The Experts below are selected from a list of 244791 Experts worldwide ranked by ideXlab platform
Liudong Xing - One of the best experts on this subject based on the ideXlab platform.
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cold vs hot standby mission Operation Cost minimization for 1 out of n systems
European Journal of Operational Research, 2014Co-Authors: Liudong Xing, Gregory LevitinAbstract:It is well recognized that using the hot standby redundancy provides fast restoration in the case of failures. However the redundant elements are exposed to working stresses before they are used, which reduces the overall system reliability. Moreover, the Cost of maintaining the hot redundant elements in the Operational state is usually much greater than the Cost of keeping them in the cold standby mode. Therefore, there exists a tradeoff between the Cost of losses associated with the restoration delays and the Operation Cost of standby elements. Such a trade-off can be obtained by designing both hot and cold redundancy types into the same system. Thus a new optimization problem arises for the standby system design. The problem, referred to in this work as optimal standby element distributing and sequencing problem (SE-DSP) is to distribute a fixed set of elements between cold and hot standby groups and select the element initiation sequence so as to minimize the expected mission Operation Cost of the system while providing a desired level of system reliability. This paper first formulates and solves the SE-DSP problem for 1-out-of-N: G heterogeneous non-repairable standby systems. A numerical method is proposed for evaluating the system reliability and expected mission Cost simultaneously. This method is based on discrete approximation of time-to-failure distributions of the system elements. A genetic algorithm is used as an optimization tool for solving the formulated optimization problem. Examples are given to illustrate the considered problem and the proposed solution methodology.
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cold vs hot standby mission Operation Cost minimization for 1 out of n systems
European Journal of Operational Research, 2014Co-Authors: Liudong Xing, Gregory LevitinAbstract:It is well recognized that using the hot standby redundancy provides fast restoration in the case of failures. However the redundant elements are exposed to working stresses before they are used, which reduces the overall system reliability. Moreover, the Cost of maintaining the hot redundant elements in the Operational state is usually much greater than the Cost of keeping them in the cold standby mode. Therefore, there exists a tradeoff between the Cost of losses associated with the restoration delays and the Operation Cost of standby elements. Such a trade-off can be obtained by designing both hot and cold redundancy types into the same system. Thus a new optimization problem arises for the standby system design. The problem, referred to in this work as optimal standby element distributing and sequencing problem (SE-DSP) is to distribute a fixed set of elements between cold and hot standby groups and select the element initiation sequence so as to minimize the expected mission Operation Cost of the system while providing a desired level of system reliability. This paper first formulates and solves the SE-DSP problem for 1-out-of-N: G heterogeneous non-repairable standby systems. A numerical method is proposed for evaluating the system reliability and expected mission Cost simultaneously. This method is based on discrete approximation of time-to-failure distributions of the system elements. A genetic algorithm is used as an optimization tool for solving the formulated optimization problem. Examples are given to illustrate the considered problem and the proposed solution methodology.
Gregory Levitin - One of the best experts on this subject based on the ideXlab platform.
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cold vs hot standby mission Operation Cost minimization for 1 out of n systems
European Journal of Operational Research, 2014Co-Authors: Liudong Xing, Gregory LevitinAbstract:It is well recognized that using the hot standby redundancy provides fast restoration in the case of failures. However the redundant elements are exposed to working stresses before they are used, which reduces the overall system reliability. Moreover, the Cost of maintaining the hot redundant elements in the Operational state is usually much greater than the Cost of keeping them in the cold standby mode. Therefore, there exists a tradeoff between the Cost of losses associated with the restoration delays and the Operation Cost of standby elements. Such a trade-off can be obtained by designing both hot and cold redundancy types into the same system. Thus a new optimization problem arises for the standby system design. The problem, referred to in this work as optimal standby element distributing and sequencing problem (SE-DSP) is to distribute a fixed set of elements between cold and hot standby groups and select the element initiation sequence so as to minimize the expected mission Operation Cost of the system while providing a desired level of system reliability. This paper first formulates and solves the SE-DSP problem for 1-out-of-N: G heterogeneous non-repairable standby systems. A numerical method is proposed for evaluating the system reliability and expected mission Cost simultaneously. This method is based on discrete approximation of time-to-failure distributions of the system elements. A genetic algorithm is used as an optimization tool for solving the formulated optimization problem. Examples are given to illustrate the considered problem and the proposed solution methodology.
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cold vs hot standby mission Operation Cost minimization for 1 out of n systems
European Journal of Operational Research, 2014Co-Authors: Liudong Xing, Gregory LevitinAbstract:It is well recognized that using the hot standby redundancy provides fast restoration in the case of failures. However the redundant elements are exposed to working stresses before they are used, which reduces the overall system reliability. Moreover, the Cost of maintaining the hot redundant elements in the Operational state is usually much greater than the Cost of keeping them in the cold standby mode. Therefore, there exists a tradeoff between the Cost of losses associated with the restoration delays and the Operation Cost of standby elements. Such a trade-off can be obtained by designing both hot and cold redundancy types into the same system. Thus a new optimization problem arises for the standby system design. The problem, referred to in this work as optimal standby element distributing and sequencing problem (SE-DSP) is to distribute a fixed set of elements between cold and hot standby groups and select the element initiation sequence so as to minimize the expected mission Operation Cost of the system while providing a desired level of system reliability. This paper first formulates and solves the SE-DSP problem for 1-out-of-N: G heterogeneous non-repairable standby systems. A numerical method is proposed for evaluating the system reliability and expected mission Cost simultaneously. This method is based on discrete approximation of time-to-failure distributions of the system elements. A genetic algorithm is used as an optimization tool for solving the formulated optimization problem. Examples are given to illustrate the considered problem and the proposed solution methodology.
Josep M. Guerrero - One of the best experts on this subject based on the ideXlab platform.
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Operation Cost Minimization of Droop-Controlled AC Microgrids Using Multiagent-Based Distributed Control
Energies, 2016Co-Authors: Mehdi Savaghebi, Josep M. Guerrero, Ernane Antônio Alves Coelho, Juan C. VasquezAbstract:Recently, microgrids are attracting increasing research interest as promising technologies to integrate renewable energy resources into the distribution system. Although many works have been done on droop control applied to microgrids, they mainly focus on achieving proportional power sharing based on the power rating of the power converters. With various primary source for the distributed generator (DG), factors that are closely related to the Operation Cost, such as fuel Cost of the generators and losses should be taken into account in order to improve the efficiency of the whole system. In this paper, a multiagent-based distributed method is proposed to minimize the Operation Cost in AC microgrids. In the microgrid, each DG is acting as an agent which regulates the power individually using a novel power regulation method based on frequency scheduling. An optimal power command is obtained through carefully designed consensus algorithm by using sparse communication links only among neighbouring agents. Experimental results for different cases verified that the proposed control strategy can effectively reduce the Operation Cost.
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convergence analysis of distributed control for Operation Cost minimization of droop controlled dc microgrid based on multiagent
Applied Power Electronics Conference, 2016Co-Authors: Juan C. Vasquez, Josep M. GuerreroAbstract:In this paper we present a distributed control method for minimizing the Operation Cost in DC microgrid based on multiagent system. Each agent is autonomous and controls the local converter in a hierarchical way through droop control, voltage scheduling and collective decision making. The collective decision for the whole system is made by proposed incremental Cost consensus, and only nearest-neighbor communication is needed. The convergence characteristics of the consensus algorithm are analyzed considering different communication topologies and control parameters. Case studies verified the proposed method by comparing it without traditional methods. The robustness of system is tested under different communication latency and plug and play Operation.
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Operation Cost minimization of droop controlled dc microgrids based on real time pricing and optimal power flow
Conference of the Industrial Electronics Society, 2015Co-Authors: Federico De Bosio, Juan C. Vasquez, Sanjay K Chaudhary, Moises Graells, Josep M. GuerreroAbstract:In this paper, an optimal power flow problem is formulated in order to minimize the total Operation Cost by considering real-time pricing in DC microgrids. Each generation resource in the system, including the utility grid, is modeled in terms of Operation Cost, which combines the Cost-efficiency of the system with the demand response requirements of the utility. By considering the primary (local) control of the grid-forming converters of a microgrid, optimal parameters can be directly applied to the control of this level, thus achieving higher control accuracy and faster response. The optimization problem is solved in a heuristic way by using genetic algorithms. In order to test the proposed algorithm, a six-bus droop-controlled DC microgrid is used as a case-study. The obtained simulation results show that under variable renewable generation, load, and electricity prices, the proposed method can successfully dispatch the resources in the microgrid with lower total Operation Costs.
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IECON - Multiagent-based distributed control for Operation Cost minimization of droop controlled DC microgrid using incremental Cost consensus
IECON 2015 - 41st Annual Conference of the IEEE Industrial Electronics Society, 2015Co-Authors: Juan C. Vasquez, Josep M. GuerreroAbstract:In this paper, a multiagent based distributed control is proposed for DC microgrid to minimize the Operation Cost. The power of each distributed generator (DG) is dispatched in a distributed manner in a multiagent system by means of voltage scheduling. Every DG unit is taken as an agent, and they share the load corresponding to the Operation Cost of all the units in the system with only communication with direct neighbors through incremental Cost consensus. The power regulation according to the power reference generated by consensus is implemented through voltage scheduling in local primary controllers. Simulation verification shows that total Operation Cost of the DC microgrid is successfully reduced though the proposed method.
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Multiagent based distributed control for Operation Cost minimization of droop controlled AC microgrid using incremental Cost consensus
2015 17th European Conference on Power Electronics and Applications (EPE'15 ECCE-Europe), 2015Co-Authors: Mehdi Savaghebi, Juan C. Vasquez, Josep M. GuerreroAbstract:Microgrid, as a promising technology to integrate renewable energy resources in the distribution system, is gaining increasing research interests recently. Although many previous works have been done based on the droop control in a microgrid, they mainly focus on achieving proportional power sharing based on the power rating. With various types of distributed generator (DG) units in the system, factors that closely related to the Operation Cost, such as fuel Cost and efficiencies of the generator should be taken into account in order to improve the efficiency of the whole system. In this paper, a multiagent based distributed method is proposed to minimize Operation Cost of the AC microgrid. Each DG is acting as an agent which regulates the power individually using proposed frequency scheduling method. Optimal power command is obtained through carefully designed consensus algorithm with only light communication between neighboring agents. Case studies verified that the proposed control strategy can effectively reduce the Operation Cost.
Xue Liu - One of the best experts on this subject based on the ideXlab platform.
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comprehensive understanding of Operation Cost reduction using energy storage for idcs
International Conference on Computer Communications, 2015Co-Authors: Haihang Zhou, Jianguo Yao, Haibing Guan, Xue LiuAbstract:To reduce the Operation Cost incurred by the rapidly growing energy consumption in internet data centers (IDCs), more and more internet service providers have spontaneously started using energy storage in various forms. The approach of energy storage is used to store cheap electricity energy when the electricity price from smart gird is low or the renewable energy is used. There are two typical forms of energy storage equipped in many IDCs, i.e., the battery storage and thermal energy storage. Recent work shows the energy storage can significantly reduce the Operation Cost for IDCs. However, the Cost of the energy storage devices are still at a high level, and it may increase the Operation Cost for IDCs. In this paper, we investigate the comprehensive understanding on the Operation Cost reduction for IDCs using the energy storage. To this end, we conduct a quantitative analysis on the normalized electricity price in the two energy storage forms. The experiments demonstrate that the Cost of the storage devices and renewable energy supply are largely affected by the storage capacity and the location of data centers, and we conclude that it does not always reduce Operation Cost using energy storage for IDCs.
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INFOCOM - Comprehensive understanding of Operation Cost reduction using energy storage for IDCs
2015 IEEE Conference on Computer Communications (INFOCOM), 2015Co-Authors: Zhou Haihang, Jianguo Yao, Haibing Guan, Xue LiuAbstract:To reduce the Operation Cost incurred by the rapidly growing energy consumption in internet data centers (IDCs), more and more internet service providers have spontaneously started using energy storage in various forms. The approach of energy storage is used to store cheap electricity energy when the electricity price from smart gird is low or the renewable energy is used. There are two typical forms of energy storage equipped in many IDCs, i.e., the battery storage and thermal energy storage. Recent work shows the energy storage can significantly reduce the Operation Cost for IDCs. However, the Cost of the energy storage devices are still at a high level, and it may increase the Operation Cost for IDCs. In this paper, we investigate the comprehensive understanding on the Operation Cost reduction for IDCs using the energy storage. To this end, we conduct a quantitative analysis on the normalized electricity price in the two energy storage forms. The experiments demonstrate that the Cost of the storage devices and renewable energy supply are largely affected by the storage capacity and the location of data centers, and we conclude that it does not always reduce Operation Cost using energy storage for IDCs.
Juan C. Vasquez - One of the best experts on this subject based on the ideXlab platform.
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Operation Cost Minimization of Droop-Controlled AC Microgrids Using Multiagent-Based Distributed Control
Energies, 2016Co-Authors: Mehdi Savaghebi, Josep M. Guerrero, Ernane Antônio Alves Coelho, Juan C. VasquezAbstract:Recently, microgrids are attracting increasing research interest as promising technologies to integrate renewable energy resources into the distribution system. Although many works have been done on droop control applied to microgrids, they mainly focus on achieving proportional power sharing based on the power rating of the power converters. With various primary source for the distributed generator (DG), factors that are closely related to the Operation Cost, such as fuel Cost of the generators and losses should be taken into account in order to improve the efficiency of the whole system. In this paper, a multiagent-based distributed method is proposed to minimize the Operation Cost in AC microgrids. In the microgrid, each DG is acting as an agent which regulates the power individually using a novel power regulation method based on frequency scheduling. An optimal power command is obtained through carefully designed consensus algorithm by using sparse communication links only among neighbouring agents. Experimental results for different cases verified that the proposed control strategy can effectively reduce the Operation Cost.
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convergence analysis of distributed control for Operation Cost minimization of droop controlled dc microgrid based on multiagent
Applied Power Electronics Conference, 2016Co-Authors: Juan C. Vasquez, Josep M. GuerreroAbstract:In this paper we present a distributed control method for minimizing the Operation Cost in DC microgrid based on multiagent system. Each agent is autonomous and controls the local converter in a hierarchical way through droop control, voltage scheduling and collective decision making. The collective decision for the whole system is made by proposed incremental Cost consensus, and only nearest-neighbor communication is needed. The convergence characteristics of the consensus algorithm are analyzed considering different communication topologies and control parameters. Case studies verified the proposed method by comparing it without traditional methods. The robustness of system is tested under different communication latency and plug and play Operation.
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Operation Cost minimization of droop controlled dc microgrids based on real time pricing and optimal power flow
Conference of the Industrial Electronics Society, 2015Co-Authors: Federico De Bosio, Juan C. Vasquez, Sanjay K Chaudhary, Moises Graells, Josep M. GuerreroAbstract:In this paper, an optimal power flow problem is formulated in order to minimize the total Operation Cost by considering real-time pricing in DC microgrids. Each generation resource in the system, including the utility grid, is modeled in terms of Operation Cost, which combines the Cost-efficiency of the system with the demand response requirements of the utility. By considering the primary (local) control of the grid-forming converters of a microgrid, optimal parameters can be directly applied to the control of this level, thus achieving higher control accuracy and faster response. The optimization problem is solved in a heuristic way by using genetic algorithms. In order to test the proposed algorithm, a six-bus droop-controlled DC microgrid is used as a case-study. The obtained simulation results show that under variable renewable generation, load, and electricity prices, the proposed method can successfully dispatch the resources in the microgrid with lower total Operation Costs.
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IECON - Multiagent-based distributed control for Operation Cost minimization of droop controlled DC microgrid using incremental Cost consensus
IECON 2015 - 41st Annual Conference of the IEEE Industrial Electronics Society, 2015Co-Authors: Juan C. Vasquez, Josep M. GuerreroAbstract:In this paper, a multiagent based distributed control is proposed for DC microgrid to minimize the Operation Cost. The power of each distributed generator (DG) is dispatched in a distributed manner in a multiagent system by means of voltage scheduling. Every DG unit is taken as an agent, and they share the load corresponding to the Operation Cost of all the units in the system with only communication with direct neighbors through incremental Cost consensus. The power regulation according to the power reference generated by consensus is implemented through voltage scheduling in local primary controllers. Simulation verification shows that total Operation Cost of the DC microgrid is successfully reduced though the proposed method.
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Multiagent based distributed control for Operation Cost minimization of droop controlled AC microgrid using incremental Cost consensus
2015 17th European Conference on Power Electronics and Applications (EPE'15 ECCE-Europe), 2015Co-Authors: Mehdi Savaghebi, Juan C. Vasquez, Josep M. GuerreroAbstract:Microgrid, as a promising technology to integrate renewable energy resources in the distribution system, is gaining increasing research interests recently. Although many previous works have been done based on the droop control in a microgrid, they mainly focus on achieving proportional power sharing based on the power rating. With various types of distributed generator (DG) units in the system, factors that closely related to the Operation Cost, such as fuel Cost and efficiencies of the generator should be taken into account in order to improve the efficiency of the whole system. In this paper, a multiagent based distributed method is proposed to minimize Operation Cost of the AC microgrid. Each DG is acting as an agent which regulates the power individually using proposed frequency scheduling method. Optimal power command is obtained through carefully designed consensus algorithm with only light communication between neighboring agents. Case studies verified that the proposed control strategy can effectively reduce the Operation Cost.
