of Applied Sciences and Arts Northwestern Switzerland (FHNW) to measure the training and test data for the model including the temperature of each layer, ambient temperature, boiler's power consumption and flow rate of water entering into the boiler. The parameters of the physics-based model were estimated from the measured data thus converting it into a grey-box model. The model performance was visually compared to the measured data and was also evaluated analytically using several metrics showing the high accuracy of the developed model.
In this paper, black-box models of the residential heating, ventilation and air conditioning (HVA... more In this paper, black-box models of the residential heating, ventilation and air conditioning (HVAC) system are developed. The data of the input and output of the system is measured and the models of the energy recovery ventilator (ERV), air handling unit (AHU), buffer tank (BT), radiant floor heating (RFH) and ground source heat pump (GSHP) are developed using the system identification techniques in Matlab®. The developed models include models based on multiple-input and multiple-output (MIMO) artificial neural network (ANN), transfer function (TF), process, state-space (SS) and autoregressive exogenous (ARX) onesof each HVAC subsystem (ERV, AHU, BT and RFH). The grey-box models of the same HVAC subsystems were developed in [1] which are also compared with the black-box models developed in this paper. The models were compared visually and analytically. Ranks of the models were calculated based on their relative performance. It was found that the ANN outperforms the other modeling methods followed by the ARX, TF, SS, process and grey-box models respectively.
In this paper the study and experiments into loudspeaker arrays for the purpose of sound focusing... more In this paper the study and experiments into loudspeaker arrays for the purpose of sound focusing are presented. The basics of the sound focusing are presented in the form of the beamforming and the acoustic control algorithms are discussed in order to describe the different methods used to focus sound in a desired region. Focusing of sound is not an easy job as it has lots of variables to control e.g. size and shape of the target zone, loudspeaker elements, and array, frequency range of interest, gaps b/w sources, amplitude difference b/w hot and cold zone, and control algorithm etc. We discuss these aspects in this paper in order to optimize the hardware and software cost involved in the design of the loudspeaker arrays. The acoustic environment in which the array has to be installed is also of the interest as the economy, convenience, power handling capacity, size and shape constraints arise from that. Smaller arenas such as installations into cars or even smaller ones such as implementation into mobile phones, portable media players, and notebook computers present even higher challenge to the designer for compactness, robustness and durability. Starting from the very basic type of line arrays, different configurations of arc and circular arrays are simulated. The methods are verified through the comparison with the professional software results. The experiments are performed in order to show the validity of simulated results. The conducted experiments contain the measurements of pressure fields and directivity under the influence of different control variables encountered in sound focusing.
The residential HVAC systems in Canada can consume more than 60% of the total energy in a house w... more The residential HVAC systems in Canada can consume more than 60% of the total energy in a house which results in higher operating costs and environmental pollution. The HVAC is a complex system with variable loads acting on it due to the changes in weather and occupancy. The energy consumption of the HVAC systems can be reduced by adapting to the ever changing loads and implementation of energy conservation strategies along with the appropriate control design. Most of the existing HVAC systems use simple on/off controllers and lack any supervisory controller to reduce the energy consumption and operating cost of the system. In Ontario, due to the variable price of electricity, there is an opportunity to design intelligent control system which can shift the loads to off-peak hours and reduce the operating cost of the HVAC system. In order to take advantage of this opportunity, a supervisory controller based on model predictive control (MPC) was designed in this research. The residential HVAC system models were developed and accurately calibrated with the data measured from the Toronto and Region Conservation Authority’s Archetype Sustainable House, House B (TRCA-ASHB) located in Vaughan, Ontario, Canada. Since HVAC is a large and complex system, it was divided into its major subsystems called energy recovery ventilator (ERV), air handling unit (AHU), radiant floor heating (RFH) system, ground source heat pump (GSHP) and buffer tank (BT). The models of each of the subsystem were developed and calibrated individually. The models were then combined together to develop the model of the whole residential HVAC system. The developed model is able to predict the temperature, flow rate, energy consumption and cost for each individual subsystem and whole HVAC system. The model was used to simulate the performance of the existing HVAC system with on/off controllers and develop the supervisory MPC. The supervisory controller was implemented on the HVAC system of TRCA-ASHB and at least 16% cost savings were verified.
Due to the power crisis in Pakistan there is a growing market of small household generators rangi... more Due to the power crisis in Pakistan there is a growing market of small household generators ranging from 2-3 KVA which can handle the load of a small house comprising of a few fans, lights, a computer and a TV. These generators are cheap and come equipped with a self-start mechanism built into the generator. On the push of a button, the user can start the generator easily. In the cities, normally these generators are used for a short period of time when the power from the grid is not available. When the power from the grid is not available the user starts the generator and connects the load to the generator manually. When the power from the grid becomes available, the user disconnects the generator from the load, turns off the generator and connects the load to the grid manually. Normally this function is performed manually and requires the engagement of the user for turning the generator on and off and shifting the load between the generator and the grid. In this paper we propose a...
In this paper, a comprehensive review of the artificial neural network (ANN) based model predicti... more In this paper, a comprehensive review of the artificial neural network (ANN) based model predictive control (MPC) system design is carried out followed by a case study in which ANN models of a residential house located in Ontario, Canada are developed and calibrated with the data measured from site. A new algorithm called best network after multiple iterations (BNMI) is introduced to help in determining the appropriate ANN architecture. The prediction performance of the developed models using BNMI algorithm was significantly better (between 6% and 59% better goodness of fit for various models) when compared to a previous study carried out by the authors which used the default single iteration ANN training algorithm of MATLAB ®. The ANN models were further used to design the supervisory MPC for the residential HVAC system. The MPC generated the dynamic temperature set-point profiles of the zone air and buffer tank water which resulted in the operating cost reduction of the equipment without violating the thermal comfort constraints. When compared to the fixed set-point (FSP), MPC was able to save operating cost between 6% and 73% depending on the season.
Residential heating, ventilation and air conditioning (HVAC) systems generally employ simple on/o... more Residential heating, ventilation and air conditioning (HVAC) systems generally employ simple on/off controllers to regulate the temperature of water and air in different subsystems. Selection of set-point of a controlled process and dead-band of controller affects the process regulation, energy consumption and actuator switching frequency. This article presents a calibrated model of a residential HVAC system. Temperature of two zones and buffer tank (BT) is regulated using on/off controllers. Non optimum controller settings result in poor regulation, higher energy consumption and higher equipment wear. The purpose of this article is to find optimum set-point and dead-band settings for on/off controllers in order to improve temperature regulation, reduce energy consumption and decrease equipment wear by reducing the switching frequency of HVAC equipment without scarifying thermal comfort of occupants.
Due to the increasing cost of electricity and its variable price structure throughout the day, it... more Due to the increasing cost of electricity and its variable price structure throughout the day, it is of interest to shift the loads to off-peak hours. In this work, the grey-box model of a domestic hot water electric boiler is presented. The developed model is useful for the development of new supervisory controller to help offset the boiler heating load to off peak hours in a smart grid environment. The boiler used in this research is an integral part of the domestic hot water system and residential Heating, Ventilating and Air-Conditioning (HVAC) systems in many Swiss homes. The water stored in the boiler is not well mixed and thus the temperature varies along the height of the boiler. The cold water is entering in the boiler from the bottom and the hot water is drawn at the top. This results in a temperature gradient along the height of the boiler which needs to be predicted to accurately simulate the temperature dynamics of the boiler. The boiler was divided into eight stratified virtual layers and physics-based model was developed by writing the heat balance equation for each layer. Experimental setup consisting of boiler, sensors and data logger was prepared at the Institute of Aerosol and Sensor Technology (IAST), University of Applied Sciences and Arts Northwestern Switzerland (FHNW) to measure the training and test data for the model including the temperature of each layer, ambient temperature, boiler's power consumption and flow rate of water entering into the boiler. The parameters of the physics-based model were estimated from the measured data thus converting it into a grey-box model. The model performance was visually compared to the measured data and was also evaluated analytically using several metrics showing the high accuracy of the developed model.
In this paper, black-box models of the residential heating, ventilation and air conditioning (HVA... more In this paper, black-box models of the residential heating, ventilation and air conditioning (HVAC) system are developed. The data of the input and output of the system is measured and the models of the energy recovery ventilator (ERV), air handling unit (AHU), buffer tank (BT), radiant floor heating (RFH) and ground source heat pump (GSHP) are developed using the system identification techniques in Matlab®. The developed models include models based on multiple-input and multiple-output (MIMO) artificial neural network (ANN), transfer function (TF), process, state-space (SS) and autoregressive exogenous (ARX) onesof each HVAC subsystem (ERV, AHU, BT and RFH). The grey-box models of the same HVAC subsystems were developed in [1] which are also compared with the black-box models developed in this paper. The models were compared visually and analytically. Ranks of the models were calculated based on their relative performance. It was found that the ANN outperforms the other modeling methods followed by the ARX, TF, SS, process and grey-box models respectively.
In this paper the study and experiments into loudspeaker arrays for the purpose of sound focusing... more In this paper the study and experiments into loudspeaker arrays for the purpose of sound focusing are presented. The basics of the sound focusing are presented in the form of the beamforming and the acoustic control algorithms are discussed in order to describe the different methods used to focus sound in a desired region. Focusing of sound is not an easy job as it has lots of variables to control e.g. size and shape of the target zone, loudspeaker elements, and array, frequency range of interest, gaps b/w sources, amplitude difference b/w hot and cold zone, and control algorithm etc. We discuss these aspects in this paper in order to optimize the hardware and software cost involved in the design of the loudspeaker arrays. The acoustic environment in which the array has to be installed is also of the interest as the economy, convenience, power handling capacity, size and shape constraints arise from that. Smaller arenas such as installations into cars or even smaller ones such as implementation into mobile phones, portable media players, and notebook computers present even higher challenge to the designer for compactness, robustness and durability. Starting from the very basic type of line arrays, different configurations of arc and circular arrays are simulated. The methods are verified through the comparison with the professional software results. The experiments are performed in order to show the validity of simulated results. The conducted experiments contain the measurements of pressure fields and directivity under the influence of different control variables encountered in sound focusing.
The residential HVAC systems in Canada can consume more than 60% of the total energy in a house w... more The residential HVAC systems in Canada can consume more than 60% of the total energy in a house which results in higher operating costs and environmental pollution. The HVAC is a complex system with variable loads acting on it due to the changes in weather and occupancy. The energy consumption of the HVAC systems can be reduced by adapting to the ever changing loads and implementation of energy conservation strategies along with the appropriate control design. Most of the existing HVAC systems use simple on/off controllers and lack any supervisory controller to reduce the energy consumption and operating cost of the system. In Ontario, due to the variable price of electricity, there is an opportunity to design intelligent control system which can shift the loads to off-peak hours and reduce the operating cost of the HVAC system. In order to take advantage of this opportunity, a supervisory controller based on model predictive control (MPC) was designed in this research. The residential HVAC system models were developed and accurately calibrated with the data measured from the Toronto and Region Conservation Authority’s Archetype Sustainable House, House B (TRCA-ASHB) located in Vaughan, Ontario, Canada. Since HVAC is a large and complex system, it was divided into its major subsystems called energy recovery ventilator (ERV), air handling unit (AHU), radiant floor heating (RFH) system, ground source heat pump (GSHP) and buffer tank (BT). The models of each of the subsystem were developed and calibrated individually. The models were then combined together to develop the model of the whole residential HVAC system. The developed model is able to predict the temperature, flow rate, energy consumption and cost for each individual subsystem and whole HVAC system. The model was used to simulate the performance of the existing HVAC system with on/off controllers and develop the supervisory MPC. The supervisory controller was implemented on the HVAC system of TRCA-ASHB and at least 16% cost savings were verified.
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Focusing of sound is not an easy job as it has lots of variables to control e.g. size and shape of the target zone, loudspeaker elements, and array, frequency range of interest, gaps b/w sources, amplitude difference b/w hot and cold zone, and control algorithm etc. We discuss these aspects in this paper in order to optimize the hardware and software cost involved in the design of the loudspeaker arrays. The acoustic environment in which the array has to be installed is also of the interest as the economy, convenience, power handling capacity, size and shape constraints arise from that. Smaller arenas such as installations into cars or even smaller ones such as implementation into mobile phones, portable media players, and notebook computers present even higher challenge to the designer for compactness, robustness and durability.
Starting from the very basic type of line arrays, different configurations of arc and circular arrays are simulated. The methods are verified through the comparison with the professional software results. The experiments are performed in order to show the validity of simulated results. The conducted experiments contain the measurements of pressure fields and directivity under the influence of different control variables encountered in sound focusing.
Most of the existing HVAC systems use simple on/off controllers and lack any supervisory controller to reduce the energy consumption and operating cost of the system. In Ontario, due to the variable price of electricity, there is an opportunity to design intelligent control system which can shift the loads to off-peak hours and reduce the operating cost of the HVAC system. In order to take advantage of this opportunity, a supervisory controller based on model predictive control (MPC) was designed in this research. The residential HVAC system models were developed and accurately calibrated with the data measured from the Toronto and Region Conservation Authority’s Archetype Sustainable House, House B (TRCA-ASHB) located in Vaughan, Ontario, Canada. Since HVAC is a large and complex system, it was divided into its major subsystems called energy recovery ventilator (ERV), air handling unit (AHU), radiant floor heating (RFH) system, ground source heat pump (GSHP) and buffer tank (BT). The models of each of the subsystem were developed and calibrated individually. The models were then combined together to develop the model of the whole residential HVAC system. The developed model is able to predict the temperature, flow rate, energy consumption and cost for each individual subsystem and whole HVAC system. The model was used to simulate the performance of the existing HVAC system with on/off controllers and develop the supervisory MPC. The supervisory controller was implemented on the HVAC system of TRCA-ASHB and at least 16% cost savings were verified.
Focusing of sound is not an easy job as it has lots of variables to control e.g. size and shape of the target zone, loudspeaker elements, and array, frequency range of interest, gaps b/w sources, amplitude difference b/w hot and cold zone, and control algorithm etc. We discuss these aspects in this paper in order to optimize the hardware and software cost involved in the design of the loudspeaker arrays. The acoustic environment in which the array has to be installed is also of the interest as the economy, convenience, power handling capacity, size and shape constraints arise from that. Smaller arenas such as installations into cars or even smaller ones such as implementation into mobile phones, portable media players, and notebook computers present even higher challenge to the designer for compactness, robustness and durability.
Starting from the very basic type of line arrays, different configurations of arc and circular arrays are simulated. The methods are verified through the comparison with the professional software results. The experiments are performed in order to show the validity of simulated results. The conducted experiments contain the measurements of pressure fields and directivity under the influence of different control variables encountered in sound focusing.
Most of the existing HVAC systems use simple on/off controllers and lack any supervisory controller to reduce the energy consumption and operating cost of the system. In Ontario, due to the variable price of electricity, there is an opportunity to design intelligent control system which can shift the loads to off-peak hours and reduce the operating cost of the HVAC system. In order to take advantage of this opportunity, a supervisory controller based on model predictive control (MPC) was designed in this research. The residential HVAC system models were developed and accurately calibrated with the data measured from the Toronto and Region Conservation Authority’s Archetype Sustainable House, House B (TRCA-ASHB) located in Vaughan, Ontario, Canada. Since HVAC is a large and complex system, it was divided into its major subsystems called energy recovery ventilator (ERV), air handling unit (AHU), radiant floor heating (RFH) system, ground source heat pump (GSHP) and buffer tank (BT). The models of each of the subsystem were developed and calibrated individually. The models were then combined together to develop the model of the whole residential HVAC system. The developed model is able to predict the temperature, flow rate, energy consumption and cost for each individual subsystem and whole HVAC system. The model was used to simulate the performance of the existing HVAC system with on/off controllers and develop the supervisory MPC. The supervisory controller was implemented on the HVAC system of TRCA-ASHB and at least 16% cost savings were verified.