The Experts below are selected from a list of 40911 Experts worldwide ranked by ideXlab platform
N. Khan - One of the best experts on this subject based on the ideXlab platform.
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Comparative study of Hvac and HVDC transmission systems
Renewable and Sustainable Energy Reviews, 2016Co-Authors: Anam Kalair, Naeem Abas, N. KhanAbstract:Transport of energy over long distances from remote natural sources to consumers in big cities requires technical, economic and environmental considerations. Uncertain wind flow, sunshine, faults and communication failures can compromise system safety, reliability, power quality during small signal and large scale power system oscillations. Hvac systems tackle power swing issue by electrical islanding protection schemes which would need to be revised for integrated AC/DC systems. Advent of DC transformers, CSC-HVDC, VSC-HVDC and MMC-HVDC technologies have enabled the enhancement of power delivery and integration of renewable energy sources under smart grid vision. HVDC transmission lines are recognized as an efficient alternative to Hvac lines. Hvac system power transfer capability is limited by reactance, whereas HVDC lines can be loaded up to the conductor thermal limit. This paper reviews power transfer capabilities of Hvac, HVDC and High Phase Order (HPO) Hvac lines to compare their relative performance under diverse conditions. Techno-economic analysis of converting existing AC lines into DC lines is presented. High voltage race has been analyzed in context of environmental concerns and HVDC transmission systems are concluded to be the right path to energy transition.
Qian Chen - One of the best experts on this subject based on the ideXlab platform.
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An RC-Network Approach for Hvac Precooling Optimization in Buildings
IEEE Transactions on Sustainable Computing, 2019Co-Authors: Hongsen Shi, Jia Liu, Qian ChenAbstract:To lower buildings' significant energy consumption and high impacts on environmental sustainability, recent years have witnessed rapidly growing interests in efficient Hvac precooling control and optimization. However, due to the complex analytical modeling of building thermal transfer, rigorous mathematical optimization for Hvac precooling is highly challenging. As a result, progress on Hvac precooling optimization remains limited in the literature. Our main contribution is that we overcome the aforementioned challenge and propose an accurate and tractable Hvac precooling optimization framework. The main results of this paper are three-fold: i) We develop an RC-network-based analytical model for multi-zone Hvac precooling to minimize both total energy costs and peak load demand; ii) We show that the Hvac procooling optimization problem based on the proposed RC network model admits a convex approximation, which enables an efficient optimization algorithm design; and iii) Based on the convex approximation insight and by exploiting special problem structures, we develop an efficient distributed algorithm to solve the Hvac precooling optimization problem. Further, we conduct extensive simulation studies to verify the performance of our proposed mathematical model and algorithms. Our numerical results indicate that compared with the five existing Hvac control strategies, the proposed algorithm consistently outperforms existing state-of-the-art approaches.
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e-Energy - Hvac Precooling Optimization for Green Buildings: An RC-Network Approach
Proceedings of the Ninth International Conference on Future Energy Systems, 2018Co-Authors: Hongsen Shi, Jia Liu, Qian ChenAbstract:To lower buildings' significant energy consumption and high impacts on environmental sustainability, recent years have witnessed rapidly growing interests in efficient Hvac precooling control and optimization. However, due to the complex analytical modeling of building thermal transfer, rigorous mathematical optimization for Hvac precooling is highly challenging. As a result, progress on Hvac precooling optimization remains rather limited in the literature. Our main contribution in this paper is that we overcome the aforementioned challenge and propose an accurate and tractable mathematical Hvac precooling optimization framework. The main results of this paper are three-fold: i) We develop an RC-network-based analytical model for multi-zone Hvac precooling to minimize both total energy costs and peak load demand; ii) We show that the Hvac procooling optimization problem based on the proposed RC network model admits a convex approximation, which enables efficient optimization algorithm design; and iii) Based on the convex approximation insight and by exploiting special problem structures, we develop an efficient distributed algorithm to solve the Hvac precooling optimization problem. Further, we conduct extensive simulation studies to verify the performance of our proposed mathematical model and algorithms. Our numerical results indicate that the proposed optimization algorithm consistently achieves energy cost reduction ranging from 30% to 60%.
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Hvac precooling optimization for green buildings an rc network approach
International Conference on Future Energy Systems, 2018Co-Authors: Hongsen Shi, Jia Liu, Qian ChenAbstract:To lower buildings' significant energy consumption and high impacts on environmental sustainability, recent years have witnessed rapidly growing interests in efficient Hvac precooling control and optimization. However, due to the complex analytical modeling of building thermal transfer, rigorous mathematical optimization for Hvac precooling is highly challenging. As a result, progress on Hvac precooling optimization remains rather limited in the literature. Our main contribution in this paper is that we overcome the aforementioned challenge and propose an accurate and tractable mathematical Hvac precooling optimization framework. The main results of this paper are three-fold: i) We develop an RC-network-based analytical model for multi-zone Hvac precooling to minimize both total energy costs and peak load demand; ii) We show that the Hvac procooling optimization problem based on the proposed RC network model admits a convex approximation, which enables efficient optimization algorithm design; and iii) Based on the convex approximation insight and by exploiting special problem structures, we develop an efficient distributed algorithm to solve the Hvac precooling optimization problem. Further, we conduct extensive simulation studies to verify the performance of our proposed mathematical model and algorithms. Our numerical results indicate that the proposed optimization algorithm consistently achieves energy cost reduction ranging from 30% to 60%.
Anam Kalair - One of the best experts on this subject based on the ideXlab platform.
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Comparative study of Hvac and HVDC transmission systems
Renewable and Sustainable Energy Reviews, 2016Co-Authors: Anam Kalair, Naeem Abas, N. KhanAbstract:Transport of energy over long distances from remote natural sources to consumers in big cities requires technical, economic and environmental considerations. Uncertain wind flow, sunshine, faults and communication failures can compromise system safety, reliability, power quality during small signal and large scale power system oscillations. Hvac systems tackle power swing issue by electrical islanding protection schemes which would need to be revised for integrated AC/DC systems. Advent of DC transformers, CSC-HVDC, VSC-HVDC and MMC-HVDC technologies have enabled the enhancement of power delivery and integration of renewable energy sources under smart grid vision. HVDC transmission lines are recognized as an efficient alternative to Hvac lines. Hvac system power transfer capability is limited by reactance, whereas HVDC lines can be loaded up to the conductor thermal limit. This paper reviews power transfer capabilities of Hvac, HVDC and High Phase Order (HPO) Hvac lines to compare their relative performance under diverse conditions. Techno-economic analysis of converting existing AC lines into DC lines is presented. High voltage race has been analyzed in context of environmental concerns and HVDC transmission systems are concluded to be the right path to energy transition.
Michael Orosz - One of the best experts on this subject based on the ideXlab platform.
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user led decentralized thermal comfort driven Hvac operations for improved efficiency in office buildings
Energy and Buildings, 2014Co-Authors: Farrokh Jazizadeh, Tatiana Kichkaylo, Ali Ghahramani, Burcin Becerikgerber, Michael OroszAbstract:Abstract Thermal comfort is one of the main driving factors in defining the operational settings of Hvac systems, and it greatly impacts energy efficiency in buildings. Lack of information about human related variables results in using unrepresentative operational settings, which in turn could bring about low efficiency in Hvac operations. In this paper, the implementation and evaluation of a framework that integrates building occupants’ personalized thermal profiles into the Hvac control logic is presented. The framework enables occupants to communicate their preferences for indoor thermal conditions through a user interface, leveraging a participatory sensing approach. The framework learns occupants’ comfort profiles, using a fuzzy predictive model, and controls the Hvac system using a complementary control strategy, which enables the framework to be implemented in existing centrally controlled Hvac systems with minimum intrusion. Evaluation of the framework in a real building setting showed user comfort improvement. Moreover, the results showed a 39% reduction in daily average airflow when the Hvac system conditions the rooms at occupants’ desired temperatures. Airflow is proportional to the energy consumption of Hvac system components. Consequently, the implementation of the framework shows improvements in the efficiency of the Hvac system's performance for centrally controlled office buildings.
Burcin Becerikgerber - One of the best experts on this subject based on the ideXlab platform.
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the coupled effects of personalized occupancy profile based Hvac schedules and room reassignment on building energy use
Energy and Buildings, 2014Co-Authors: Zheng Yang, Burcin BecerikgerberAbstract:Abstract Buildings account for nearly 38% of the total energy use in the U.S., and 46% of this use is associated with commercial buildings. More than 40% of the energy in commercial buildings is consumed by Hvac systems, which provide heating, cooling and ventilation to individual zones to maintain comfortable and healthy indoor environments. A more refined control strategy based on actual occupancy might improve Hvac system related energy efficiency. Accurate occupancy profiles are important to determine actual energy demands and corresponding control schedules. This paper focuses on energy efficiency in office buildings with centrally controlled VAV systems by setting zone-level Hvac start/stop schedules using personalized occupancy profiles, which represent occupants’ long-term presence patterns. Evaluation of the method was performed using a simulation model, calibrated by the actual energy use data of an office test bed building. Up to 9% of the energy was saved when personalized occupancy profile based Hvac schedules were used. However, if occupants of a zone have different occupancy patterns, the aggregated patterns may hinder any potential efficiency that might be realized from zone-level Hvac start/stop schedules. This paper also presents an approach for reassigning rooms to unify the start/stop times at the zone level by placing occupants with similar profiles in the same mechanical zones. When room reassignment was implemented and coupled with profile based control schedule, Hvac energy use was reduced by another 8%. The proposed methods could provide reliable personalized Hvac control for small-size office buildings without advanced building automation systems, nevertheless, they could also be extended to buildings with packaged Hvac systems and individual air-conditioning systems.
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user led decentralized thermal comfort driven Hvac operations for improved efficiency in office buildings
Energy and Buildings, 2014Co-Authors: Farrokh Jazizadeh, Tatiana Kichkaylo, Ali Ghahramani, Burcin Becerikgerber, Michael OroszAbstract:Abstract Thermal comfort is one of the main driving factors in defining the operational settings of Hvac systems, and it greatly impacts energy efficiency in buildings. Lack of information about human related variables results in using unrepresentative operational settings, which in turn could bring about low efficiency in Hvac operations. In this paper, the implementation and evaluation of a framework that integrates building occupants’ personalized thermal profiles into the Hvac control logic is presented. The framework enables occupants to communicate their preferences for indoor thermal conditions through a user interface, leveraging a participatory sensing approach. The framework learns occupants’ comfort profiles, using a fuzzy predictive model, and controls the Hvac system using a complementary control strategy, which enables the framework to be implemented in existing centrally controlled Hvac systems with minimum intrusion. Evaluation of the framework in a real building setting showed user comfort improvement. Moreover, the results showed a 39% reduction in daily average airflow when the Hvac system conditions the rooms at occupants’ desired temperatures. Airflow is proportional to the energy consumption of Hvac system components. Consequently, the implementation of the framework shows improvements in the efficiency of the Hvac system's performance for centrally controlled office buildings.
