The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform

Yan Zhang - One of the best experts on this subject based on the ideXlab platform.

  • Balancing Power Demand Through EV Mobility in Vehicle-to-Grid Mobile Energy Networks
    IEEE Transactions on Industrial Informatics, 2016
    Co-Authors: Rong Yu, Shengli Xie, Stein Gjessing, Weifeng Zhong, Chau Yuen, Yan Zhang
    Abstract:

    Vehicle-to-grid (V2G) technology enables bidirectional energy flow between electric vehicles (EVs) and power grid, which provides flexible demand Response Management (DRM) for the reliability of smart grid. EV mobility is a unique and inherent feature of the V2G system. However, the inter-relationship between EV mobility and DRM is not obvious. In this paper, we focus on the exploration of EV mobility to impact DRM in V2G systems in smart grid. We first present a dynamic complex network model of V2G mobile energy networks, considering the fact that EVs travel across multiple districts, and hence EVs can be acting as energy transporters among different districts. We formulate the districts' DRM dynamics, which is coupled with each other through EV fleets. In addition, a complex network synchronization method is proposed to analyze the dynamic behavior in V2G mobile energy networks. Numerical results show that EVs mobility of symmetrical EV fleet is able to achieve synchronous stability of network and balance the power demand among different districts. This observation is also validated by simulation with real world data.

  • demand Response Management in the smart grid in a large population regime
    IEEE Transactions on Smart Grid, 2016
    Co-Authors: Sabita Maharjan, Stein Gjessing, Quanyan Zhu, Yan Zhang, Tamer Başar
    Abstract:

    In this paper, we introduce a hierarchical system model that captures the decision making processes involved in a network of multiple providers and a large number of consumers in the smart grid, incorporating multiple processes from power generation to market activities and to power consumption. We establish a Stackelberg game between providers and end users, where the providers behave as leaders maximizing their profit and end users act as the followers maximizing their individual welfare. We obtain closed-form expressions for the Stackelberg equilibrium of the game and prove that a unique equilibrium solution exists. In the large population regime, we show that a higher number of providers help to improve profits for the providers. This is inline with the goal of facilitating multiple distributed power generation units, one of the main design considerations in the smart grid. We further prove that there exist a unique number of providers that maximize their profits, and develop an iterative and distributed algorithm to obtain it. Finally, we provide numerical examples to illustrate the solutions and to corroborate the results.

  • demand Response Management with multiple utility companies a two level game approach
    IEEE Transactions on Smart Grid, 2014
    Co-Authors: Bo Chai, Jiming Chen, Zaiyue Yang, Yan Zhang
    Abstract:

    Demand Response Management (DRM) is a key component of the future smart grid that helps to reduce power peak load and variation. Different from most existing studies that focus on the scenario with a single utility company, this paper studies DRM with multiple utility companies. First, the interaction between utility companies and residential users is modeled as a two-level game. That is, the competition among the utility companies is formulated as a non-cooperative game, while the interaction among the residential users is formulated as an evolutionary game. Then, we prove that the proposed strategies are able to make both games converge to their own equilibrium. In addtion, the strategies for the utility companies and the residential users are implemented by distributed algorithms. Illustrative examples show that the proposed scheme is able to significantly reduce peak load and demand variation.

  • dependable demand Response Management in the smart grid a stackelberg game approach
    IEEE Transactions on Smart Grid, 2013
    Co-Authors: Sabita Maharjan, Stein Gjessing, Quanyan Zhu, Yan Zhang, Tamer Başar
    Abstract:

    Demand Response Management (DRM) is a key component in the smart grid to effectively reduce power generation costs and user bills. However, it has been an open issue to address the DRM problem in a network of multiple utility companies and consumers where every entity is concerned about maximizing its own benefit. In this paper, we propose a Stackelberg game between utility companies and end-users to maximize the revenue of each utility company and the payoff of each user. We derive analytical results for the Stackelberg equilibrium of the game and prove that a unique solution exists. We develop a distributed algorithm which converges to the equilibrium with only local information available for both utility companies and end-users. Though DRM helps to facilitate the reliability of power supply, the smart grid can be succeptible to privacy and security issues because of communication links between the utility companies and the consumers. We study the impact of an attacker who can manipulate the price information from the utility companies. We also propose a scheme based on the concept of shared reserve power to improve the grid reliability and ensure its dependability.

Tamer Başar - One of the best experts on this subject based on the ideXlab platform.

  • demand Response Management in the smart grid in a large population regime
    IEEE Transactions on Smart Grid, 2016
    Co-Authors: Sabita Maharjan, Stein Gjessing, Quanyan Zhu, Yan Zhang, Tamer Başar
    Abstract:

    In this paper, we introduce a hierarchical system model that captures the decision making processes involved in a network of multiple providers and a large number of consumers in the smart grid, incorporating multiple processes from power generation to market activities and to power consumption. We establish a Stackelberg game between providers and end users, where the providers behave as leaders maximizing their profit and end users act as the followers maximizing their individual welfare. We obtain closed-form expressions for the Stackelberg equilibrium of the game and prove that a unique equilibrium solution exists. In the large population regime, we show that a higher number of providers help to improve profits for the providers. This is inline with the goal of facilitating multiple distributed power generation units, one of the main design considerations in the smart grid. We further prove that there exist a unique number of providers that maximize their profits, and develop an iterative and distributed algorithm to obtain it. Finally, we provide numerical examples to illustrate the solutions and to corroborate the results.

  • value of demand Response in the smart grid
    Power and Energy Conference at Illinois, 2013
    Co-Authors: Quanyan Zhu, Peter W Sauer, Tamer Başar
    Abstract:

    In this paper, we raise the question: What is the value that demand Response Management (DRM) can bring to generation companies and consumers in the smart grid? The question is fundamental for understanding the efficiency and impact of DRM on the future power grid. To answer this question, we first establish a Stackelberg game framework that captures the hierarchical communication architecture of the energy system, and the rational behaviors of the consumers and the market operator. We define the value of demand Response based on the Stackelberg equilibrium (SE) solution to the hierarchical two-person game problem, and the standard optimal solution to economic dispatch problem. In order to compute the equilibrium solution, we show that a consistency principle can be used to characterize the SE of the game in which the follower responds to the dual variable of the leader's problem. We use logarithmic utility functions to illustrate the solution concept and show that in some cases, DRM provides conflicting values to the gencos and consumers.

  • dependable demand Response Management in the smart grid a stackelberg game approach
    IEEE Transactions on Smart Grid, 2013
    Co-Authors: Sabita Maharjan, Stein Gjessing, Quanyan Zhu, Yan Zhang, Tamer Başar
    Abstract:

    Demand Response Management (DRM) is a key component in the smart grid to effectively reduce power generation costs and user bills. However, it has been an open issue to address the DRM problem in a network of multiple utility companies and consumers where every entity is concerned about maximizing its own benefit. In this paper, we propose a Stackelberg game between utility companies and end-users to maximize the revenue of each utility company and the payoff of each user. We derive analytical results for the Stackelberg equilibrium of the game and prove that a unique solution exists. We develop a distributed algorithm which converges to the equilibrium with only local information available for both utility companies and end-users. Though DRM helps to facilitate the reliability of power supply, the smart grid can be succeptible to privacy and security issues because of communication links between the utility companies and the consumers. We study the impact of an attacker who can manipulate the price information from the utility companies. We also propose a scheme based on the concept of shared reserve power to improve the grid reliability and ensure its dependability.

Ping Zhang - One of the best experts on this subject based on the ideXlab platform.

  • Priority-Based Dynamic Spectrum Management in a Smart Grid Network Environment
    IEEE Journal on Selected Areas in Communications, 2015
    Co-Authors: Zhiyong Feng, T. Aaron Gulliver, Ping Zhang
    Abstract:

    The heterogeneous smart grid (SG) poses two major challenges for wireless networks, namely, providing sufficient bandwidth for a wide variety of applications and high reliability for critical real-time applications. To address these challenges, the impact of communication outage on the demand Response Management as a typical SG application is analyzed in this paper. A dynamic spectrum Management (DSM) technique is proposed to allocate resources, considering the QoS and application priorities. Vacant digital TV frequency bands are utilized to support SG applications. An algorithm to estimate the SG capacity is introduced, which can be applied to various user distributions and SG environments. This is used in conjunction with a low-complexity coloring theory algorithm to allocate the spectrum. The results presented show that DSM provides better performance than traditional fixed spectrum Management, in terms of QoS and secondary spectrum utilization.

  • joint spatial and temporal spectrum sharing for demand Response Management in cognitive radio enabled smart grid
    IEEE Transactions on Smart Grid, 2014
    Co-Authors: Qian Li, Zhiyong Feng, Wei Li, Aaron T Gulliver, Ping Zhang
    Abstract:

    Real-time demand Response Management (DRM) in smart grid (SG) requires a reliable wireless communication network with sufficient spectrum resources. However, the allocated spectrum for wireless communications is heavily under-utilized in the spatial and temporal dimensions. To solve the spectrum scarcity problem, cognitive radio (CR) and dynamic spectrum sharing have been proposed, but this can result in poor reliability. In this paper, the influence of wireless communication reliability on DRM is analyzed and the relationship between outage and DRM performance is derived. Outage results from not only interference and noise, but also the unavailability of spectrum resources. Therefore, joint spatial and temporal spectrum sharing is proposed to improve spectrum utilization. The SG network is divided into a Temporal Spectrum Sharing Region (TSSR) and a Free Spatial Spectrum Sharing Region (Free-SSSR). SG nodes in the TSSR can utilize the licensed spectrum when primary users (PUs) are idle, while in the Free-SSSR they can simultaneously share this spectrum with the PUs without using power control. Performance results are presented which show that joint spatial and temporal spectrum sharing can increase the SG spectrum utilization opportunities and lower the outage probability, which is beneficial for DRM performance.

Sabita Maharjan - One of the best experts on this subject based on the ideXlab platform.

  • demand Response Management in the smart grid in a large population regime
    IEEE Transactions on Smart Grid, 2016
    Co-Authors: Sabita Maharjan, Stein Gjessing, Quanyan Zhu, Yan Zhang, Tamer Başar
    Abstract:

    In this paper, we introduce a hierarchical system model that captures the decision making processes involved in a network of multiple providers and a large number of consumers in the smart grid, incorporating multiple processes from power generation to market activities and to power consumption. We establish a Stackelberg game between providers and end users, where the providers behave as leaders maximizing their profit and end users act as the followers maximizing their individual welfare. We obtain closed-form expressions for the Stackelberg equilibrium of the game and prove that a unique equilibrium solution exists. In the large population regime, we show that a higher number of providers help to improve profits for the providers. This is inline with the goal of facilitating multiple distributed power generation units, one of the main design considerations in the smart grid. We further prove that there exist a unique number of providers that maximize their profits, and develop an iterative and distributed algorithm to obtain it. Finally, we provide numerical examples to illustrate the solutions and to corroborate the results.

  • An incentivized auction-based group-selling approach for demand Response Management in V2G systems
    IEEE Transactions on Industrial Informatics, 2015
    Co-Authors: Ming Zeng, Stein Gjessing, Sabita Maharjan, Supeng Leng, Jianhua He
    Abstract:

    Vehicle-to-grid (V2G) system with efficient demand Response Management\n(DRM) is critical to solve the problem of supplying electricity by\nutilizing surplus electricity available at electric vehicles (EVs). An\nincentivized DRM approach is studied to reduce the system cost and\nmaintain the system stability. EVs are motivated with dynamic pricing\ndetermined by the group-selling-based auction. In the proposed approach,\na number of aggregators sit on the first-level auction responsible to\ncommunicate with a group of EVs. EVs as bidders consider quality of\nenergy (QoE) requirements, and report interests and decisions on the\nbidding process coordinated by the associated aggregator. Auction\nwinners are determined based on the bidding prices and the amount of\nelectricity sold by the EV bidders. We investigate the impact of the\nproposed mechanism on the system performance with maximum feedback power\nconstraints of aggregators. The designed mechanism is proven to have\nessential economic properties. Simulation results indicate that the\nproposed mechanism can reduce the system cost and offer EVs significant\nincentives to participate in the V2G DRM operation.

  • dependable demand Response Management in the smart grid a stackelberg game approach
    IEEE Transactions on Smart Grid, 2013
    Co-Authors: Sabita Maharjan, Stein Gjessing, Quanyan Zhu, Yan Zhang, Tamer Başar
    Abstract:

    Demand Response Management (DRM) is a key component in the smart grid to effectively reduce power generation costs and user bills. However, it has been an open issue to address the DRM problem in a network of multiple utility companies and consumers where every entity is concerned about maximizing its own benefit. In this paper, we propose a Stackelberg game between utility companies and end-users to maximize the revenue of each utility company and the payoff of each user. We derive analytical results for the Stackelberg equilibrium of the game and prove that a unique solution exists. We develop a distributed algorithm which converges to the equilibrium with only local information available for both utility companies and end-users. Though DRM helps to facilitate the reliability of power supply, the smart grid can be succeptible to privacy and security issues because of communication links between the utility companies and the consumers. We study the impact of an attacker who can manipulate the price information from the utility companies. We also propose a scheme based on the concept of shared reserve power to improve the grid reliability and ensure its dependability.

Stein Gjessing - One of the best experts on this subject based on the ideXlab platform.

  • Balancing Power Demand Through EV Mobility in Vehicle-to-Grid Mobile Energy Networks
    IEEE Transactions on Industrial Informatics, 2016
    Co-Authors: Rong Yu, Shengli Xie, Stein Gjessing, Weifeng Zhong, Chau Yuen, Yan Zhang
    Abstract:

    Vehicle-to-grid (V2G) technology enables bidirectional energy flow between electric vehicles (EVs) and power grid, which provides flexible demand Response Management (DRM) for the reliability of smart grid. EV mobility is a unique and inherent feature of the V2G system. However, the inter-relationship between EV mobility and DRM is not obvious. In this paper, we focus on the exploration of EV mobility to impact DRM in V2G systems in smart grid. We first present a dynamic complex network model of V2G mobile energy networks, considering the fact that EVs travel across multiple districts, and hence EVs can be acting as energy transporters among different districts. We formulate the districts' DRM dynamics, which is coupled with each other through EV fleets. In addition, a complex network synchronization method is proposed to analyze the dynamic behavior in V2G mobile energy networks. Numerical results show that EVs mobility of symmetrical EV fleet is able to achieve synchronous stability of network and balance the power demand among different districts. This observation is also validated by simulation with real world data.

  • demand Response Management in the smart grid in a large population regime
    IEEE Transactions on Smart Grid, 2016
    Co-Authors: Sabita Maharjan, Stein Gjessing, Quanyan Zhu, Yan Zhang, Tamer Başar
    Abstract:

    In this paper, we introduce a hierarchical system model that captures the decision making processes involved in a network of multiple providers and a large number of consumers in the smart grid, incorporating multiple processes from power generation to market activities and to power consumption. We establish a Stackelberg game between providers and end users, where the providers behave as leaders maximizing their profit and end users act as the followers maximizing their individual welfare. We obtain closed-form expressions for the Stackelberg equilibrium of the game and prove that a unique equilibrium solution exists. In the large population regime, we show that a higher number of providers help to improve profits for the providers. This is inline with the goal of facilitating multiple distributed power generation units, one of the main design considerations in the smart grid. We further prove that there exist a unique number of providers that maximize their profits, and develop an iterative and distributed algorithm to obtain it. Finally, we provide numerical examples to illustrate the solutions and to corroborate the results.

  • An incentivized auction-based group-selling approach for demand Response Management in V2G systems
    IEEE Transactions on Industrial Informatics, 2015
    Co-Authors: Ming Zeng, Stein Gjessing, Sabita Maharjan, Supeng Leng, Jianhua He
    Abstract:

    Vehicle-to-grid (V2G) system with efficient demand Response Management\n(DRM) is critical to solve the problem of supplying electricity by\nutilizing surplus electricity available at electric vehicles (EVs). An\nincentivized DRM approach is studied to reduce the system cost and\nmaintain the system stability. EVs are motivated with dynamic pricing\ndetermined by the group-selling-based auction. In the proposed approach,\na number of aggregators sit on the first-level auction responsible to\ncommunicate with a group of EVs. EVs as bidders consider quality of\nenergy (QoE) requirements, and report interests and decisions on the\nbidding process coordinated by the associated aggregator. Auction\nwinners are determined based on the bidding prices and the amount of\nelectricity sold by the EV bidders. We investigate the impact of the\nproposed mechanism on the system performance with maximum feedback power\nconstraints of aggregators. The designed mechanism is proven to have\nessential economic properties. Simulation results indicate that the\nproposed mechanism can reduce the system cost and offer EVs significant\nincentives to participate in the V2G DRM operation.

  • dependable demand Response Management in the smart grid a stackelberg game approach
    IEEE Transactions on Smart Grid, 2013
    Co-Authors: Sabita Maharjan, Stein Gjessing, Quanyan Zhu, Yan Zhang, Tamer Başar
    Abstract:

    Demand Response Management (DRM) is a key component in the smart grid to effectively reduce power generation costs and user bills. However, it has been an open issue to address the DRM problem in a network of multiple utility companies and consumers where every entity is concerned about maximizing its own benefit. In this paper, we propose a Stackelberg game between utility companies and end-users to maximize the revenue of each utility company and the payoff of each user. We derive analytical results for the Stackelberg equilibrium of the game and prove that a unique solution exists. We develop a distributed algorithm which converges to the equilibrium with only local information available for both utility companies and end-users. Though DRM helps to facilitate the reliability of power supply, the smart grid can be succeptible to privacy and security issues because of communication links between the utility companies and the consumers. We study the impact of an attacker who can manipulate the price information from the utility companies. We also propose a scheme based on the concept of shared reserve power to improve the grid reliability and ensure its dependability.