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A stochastic framework for clearing of reactive power market

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  • Amjady, N.
  • Rabiee, A.
  • Shayanfar, H.A.

Abstract

This paper presents a new stochastic framework for clearing of day-ahead reactive power market. The uncertainty of generating units in the form of system contingencies are considered in the reactive power market-clearing procedure by the stochastic model in two steps. The Monte-Carlo Simulation (MCS) is first used to generate random scenarios. Then, in the second step, the stochastic market-clearing procedure is implemented as a series of deterministic optimization problems (scenarios) including non-contingent scenario and different post-contingency states. In each of these deterministic optimization problems, the objective function is total payment function (TPF) of generators which refers to the payment paid to the generators for their reactive power compensation. The effectiveness of the proposed model is examined based on the IEEE 24-bus Reliability Test System (IEEE 24-bus RTS).

Suggested Citation

  • Amjady, N. & Rabiee, A. & Shayanfar, H.A., 2010. "A stochastic framework for clearing of reactive power market," Energy, Elsevier, vol. 35(1), pages 239-245.
    • Handle: RePEc:eee:energy:v:35:y:2010:i:1:p:239-245
    DOI: 10.1016/j.energy.2009.09.015
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    References listed on IDEAS

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    1. Rabiee, A. & Shayanfar, H. & Amjady, N., 2009. "Multiobjective clearing of reactive power market in deregulated power systems," Applied Energy, Elsevier, vol. 86(9), pages 1555-1564, September.
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    Cited by:

    1. Reddy, S. Surender & Abhyankar, A.R. & Bijwe, P.R., 2011. "Reactive power price clearing using multi-objective optimization," Energy, Elsevier, vol. 36(5), pages 3579-3589.
    2. Fodor, Attila & Magyar, Attila & Hangos, Katalin M., 2012. "Control-oriented modeling of the energy-production of a synchronous generator in a nuclear power plant," Energy, Elsevier, vol. 39(1), pages 135-145.
    3. Kim, M.K. & Park, J.K. & Nam, Y.W., 2011. "Market-clearing for pricing system security based on voltage stability criteria," Energy, Elsevier, vol. 36(2), pages 1255-1264.
    4. Khazali, A.H. & Kalantar, M. & Khazali, Ali, 2011. "Fuzzy multi-objective reactive power clearing considering reactive compensation sources," Energy, Elsevier, vol. 36(5), pages 3319-3327.
    5. Kargarian, A. & Raoofat, M., 2011. "Stochastic reactive power market with volatility of wind power considering voltage security," Energy, Elsevier, vol. 36(5), pages 2565-2571.
    6. Samimi, Abouzar & Nikzad, Mehdi & Siano, Pierluigi, 2017. "Scenario-based stochastic framework for coupled active and reactive power market in smart distribution systems with demand response programs," Renewable Energy, Elsevier, vol. 109(C), pages 22-40.
    7. Saraswat, Amit & Saini, Ashish & Saxena, Ajay Kumar, 2013. "A novel multi-zone reactive power market settlement model: A pareto-optimization approach," Energy, Elsevier, vol. 51(C), pages 85-100.

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