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A novel multi-zone reactive power market settlement model: A pareto-optimization approach

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  • Saraswat, Amit
  • Saini, Ashish
  • Saxena, Ajay Kumar

Abstract

This paper presents a Pareto-optimization based zonal day-ahead reactive power market settlement model named as multi-zone DA-RPMS model. Three competing objective functions such as Total Payment Function (TPF) for reactive power support services from generators/synchronous condensers, Total Real Transmission Loss (TRTL) and Voltage Stability Enhancement Index (VSEI) are optimized simultaneously by satisfying various power system operating constraints while settling the day-ahead reactive power market. The proposed multi-zone DA-RPMS model is tested and compared with single-zone DA-RPMS model on standard IEEE 24 bus reliability test system. A Hybrid Fuzzy Multi-Objective Evolutionary Algorithm (HFMOEA) approach is applied and compared with NSGA-II for solving these DA-RPMS models in competitive electricity market environment. Further, both the single-zone and multi-zone DA-RPMS models are also analyzed on the basis of market power owned by any generator/any generating company. The simulation results obtained confirm the superiority of HFMOEA in finding the better Pareto-optimal fronts in order to take better day-ahead reactive power market settlement decisions.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:energy:v:51:y:2013:i:c:p:85-100
    DOI: 10.1016/j.energy.2012.12.009
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    References listed on IDEAS

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    1. Aghaei, J. & Shayanfar, H.A. & Amjady, N., 2009. "Joint market clearing in a stochastic framework considering power system security," Applied Energy, Elsevier, vol. 86(9), pages 1675-1682, September.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
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