IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v51y2013icp85-100.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544212009218
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2012.12.009?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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.
    2. 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.
    3. 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.
    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. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Liu, Nian & Chen, Zheng & Liu, Jie & Tang, Xiao & Xiao, Xiangning & Zhang, Jianhua, 2014. "Multi-objective optimization for component capacity of the photovoltaic-based battery switch stations: Towards benefits of economy and environment," Energy, Elsevier, vol. 64(C), pages 779-792.
    2. Baohua Zhang & Weihao Hu & Peng Hou & Jin Tan & Mohsen Soltani & Zhe Chen, 2017. "Review of Reactive Power Dispatch Strategies for Loss Minimization in a DFIG-based Wind Farm," Energies, MDPI, vol. 10(7), pages 1-17, June.
    3. Ibrahim, Amin & Rahnamayan, Shahryar & Vargas Martin, Miguel & Yilbas, Bekir, 2014. "Multi-objective thermal analysis of a thermoelectric device: Influence of geometric features on device characteristics," Energy, Elsevier, vol. 77(C), pages 305-317.
    4. Pourakbari-Kasmaei, Mahdi & Rider, Marcos J. & Mantovani, José R.S., 2014. "An unequivocal normalization-based paradigm to solve dynamic economic and emission active-reactive OPF (optimal power flow)," Energy, Elsevier, vol. 73(C), pages 554-566.
    5. Ippolito, M.G. & Di Silvestre, M.L. & Riva Sanseverino, E. & Zizzo, G. & Graditi, G., 2014. "Multi-objective optimized management of electrical energy storage systems in an islanded network with renewable energy sources under different design scenarios," Energy, Elsevier, vol. 64(C), pages 648-662.
    6. Zare, Mohsen & Niknam, Taher & Azizipanah-Abarghooee, Rasoul & Amiri, Babak, 2014. "Multi-objective probabilistic reactive power and voltage control with wind site correlations," Energy, Elsevier, vol. 66(C), pages 810-822.
    7. Jin, Hongyang & Li, Zhengshuo & Sun, Hongbin & Guo, Qinglai & Wang, Bin, 2018. "A two-stage reactive power optimization in transmission network incorporating reserves from voltage-dependent loads," Energy, Elsevier, vol. 157(C), pages 752-763.
    8. Sousa, Tiago & Morais, Hugo & Vale, Zita & Castro, Rui, 2015. "A multi-objective optimization of the active and reactive resource scheduling at a distribution level in a smart grid context," Energy, Elsevier, vol. 85(C), pages 236-250.
    9. Ahmadimanesh, A. & Kalantar, M., 2017. "A novel cost reducing reactive power market structure for modifying mandatory generation regions of producers," Energy Policy, Elsevier, vol. 108(C), pages 702-711.
    10. Witanowski, Łukasz & Klonowicz, Piotr & Lampart, Piotr & Ziółkowski, Paweł, 2023. "Multi-objective optimization of the ORC axial turbine for a waste heat recovery system working in two modes: cogeneration and condensation," Energy, Elsevier, vol. 264(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kargarian, A. & Raoofat, M. & Mohammadi, M., 2011. "Reactive power market management considering voltage control area reserve and system security," Applied Energy, Elsevier, vol. 88(11), pages 3832-3840.
    2. Esmaili, Masoud & Shayanfar, Heidar Ali & Amjady, Nima, 2010. "Congestion management enhancing transient stability of power systems," Applied Energy, Elsevier, vol. 87(3), pages 971-981, March.
    3. 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.
    4. 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.
    5. Jin, Hongyang & Li, Zhengshuo & Sun, Hongbin & Guo, Qinglai & Wang, Bin, 2018. "A two-stage reactive power optimization in transmission network incorporating reserves from voltage-dependent loads," Energy, Elsevier, vol. 157(C), pages 752-763.
    6. Canizes, Bruno & Soares, João & Faria, Pedro & Vale, Zita, 2013. "Mixed integer non-linear programming and Artificial Neural Network based approach to ancillary services dispatch in competitive electricity markets," Applied Energy, Elsevier, vol. 108(C), pages 261-270.
    7. Fernández-Blanco, Ricardo & Arroyo, José M. & Alguacil, Natalia, 2014. "Consumer payment minimization under uniform pricing: A mixed-integer linear programming approach," Applied Energy, Elsevier, vol. 114(C), pages 676-686.
    8. Esmaili, Masoud & Amjady, Nima & Shayanfar, Heidar Ali, 2011. "Multi-objective congestion management by modified augmented [epsilon]-constraint method," Applied Energy, Elsevier, vol. 88(3), pages 755-766, March.
    9. Pan, Jeng-Shyang & Hu, Pei & Chu, Shu-Chuan, 2021. "Binary fish migration optimization for solving unit commitment," Energy, Elsevier, vol. 226(C).
    10. Di Somma, M. & Graditi, G. & Heydarian-Forushani, E. & Shafie-khah, M. & Siano, P., 2018. "Stochastic optimal scheduling of distributed energy resources with renewables considering economic and environmental aspects," Renewable Energy, Elsevier, vol. 116(PA), pages 272-287.
    11. Cao, M.F. & Huang, G.H. & Lin, Q.G., 2010. "Integer programming with random-boundary intervals for planning municipal power systems," Applied Energy, Elsevier, vol. 87(8), pages 2506-2516, August.
    12. Morales, J.M. & Mínguez, R. & Conejo, A.J., 2010. "A methodology to generate statistically dependent wind speed scenarios," Applied Energy, Elsevier, vol. 87(3), pages 843-855, March.
    13. Erdogdu, Erkan, 2010. "A paper on the unsettled question of Turkish electricity market: Balancing and settlement system (Part I)," Applied Energy, Elsevier, vol. 87(1), pages 251-258, January.
    14. Tabandeh, Abbas & Abdollahi, Amir & Rashidinejad, Masoud, 2016. "Reliability constrained congestion management with uncertain negawatt demand response firms considering repairable advanced metering infrastructures," Energy, Elsevier, vol. 104(C), pages 213-228.
    15. Vijay, Avinash & Fouquet, Nicolas & Staffell, Iain & Hawkes, Adam, 2017. "The value of electricity and reserve services in low carbon electricity systems," Applied Energy, Elsevier, vol. 201(C), pages 111-123.
    16. Anaya, Karim L. & Pollitt, Michael G., 2022. "A social cost benefit analysis for the procurement of reactive power: The case of Power Potential," Applied Energy, Elsevier, vol. 312(C).
    17. Jay, Devika & Swarup, K.S., 2021. "A comprehensive survey on reactive power ancillary service markets," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    18. Aghaei, Jamshid & Alizadeh, Mohammad-Iman, 2013. "Multi-objective self-scheduling of CHP (combined heat and power)-based microgrids considering demand response programs and ESSs (energy storage systems)," Energy, Elsevier, vol. 55(C), pages 1044-1054.
    19. Fotouhi Ghazvini, Mohammad Ali & Canizes, Bruno & Vale, Zita & Morais, Hugo, 2013. "Stochastic short-term maintenance scheduling of GENCOs in an oligopolistic electricity market," Applied Energy, Elsevier, vol. 101(C), pages 667-677.
    20. Dylan F. Jones & Graham Wall, 2016. "An extended goal programming model for site selection in the offshore wind farm sector," Annals of Operations Research, Springer, vol. 245(1), pages 121-135, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:51:y:2013:i:c:p:85-100. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.