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Integrated day-ahead and hour-ahead operation model of discos in retail electricity markets considering DGs and CO2 emission penalty cost

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  • Ghadikolaei, Hadi Moghimi
  • Tajik, Elham
  • Aghaei, Jamshid
  • Charwand, Mansour

Abstract

This paper proposes a new framework for the operation of distribution companies (discos) in the liberalized electricity market environment considering distributed generation (DG) units and carbon dioxide (CO2) emission penalty cost. The proposed short-term framework is a two-stage model. The first stage, namely day-ahead stage, deals with the activities of discos. This stage includes a optimization problem to minimize the costs of distribution company (operational and CO2 emission costs). The first stage is formulated as a mixed integer nonlinear programming (MINLP) framework using the Benders decomposition to determine the decisions of discos to buy power from grid, schedule the DG units and contract with interruptible loads (ILs). The results of the first stage are imposed as the boundary constraints in the second stage which deals with the activities of discos in an hour-ahead period. In the hour-ahead stage, the retailers determine the amount of purchased active and reactive power from the grid and the production of each DG unit in the energy and reserve market keeping in mind its day-ahead decision to maximize the desired short-term profit. Finally, the efficiency of the proposed framework is studied on a case study.

Suggested Citation

  • Ghadikolaei, Hadi Moghimi & Tajik, Elham & Aghaei, Jamshid & Charwand, Mansour, 2012. "Integrated day-ahead and hour-ahead operation model of discos in retail electricity markets considering DGs and CO2 emission penalty cost," Applied Energy, Elsevier, vol. 95(C), pages 174-185.
  • Handle: RePEc:eee:appene:v:95:y:2012:i:c:p:174-185
    DOI: 10.1016/j.apenergy.2012.02.034
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    References listed on IDEAS

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    Cited by:

    1. Ahmadi, Abdollah & Charwand, Mansour & Siano, Pierluigi & Nezhad, Ali Esmaeel & Sarno, Debora & Gitizadeh, Mohsen & Raeisi, Fatima, 2016. "A novel two-stage stochastic programming model for uncertainty characterization in short-term optimal strategy for a distribution company," Energy, Elsevier, vol. 117(P1), pages 1-9.
    2. Bae, Mungyu & Kim, Hwantae & Kim, Eugene & Chung, Albert Yongjoon & Kim, Hwangnam & Roh, Jae Hyung, 2014. "Toward electricity retail competition: Survey and case study on technical infrastructure for advanced electricity market system," Applied Energy, Elsevier, vol. 133(C), pages 252-273.
    3. Fotouhi Ghazvini, Mohammad Ali & Faria, Pedro & Ramos, Sergio & Morais, Hugo & Vale, Zita, 2015. "Incentive-based demand response programs designed by asset-light retail electricity providers for the day-ahead market," Energy, Elsevier, vol. 82(C), pages 786-799.
    4. Muttaqi, K.M. & Le, An D.T. & Aghaei, J. & Mahboubi-Moghaddam, E. & Negnevitsky, M. & Ledwich, G., 2016. "Optimizing distributed generation parameters through economic feasibility assessment," Applied Energy, Elsevier, vol. 165(C), pages 893-903.
    5. Shayegan-Rad, Ali & Badri, Ali & Zangeneh, Ali, 2017. "Day-ahead scheduling of virtual power plant in joint energy and regulation reserve markets under uncertainties," Energy, Elsevier, vol. 121(C), pages 114-125.
    6. Zamani, Ali Ghahgharaee & Zakariazadeh, Alireza & Jadid, Shahram, 2016. "Day-ahead resource scheduling of a renewable energy based virtual power plant," Applied Energy, Elsevier, vol. 169(C), pages 324-340.
    7. Woo, C.K. & Li, R. & Shiu, A. & Horowitz, I., 2013. "Residential winter kWh responsiveness under optional time-varying pricing in British Columbia," Applied Energy, Elsevier, vol. 108(C), pages 288-297.
    8. Pruitt, Kristopher A. & Braun, Robert J. & Newman, Alexandra M., 2013. "Establishing conditions for the economic viability of fuel cell-based, combined heat and power distributed generation systems," Applied Energy, Elsevier, vol. 111(C), pages 904-920.
    9. 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.
    10. repec:eee:appene:v:220:y:2018:i:c:p:800-813 is not listed on IDEAS
    11. Moreno, Blanca & García-Álvarez, María Teresa & Ramos, Carmen & Fernández-Vázquez, Esteban, 2014. "A General Maximum Entropy Econometric approach to model industrial electricity prices in Spain: A challenge for the competitiveness," Applied Energy, Elsevier, vol. 135(C), pages 815-824.
    12. Wu, Jung-Hua & Huang, Yun-Hsun, 2014. "Electricity portfolio planning model incorporating renewable energy characteristics," Applied Energy, Elsevier, vol. 119(C), pages 278-287.
    13. Ghasemi, Ahmad & Mortazavi, Seyed Saeidollah & Mashhour, Elaheh, 2016. "Hourly demand response and battery energy storage for imbalance reduction of smart distribution company embedded with electric vehicles and wind farms," Renewable Energy, Elsevier, vol. 85(C), pages 124-136.
    14. Ghasemi, Ahmad & Mortazavi, Seyed Saeidollah & Mashhour, Elaheh, 2015. "Integration of nodal hourly pricing in day-ahead SDC (smart distribution company) optimization framework to effectively activate demand response," Energy, Elsevier, vol. 86(C), pages 649-660.
    15. Esmaili, Masoud & Firozjaee, Esmail Chaktan & Shayanfar, Heidar Ali, 2014. "Optimal placement of distributed generations considering voltage stability and power losses with observing voltage-related constraints," Applied Energy, Elsevier, vol. 113(C), pages 1252-1260.

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