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Heidar Ali Shayanfar - One of the best experts on this subject based on the ideXlab platform.

  • Congestion Management in hybrid power markets using modified Benders decomposition
    Applied Energy, 2013
    Co-Authors: Masoud Esmaili, Heidar Ali Shayanfar, Fatemeh Ebadi, Shahram Jadid
    Abstract:

    Abstract Congestion Management is one of critical tasks in electric power markets. Although Congestion Management using a centralized optimal power flow may give an efficient solution, it lacks enough transparency in a competitive power market for its participants about Congestion related costs. On the other hand, clearing the market and mitigating Congestion separately may not result in an efficient solution from cost viewpoint. In this paper, a two-stage method using a modified Benders decomposition technique is proposed for Congestion Management in hybrid electricity markets including pool and bilateral transactions. An innovative convergence criterion and a new type of the sub-problem are proposed in using Benders decomposition in Congestion Management. The proposed method not only gives the efficient solution, but also provides enough transparency about Congestion cost. Results of testing the method on the New-England test system are presented and discussed in detail. The results confirm the efficiency of the proposed Congestion Management method.

  • multi objective Congestion Management by modified augmented e constraint method
    Applied Energy, 2011
    Co-Authors: Masoud Esmaili, Nima Amjady, Heidar Ali Shayanfar
    Abstract:

    Abstract Congestion Management is a vital part of power system operations in recent deregulated electricity markets. However, after relieving Congestion, power systems may be operated with a reduced voltage or transient stability margin because of hitting security limits or increasing the contribution of risky participants. Therefore, power system stability margins should be considered within the Congestion Management framework. The multi-objective Congestion Management provides not only more security but also more flexibility than single-objective methods. In this paper, a multi-objective Congestion Management framework is presented while simultaneously optimizing the competing objective functions of Congestion Management cost, voltage security, and dynamic security. The proposed multi-objective framework, called modified augmented e-constraint method, is based on the augmented e-constraint technique hybridized by the weighting method. The proposed framework generates candidate solutions for the multi-objective problem including only efficient Pareto surface enhancing the competitiveness and economic effectiveness of the power market. Besides, the relative importance of the objective functions is explicitly modeled in the proposed framework. Results of testing the proposed multi-objective Congestion Management method on the New-England test system are presented and compared with those of the previous single objective and multi-objective techniques in detail. These comparisons confirm the efficiency of the developed method.

  • Multi-objective Congestion Management by modified augmented ε-constraint method
    Applied Energy, 2011
    Co-Authors: Masoud Esmaili, Nima Amjady, Heidar Ali Shayanfar
    Abstract:

    Abstract Congestion Management is a vital part of power system operations in recent deregulated electricity markets. However, after relieving Congestion, power systems may be operated with a reduced voltage or transient stability margin because of hitting security limits or increasing the contribution of risky participants. Therefore, power system stability margins should be considered within the Congestion Management framework. The multi-objective Congestion Management provides not only more security but also more flexibility than single-objective methods. In this paper, a multi-objective Congestion Management framework is presented while simultaneously optimizing the competing objective functions of Congestion Management cost, voltage security, and dynamic security. The proposed multi-objective framework, called modified augmented e-constraint method, is based on the augmented e-constraint technique hybridized by the weighting method. The proposed framework generates candidate solutions for the multi-objective problem including only efficient Pareto surface enhancing the competitiveness and economic effectiveness of the power market. Besides, the relative importance of the objective functions is explicitly modeled in the proposed framework. Results of testing the proposed multi-objective Congestion Management method on the New-England test system are presented and compared with those of the previous single objective and multi-objective techniques in detail. These comparisons confirm the efficiency of the developed method.

  • Stochastic Congestion Management in power markets using efficient scenario approaches
    Energy Conversion and Management, 2010
    Co-Authors: Masoud Esmaili, Nima Amjady, Heidar Ali Shayanfar
    Abstract:

    Congestion Management in electricity markets is traditionally performed using deterministic values of system parameters assuming a fixed network configuration. In this paper, a stochastic programming framework is proposed for Congestion Management considering the power system uncertainties comprising outage of generating units and transmission branches. The Forced Outage Rate of equipment is employed in the stochastic programming. Using the Monte Carlo simulation, possible scenarios of power system operating states are generated and a probability is assigned to each scenario. The performance of the ordinary as well as Lattice rank-1 and rank-2 Monte Carlo simulations is evaluated in the proposed Congestion Management framework. As a tradeoff between computation time and accuracy, scenario reduction based on the standard deviation of accepted scenarios is adopted. The stochastic Congestion Management solution is obtained by aggregating individual solutions of accepted scenarios. Congestion Management using the proposed stochastic framework provides a more realistic solution compared with traditional deterministic solutions. Results of testing the proposed stochastic Congestion Management on the 24-bus reliability test system indicate the efficiency of the proposed framework.

  • multi objective Congestion Management incorporating voltage and transient stabilities
    Energy, 2009
    Co-Authors: Masoud Esmaili, Heidar Ali Shayanfar, Nima Amjady
    Abstract:

    Congestion in a power system is turned up due to operating limits. To relieve Congestion in a deregulated power market, the system operator pays to market participants considering their bids to alter their active powers. After relieving Congestion, the network may be operated with a reduced voltage or transient stability margin because of hitting security limits or increasing the contribution of risky participants. The proposed multi-objective framework for Congestion Management in this paper simultaneously optimizes competing objective functions of Congestion Management cost, voltage security, and dynamic security. The voltage stability margin and corrected transient energy margin are employed as indices to be incorporated into the multi-objective Congestion Management. A fuzzy decision maker is proposed to derive the most efficient solution among Pareto-optimal solutions of multi-objective mathematical programming problem. Results of testing the proposed method on the New-England test system elaborate the efficiency of the proposed method.

Nima Amjady - One of the best experts on this subject based on the ideXlab platform.

  • a new multi objective solution approach to solve transmission Congestion Management problem of energy markets
    Applied Energy, 2016
    Co-Authors: S A Hosseini, Nima Amjady, Miadreza Shafiekhah, Joao P S Catalao
    Abstract:

    Transmission Congestion Management plays a key role in deregulated energy markets. To correctly model and solve this problem, power system voltage and transient stability limits should be considered to avoid obtaining a vulnerable power system with low stability margins. Congestion Management is modeled as a multi-objective optimization problem in this paper. The proposed scheme includes the cost of Congestion Management, voltage stability margin and transient stability margin as its multiple competing objectives. Moreover, a new effective Multi-objective Mathematical Programming (MMP) solution approach based on normalized normal constraint (NNC) method is presented to solve the multi-objective optimization problem of the Congestion Management, which can generate a well-distributed and efficient Pareto frontier. The proposed Congestion Management model and MMP solution approach are implemented on the New-England’s test system and the obtained results are compared with the results of several other Congestion Management methods. These comparisons verify the superiority of the proposed approach.

  • Dynamic voltage stability constrained Congestion Management framework for deregulated electricity markets
    Energy Conversion and Management, 2012
    Co-Authors: Nima Amjady, Mahmood Hakimi
    Abstract:

    Congestion Management is an important part of power system operation in today deregulated electricity markets. However, Congestion Management is traditionally performed based on static analysis tools, while these tools may not correctly capture dynamic voltage stability limits of a power system. In this paper, a new Congestion Management framework considering dynamic voltage stability boundary of power system is proposed. For this purpose, precise dynamic modeling of power system equipment, including generators and loads, is incorporated into the proposed Congestion Management framework. The proposed method alleviates Congestion with a lower Congestion Management cost and more dynamic voltage stability margin, resulting in a more robust power system, compared with the previous Congestion Management methods. The validity of proposed Congestion Management framework is studied based on the New England 39-bus power system. The obtained results confirm the validity of the developed approach.

  • multi objective Congestion Management by modified augmented e constraint method
    Applied Energy, 2011
    Co-Authors: Masoud Esmaili, Nima Amjady, Heidar Ali Shayanfar
    Abstract:

    Abstract Congestion Management is a vital part of power system operations in recent deregulated electricity markets. However, after relieving Congestion, power systems may be operated with a reduced voltage or transient stability margin because of hitting security limits or increasing the contribution of risky participants. Therefore, power system stability margins should be considered within the Congestion Management framework. The multi-objective Congestion Management provides not only more security but also more flexibility than single-objective methods. In this paper, a multi-objective Congestion Management framework is presented while simultaneously optimizing the competing objective functions of Congestion Management cost, voltage security, and dynamic security. The proposed multi-objective framework, called modified augmented e-constraint method, is based on the augmented e-constraint technique hybridized by the weighting method. The proposed framework generates candidate solutions for the multi-objective problem including only efficient Pareto surface enhancing the competitiveness and economic effectiveness of the power market. Besides, the relative importance of the objective functions is explicitly modeled in the proposed framework. Results of testing the proposed multi-objective Congestion Management method on the New-England test system are presented and compared with those of the previous single objective and multi-objective techniques in detail. These comparisons confirm the efficiency of the developed method.

  • Multi-objective Congestion Management by modified augmented ε-constraint method
    Applied Energy, 2011
    Co-Authors: Masoud Esmaili, Nima Amjady, Heidar Ali Shayanfar
    Abstract:

    Abstract Congestion Management is a vital part of power system operations in recent deregulated electricity markets. However, after relieving Congestion, power systems may be operated with a reduced voltage or transient stability margin because of hitting security limits or increasing the contribution of risky participants. Therefore, power system stability margins should be considered within the Congestion Management framework. The multi-objective Congestion Management provides not only more security but also more flexibility than single-objective methods. In this paper, a multi-objective Congestion Management framework is presented while simultaneously optimizing the competing objective functions of Congestion Management cost, voltage security, and dynamic security. The proposed multi-objective framework, called modified augmented e-constraint method, is based on the augmented e-constraint technique hybridized by the weighting method. The proposed framework generates candidate solutions for the multi-objective problem including only efficient Pareto surface enhancing the competitiveness and economic effectiveness of the power market. Besides, the relative importance of the objective functions is explicitly modeled in the proposed framework. Results of testing the proposed multi-objective Congestion Management method on the New-England test system are presented and compared with those of the previous single objective and multi-objective techniques in detail. These comparisons confirm the efficiency of the developed method.

  • Stochastic Congestion Management in power markets using efficient scenario approaches
    Energy Conversion and Management, 2010
    Co-Authors: Masoud Esmaili, Nima Amjady, Heidar Ali Shayanfar
    Abstract:

    Congestion Management in electricity markets is traditionally performed using deterministic values of system parameters assuming a fixed network configuration. In this paper, a stochastic programming framework is proposed for Congestion Management considering the power system uncertainties comprising outage of generating units and transmission branches. The Forced Outage Rate of equipment is employed in the stochastic programming. Using the Monte Carlo simulation, possible scenarios of power system operating states are generated and a probability is assigned to each scenario. The performance of the ordinary as well as Lattice rank-1 and rank-2 Monte Carlo simulations is evaluated in the proposed Congestion Management framework. As a tradeoff between computation time and accuracy, scenario reduction based on the standard deviation of accepted scenarios is adopted. The stochastic Congestion Management solution is obtained by aggregating individual solutions of accepted scenarios. Congestion Management using the proposed stochastic framework provides a more realistic solution compared with traditional deterministic solutions. Results of testing the proposed stochastic Congestion Management on the 24-bus reliability test system indicate the efficiency of the proposed framework.

Masoud Esmaili - One of the best experts on this subject based on the ideXlab platform.

  • Congestion Management in hybrid power markets using modified Benders decomposition
    Applied Energy, 2013
    Co-Authors: Masoud Esmaili, Heidar Ali Shayanfar, Fatemeh Ebadi, Shahram Jadid
    Abstract:

    Abstract Congestion Management is one of critical tasks in electric power markets. Although Congestion Management using a centralized optimal power flow may give an efficient solution, it lacks enough transparency in a competitive power market for its participants about Congestion related costs. On the other hand, clearing the market and mitigating Congestion separately may not result in an efficient solution from cost viewpoint. In this paper, a two-stage method using a modified Benders decomposition technique is proposed for Congestion Management in hybrid electricity markets including pool and bilateral transactions. An innovative convergence criterion and a new type of the sub-problem are proposed in using Benders decomposition in Congestion Management. The proposed method not only gives the efficient solution, but also provides enough transparency about Congestion cost. Results of testing the method on the New-England test system are presented and discussed in detail. The results confirm the efficiency of the proposed Congestion Management method.

  • multi objective Congestion Management by modified augmented e constraint method
    Applied Energy, 2011
    Co-Authors: Masoud Esmaili, Nima Amjady, Heidar Ali Shayanfar
    Abstract:

    Abstract Congestion Management is a vital part of power system operations in recent deregulated electricity markets. However, after relieving Congestion, power systems may be operated with a reduced voltage or transient stability margin because of hitting security limits or increasing the contribution of risky participants. Therefore, power system stability margins should be considered within the Congestion Management framework. The multi-objective Congestion Management provides not only more security but also more flexibility than single-objective methods. In this paper, a multi-objective Congestion Management framework is presented while simultaneously optimizing the competing objective functions of Congestion Management cost, voltage security, and dynamic security. The proposed multi-objective framework, called modified augmented e-constraint method, is based on the augmented e-constraint technique hybridized by the weighting method. The proposed framework generates candidate solutions for the multi-objective problem including only efficient Pareto surface enhancing the competitiveness and economic effectiveness of the power market. Besides, the relative importance of the objective functions is explicitly modeled in the proposed framework. Results of testing the proposed multi-objective Congestion Management method on the New-England test system are presented and compared with those of the previous single objective and multi-objective techniques in detail. These comparisons confirm the efficiency of the developed method.

  • Multi-objective Congestion Management by modified augmented ε-constraint method
    Applied Energy, 2011
    Co-Authors: Masoud Esmaili, Nima Amjady, Heidar Ali Shayanfar
    Abstract:

    Abstract Congestion Management is a vital part of power system operations in recent deregulated electricity markets. However, after relieving Congestion, power systems may be operated with a reduced voltage or transient stability margin because of hitting security limits or increasing the contribution of risky participants. Therefore, power system stability margins should be considered within the Congestion Management framework. The multi-objective Congestion Management provides not only more security but also more flexibility than single-objective methods. In this paper, a multi-objective Congestion Management framework is presented while simultaneously optimizing the competing objective functions of Congestion Management cost, voltage security, and dynamic security. The proposed multi-objective framework, called modified augmented e-constraint method, is based on the augmented e-constraint technique hybridized by the weighting method. The proposed framework generates candidate solutions for the multi-objective problem including only efficient Pareto surface enhancing the competitiveness and economic effectiveness of the power market. Besides, the relative importance of the objective functions is explicitly modeled in the proposed framework. Results of testing the proposed multi-objective Congestion Management method on the New-England test system are presented and compared with those of the previous single objective and multi-objective techniques in detail. These comparisons confirm the efficiency of the developed method.

  • Stochastic Congestion Management in power markets using efficient scenario approaches
    Energy Conversion and Management, 2010
    Co-Authors: Masoud Esmaili, Nima Amjady, Heidar Ali Shayanfar
    Abstract:

    Congestion Management in electricity markets is traditionally performed using deterministic values of system parameters assuming a fixed network configuration. In this paper, a stochastic programming framework is proposed for Congestion Management considering the power system uncertainties comprising outage of generating units and transmission branches. The Forced Outage Rate of equipment is employed in the stochastic programming. Using the Monte Carlo simulation, possible scenarios of power system operating states are generated and a probability is assigned to each scenario. The performance of the ordinary as well as Lattice rank-1 and rank-2 Monte Carlo simulations is evaluated in the proposed Congestion Management framework. As a tradeoff between computation time and accuracy, scenario reduction based on the standard deviation of accepted scenarios is adopted. The stochastic Congestion Management solution is obtained by aggregating individual solutions of accepted scenarios. Congestion Management using the proposed stochastic framework provides a more realistic solution compared with traditional deterministic solutions. Results of testing the proposed stochastic Congestion Management on the 24-bus reliability test system indicate the efficiency of the proposed framework.

  • multi objective Congestion Management incorporating voltage and transient stabilities
    Energy, 2009
    Co-Authors: Masoud Esmaili, Heidar Ali Shayanfar, Nima Amjady
    Abstract:

    Congestion in a power system is turned up due to operating limits. To relieve Congestion in a deregulated power market, the system operator pays to market participants considering their bids to alter their active powers. After relieving Congestion, the network may be operated with a reduced voltage or transient stability margin because of hitting security limits or increasing the contribution of risky participants. The proposed multi-objective framework for Congestion Management in this paper simultaneously optimizes competing objective functions of Congestion Management cost, voltage security, and dynamic security. The voltage stability margin and corrected transient energy margin are employed as indices to be incorporated into the multi-objective Congestion Management. A fuzzy decision maker is proposed to derive the most efficient solution among Pareto-optimal solutions of multi-objective mathematical programming problem. Results of testing the proposed method on the New-England test system elaborate the efficiency of the proposed method.

Joao P S Catalao - One of the best experts on this subject based on the ideXlab platform.

  • a new multi objective solution approach to solve transmission Congestion Management problem of energy markets
    Applied Energy, 2016
    Co-Authors: S A Hosseini, Nima Amjady, Miadreza Shafiekhah, Joao P S Catalao
    Abstract:

    Transmission Congestion Management plays a key role in deregulated energy markets. To correctly model and solve this problem, power system voltage and transient stability limits should be considered to avoid obtaining a vulnerable power system with low stability margins. Congestion Management is modeled as a multi-objective optimization problem in this paper. The proposed scheme includes the cost of Congestion Management, voltage stability margin and transient stability margin as its multiple competing objectives. Moreover, a new effective Multi-objective Mathematical Programming (MMP) solution approach based on normalized normal constraint (NNC) method is presented to solve the multi-objective optimization problem of the Congestion Management, which can generate a well-distributed and efficient Pareto frontier. The proposed Congestion Management model and MMP solution approach are implemented on the New-England’s test system and the obtained results are compared with the results of several other Congestion Management methods. These comparisons verify the superiority of the proposed approach.

Fang Da-zhong - One of the best experts on this subject based on the ideXlab platform.

  • A Model for Real-time Congestion Management with Transient Stability Constraints
    Power system technology, 2006
    Co-Authors: Fang Da-zhong
    Abstract:

    A power pool transaction mode based on real-time dynamic Congestion Management model is proposed, in which the dynamic Congestion Management under transient stability constraint is described as an algebraic nonlinear programming that adjusts the output of generators to make the increment of power purchasing cost minimized. The feature of the proposed model is that both transient stability constraint and power flow constraint are expressed by the adjusted quantities of generators' active outputs. Applying the proposed model to the simulation of dynamic Congestion Management by use of typical New England 39-node test system and the simulation results are compared with the calculation results from a static Congestion Management model. Comparison result proves that the proposed model can ensure the secure and stable operation of power system while the network Congestion is eliminated.