The Experts below are selected from a list of 550032 Experts worldwide ranked by ideXlab platform
Tamer Basar - One of the best experts on this subject based on the ideXlab platform.
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dynamic power distribution system management with a locally connected Communication Network
IEEE Journal of Selected Topics in Signal Processing, 2018Co-Authors: Kaiqing Zhang, Wei Shi, Hao Zhu, Emiliano Dallanese, Tamer BasarAbstract:Coordinated optimization and control of distribution-level assets enables a reliable and optimal integration of massive amount of distributed energy resources (DERs) and facilitates distribution system management (DSM). Accordingly, the objective is to coordinate the power injection at the DERs to maintain certain quantities across the Network, e.g., voltage magnitude, line flows, and line losses, to be close to a desired profile. By and large, the performance of the DSM algorithms has been challenged by two factors: 1) the possibly nonstrongly connected Communication Network over DERs that hinders the coordination; and 2) the dynamics of the real system caused by the DERs with heterogeneous capabilities, time-varying operating conditions, and real-time measurement mismatches. In this paper, we investigate the modeling and algorithm design and analysis with the consideration of these two factors. In particular, a game-theoretic characterization is first proposed to account for a locally connected Communication Network over DERs, along with the analysis of the existence and uniqueness of the Nash equilibrium therein. To achieve the equilibrium in a distributed fashion, a projected-gradient -based asynchronous DSM algorithm is then advocated. The algorithm performance, including the convergence speed and the tracking error, is analytically guaranteed under the dynamic setting. Extensive numerical tests on both synthetic and realistic cases corroborate the analytical results derived.
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distributed equilibrium learning for power Network voltage control with a locally connected Communication Network
Advances in Computing and Communications, 2018Co-Authors: Kaiqing Zhang, Wei Shi, Hao Zhu, Tamer BasarAbstract:We address the problem of voltage control in power distribution Networks by coordinating the distributed energy resources (DERs) at different buses. This problem has been investigated actively via either distributed optimization-based or local feedback control-based approaches. The former one requires a strongly-connected Communication Network among all DERs for implementing the optimization algorithms, which is not yet realistic in existing distribution systems with under-deployed Communication infrastructure. The latter one, on the other hand, has been proven to suffer from loss of Network-wide operational optimality. In this paper, we propose a game-theoretic characterization for semi-local voltage control with only a locally connected Communication Network. We analyze the existence and uniqueness of the generalized Nash equilibrium (GNE) for this characterization, and develop a fully distributed equilibrium-learning algorithm that hinges on only neighbor-to-neighbor information exchange of DERs. Provable convergence results are provided along with numerical tests, to illustrate the robust convergence property of our algorithm.
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distributed equilibrium learning for power Network voltage control with a locally connected Communication Network
arXiv: Systems and Control, 2018Co-Authors: Kaiqing Zhang, Wei Shi, Hao Zhu, Tamer BasarAbstract:In current power distribution systems, one of the most challenging operation tasks is to coordinate the Network- wide distributed energy resources (DERs) to maintain the stability of voltage magnitude of the system. This voltage control task has been investigated actively under either distributed optimization-based or local feedback control-based characterizations. The former architecture requires a strongly-connected Communication Network among all DERs for implementing the optimization algorithms, a scenario not yet realistic in most of the existing distribution systems with under-deployed Communication infrastructure. The latter one, on the other hand, has been proven to suffer from loss of Network-wide op- erational optimality. In this paper, we propose a game-theoretic characterization for semi-local voltage control with only a locally connected Communication Network. We analyze the existence and uniqueness of the generalized Nash equilibrium (GNE) for this characterization and develop a fully distributed equilibrium-learning algorithm that relies on only neighbor-to-neighbor information exchange. Provable convergence results are provided along with numerical tests which corroborate the robust convergence property of the proposed algorithm.
Naveed Aqdas - One of the best experts on this subject based on the ideXlab platform.
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Cognitive radio based Smart Grid Communication Network
Renewable and Sustainable Energy Reviews, 2017Co-Authors: Sheraz Alam, M. Farhan Sohail, Sajjad Ahmed Ghauri, Ijaz Mansoor Qureshi, Naveed AqdasAbstract:Smart Grid (SG) is an evolution of conventional electricity grid, answering to the problems like electricity shortages, escalation in electricity prices, power quality issues and need for using environment friendly green energy resources. Key to attain this is design and deployment of a Smart Grid Communication Network (SGCN) that is not only reliable and secure but also fulfills the Communication requirements. The purpose of this research article is to provide a detailed survey on SGCN in terms of Communication Network requirements, architecture, technologies and applications. Using a multi-layer approach of dividing the Communication layer in to Home Area Network (HAN), Neighborhood Area Network (NAN) and Wide Area Network (WAN), this paper first discusses the Communication requirements, followed by an overview of SG applications. Then a detailed comparison is given for current wired and wireless Communication technologies along with new standards/technologies like Cognitive Radio (CR), Smart Utility Networks (SUNs) and TV White Spaces (TVWS) that are ideal for SG environment, followed by proposed CR based Network architecture for SGCN and its salient features. The paper is then concluded by contributing some open issues, challenges and future directions.
Kaiqing Zhang - One of the best experts on this subject based on the ideXlab platform.
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dynamic power distribution system management with a locally connected Communication Network
IEEE Journal of Selected Topics in Signal Processing, 2018Co-Authors: Kaiqing Zhang, Wei Shi, Hao Zhu, Emiliano Dallanese, Tamer BasarAbstract:Coordinated optimization and control of distribution-level assets enables a reliable and optimal integration of massive amount of distributed energy resources (DERs) and facilitates distribution system management (DSM). Accordingly, the objective is to coordinate the power injection at the DERs to maintain certain quantities across the Network, e.g., voltage magnitude, line flows, and line losses, to be close to a desired profile. By and large, the performance of the DSM algorithms has been challenged by two factors: 1) the possibly nonstrongly connected Communication Network over DERs that hinders the coordination; and 2) the dynamics of the real system caused by the DERs with heterogeneous capabilities, time-varying operating conditions, and real-time measurement mismatches. In this paper, we investigate the modeling and algorithm design and analysis with the consideration of these two factors. In particular, a game-theoretic characterization is first proposed to account for a locally connected Communication Network over DERs, along with the analysis of the existence and uniqueness of the Nash equilibrium therein. To achieve the equilibrium in a distributed fashion, a projected-gradient -based asynchronous DSM algorithm is then advocated. The algorithm performance, including the convergence speed and the tracking error, is analytically guaranteed under the dynamic setting. Extensive numerical tests on both synthetic and realistic cases corroborate the analytical results derived.
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distributed equilibrium learning for power Network voltage control with a locally connected Communication Network
Advances in Computing and Communications, 2018Co-Authors: Kaiqing Zhang, Wei Shi, Hao Zhu, Tamer BasarAbstract:We address the problem of voltage control in power distribution Networks by coordinating the distributed energy resources (DERs) at different buses. This problem has been investigated actively via either distributed optimization-based or local feedback control-based approaches. The former one requires a strongly-connected Communication Network among all DERs for implementing the optimization algorithms, which is not yet realistic in existing distribution systems with under-deployed Communication infrastructure. The latter one, on the other hand, has been proven to suffer from loss of Network-wide operational optimality. In this paper, we propose a game-theoretic characterization for semi-local voltage control with only a locally connected Communication Network. We analyze the existence and uniqueness of the generalized Nash equilibrium (GNE) for this characterization, and develop a fully distributed equilibrium-learning algorithm that hinges on only neighbor-to-neighbor information exchange of DERs. Provable convergence results are provided along with numerical tests, to illustrate the robust convergence property of our algorithm.
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distributed equilibrium learning for power Network voltage control with a locally connected Communication Network
arXiv: Systems and Control, 2018Co-Authors: Kaiqing Zhang, Wei Shi, Hao Zhu, Tamer BasarAbstract:In current power distribution systems, one of the most challenging operation tasks is to coordinate the Network- wide distributed energy resources (DERs) to maintain the stability of voltage magnitude of the system. This voltage control task has been investigated actively under either distributed optimization-based or local feedback control-based characterizations. The former architecture requires a strongly-connected Communication Network among all DERs for implementing the optimization algorithms, a scenario not yet realistic in most of the existing distribution systems with under-deployed Communication infrastructure. The latter one, on the other hand, has been proven to suffer from loss of Network-wide op- erational optimality. In this paper, we propose a game-theoretic characterization for semi-local voltage control with only a locally connected Communication Network. We analyze the existence and uniqueness of the generalized Nash equilibrium (GNE) for this characterization and develop a fully distributed equilibrium-learning algorithm that relies on only neighbor-to-neighbor information exchange. Provable convergence results are provided along with numerical tests which corroborate the robust convergence property of the proposed algorithm.
Yujian Chao - One of the best experts on this subject based on the ideXlab platform.
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reliability prediction of power Communication Network based on bp neural Network optimized by genetic algorithm
DEStech Transactions on Computer Science and Engineering, 2017Co-Authors: Jihai Yang, Xidan Peng, Yujian ChaoAbstract:The power Communication Network is a Communication Network which serves the power system. Its reliability has an important influence on the safe and stable operation of the power system. It is of great practical significance to study the reliability of the power Communication Network. However, the current research on the power Communication Network lag, the reliability of the quantitative measurement, in practice, mostly artificial evaluation of the business, subjective and arbitrariness. In order to achieve the transition from expert to data-driven, this paper is based on the business segment, with two sites and between a cable as a research object. Based on the construction of the index system, BP neural Network and genetic algorithm optimization BP neural Network prediction model are established respectively. Using the real data and simulation data of the national grid in Jiangxi Province, the empirical experiment is carried out to compare the effect of the model. The example shows the effectiveness of the model.
Wei Shi - One of the best experts on this subject based on the ideXlab platform.
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dynamic power distribution system management with a locally connected Communication Network
IEEE Journal of Selected Topics in Signal Processing, 2018Co-Authors: Kaiqing Zhang, Wei Shi, Hao Zhu, Emiliano Dallanese, Tamer BasarAbstract:Coordinated optimization and control of distribution-level assets enables a reliable and optimal integration of massive amount of distributed energy resources (DERs) and facilitates distribution system management (DSM). Accordingly, the objective is to coordinate the power injection at the DERs to maintain certain quantities across the Network, e.g., voltage magnitude, line flows, and line losses, to be close to a desired profile. By and large, the performance of the DSM algorithms has been challenged by two factors: 1) the possibly nonstrongly connected Communication Network over DERs that hinders the coordination; and 2) the dynamics of the real system caused by the DERs with heterogeneous capabilities, time-varying operating conditions, and real-time measurement mismatches. In this paper, we investigate the modeling and algorithm design and analysis with the consideration of these two factors. In particular, a game-theoretic characterization is first proposed to account for a locally connected Communication Network over DERs, along with the analysis of the existence and uniqueness of the Nash equilibrium therein. To achieve the equilibrium in a distributed fashion, a projected-gradient -based asynchronous DSM algorithm is then advocated. The algorithm performance, including the convergence speed and the tracking error, is analytically guaranteed under the dynamic setting. Extensive numerical tests on both synthetic and realistic cases corroborate the analytical results derived.
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distributed equilibrium learning for power Network voltage control with a locally connected Communication Network
Advances in Computing and Communications, 2018Co-Authors: Kaiqing Zhang, Wei Shi, Hao Zhu, Tamer BasarAbstract:We address the problem of voltage control in power distribution Networks by coordinating the distributed energy resources (DERs) at different buses. This problem has been investigated actively via either distributed optimization-based or local feedback control-based approaches. The former one requires a strongly-connected Communication Network among all DERs for implementing the optimization algorithms, which is not yet realistic in existing distribution systems with under-deployed Communication infrastructure. The latter one, on the other hand, has been proven to suffer from loss of Network-wide operational optimality. In this paper, we propose a game-theoretic characterization for semi-local voltage control with only a locally connected Communication Network. We analyze the existence and uniqueness of the generalized Nash equilibrium (GNE) for this characterization, and develop a fully distributed equilibrium-learning algorithm that hinges on only neighbor-to-neighbor information exchange of DERs. Provable convergence results are provided along with numerical tests, to illustrate the robust convergence property of our algorithm.
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distributed equilibrium learning for power Network voltage control with a locally connected Communication Network
arXiv: Systems and Control, 2018Co-Authors: Kaiqing Zhang, Wei Shi, Hao Zhu, Tamer BasarAbstract:In current power distribution systems, one of the most challenging operation tasks is to coordinate the Network- wide distributed energy resources (DERs) to maintain the stability of voltage magnitude of the system. This voltage control task has been investigated actively under either distributed optimization-based or local feedback control-based characterizations. The former architecture requires a strongly-connected Communication Network among all DERs for implementing the optimization algorithms, a scenario not yet realistic in most of the existing distribution systems with under-deployed Communication infrastructure. The latter one, on the other hand, has been proven to suffer from loss of Network-wide op- erational optimality. In this paper, we propose a game-theoretic characterization for semi-local voltage control with only a locally connected Communication Network. We analyze the existence and uniqueness of the generalized Nash equilibrium (GNE) for this characterization and develop a fully distributed equilibrium-learning algorithm that relies on only neighbor-to-neighbor information exchange. Provable convergence results are provided along with numerical tests which corroborate the robust convergence property of the proposed algorithm.
