Incorporating the effects of service quality regulation in decision-making framework of distribution companies

Incorporating the effects of service quality regulation in decision-making framework of distribution companies

For access to this article, please select a purchase option:

Buy article PDF
(plus tax if applicable)
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Your details
Why are you recommending this title?
Select reason:
IET Generation, Transmission & Distribution — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

Incentive regulations of reliability have made a link between distribution companies' revenue and their service reliability. The companies have to decide how much to spend on various projects to provide an acceptable level of reliability while anticipation of load growth. Planners and decision makers require a comprehensive framework to optimally allocate available budgets to different plans with the highest benefits considering implementation of incentive regulation. This paper proposes a decision framework for the optimum share of expansion and reliability oriented plans in presence of reward–penalty mechanisms. A two-layer optimization model is introduced, where in the outer layer, an iterative algorithm is applied to determine the optimal set of long-term projects including Distributed Generations (DGs) installation. A heuristic optimization algorithm is employed in this layer. Considering long-term plans, in inner optimization layer, the optimal set of mid-term plans including feeder reinforcement, and preventive maintenance actions are determined using algorithms such as Branch-and-Cut and dynamic programming techniques. The model is further implemented on a test distribution network and the results are investigated through various case studies. Obtained results show the strong influence of incentive regulation on reliability indices.


    1. 1)
      • 1. Fumagalli, E., Schiavo, L., Delestre, F.: ‘Service quality regulation in electricity distribution and retail’ (Springer Science & Business Media, Berlin, Germany, 2007).
    2. 2)
      • 2. Council of European Energy Regulators (CEER): ‘6th CEER benchmarking report on the quality of electricity and gas supply’, 2016, Available on:
    3. 3)
      • 3. Ghasemi, M., Dashti, R.: ‘A risk-based model for performance-based regulation of electric distribution companies’, Util. Policy, 2017, 45, pp. 3644.
    4. 4)
      • 4. Mohammadi, A., Mehrtash, M., Kargarian, A.: ‘Diagonal quadratic approximation for decentralized collaborative TSO + DSO optimal power flow’, IEEE Trans. Smart Grid, 2018, pp. 11, DOI: 10.1109/TSG.2018.2796034.
    5. 5)
      • 5. Bahrami, S., Amini, M.H., Shafie-khah, M., et al: ‘A decentralized electricity market scheme enabling demand response deployment’, IEEE Trans. Power Syst., 2017, 31, (4), pp. 42184227.
    6. 6)
      • 6. Asensio, M., de Quevedo, P.M., Munoz-Delgado, G., et al: ‘Joint distribution network and renewable energy expansion planning considering demand response and energy storage – Part I: stochastic programming model’, IEEE Trans. Smart Grid, 2018, 2, (9), pp. 655666.
    7. 7)
      • 7. Muñoz-Delgado, G., Contreras, J., Arroyo, J.M.: ‘Joint expansion planning of distributed generation and distribution networks’, IEEE Trans. Power Syst., 2015, 30, (5), pp. 25792590.
    8. 8)
      • 8. Asensio, M., Muñoz-Delgado, G., Contreras, J.: ‘Bi-level approach to distribution network and renewable energy expansion planning considering demand response’, IEEE Trans. Power Syst., 2017, 32, (6), pp. 42984309.
    9. 9)
      • 9. Zare, A., Chung, C., Zhan, J., et al: ‘A distributionally robust chance-constrained MILP model for multistage distribution system planning with uncertain renewables and loads’, IEEE Trans. Power Syst., 2018, 33, (5), pp. 52485262.
    10. 10)
      • 10. Muñoz-Delgado, G., Contreras, J., Arroyo, J.M.: ‘Distribution network expansion planning with an explicit formulation for reliability assessment’, IEEE Trans. Power Syst., 2018, 33, (3), pp. 25832596.
    11. 11)
      • 11. Muñoz-Delgado, G., Contreras, J., Arroyo, J.M.: ‘Multistage generation and network expansion planning in distribution systems considering uncertainty and reliability’, IEEE Trans. Power Syst., 2016, 31, (5), pp. 37153728.
    12. 12)
      • 12. Rupolo, D., Pereira, B.R.Jr, Contreras, J., et al: ‘Medium- and low-voltage planning of radial electric power distribution systems considering reliability’, IET Gener. Transm. Distrib., 2017, 11, (9), pp. 22122221.
    13. 13)
      • 13. Heidari, S., Fotuhi-Firuzabad, M., Lehtonen, M.: ‘Planning to equip the power distribution networks with automation system’, IEEE Trans. Power Syst., 2017, 32, (5), pp. 34513460.
    14. 14)
      • 14. Lotero, R.C., Contreras, J.: ‘Distribution system planning with reliability’, IEEE Trans. Power Deliv., 2011, 26, (4), pp. 25522562.
    15. 15)
      • 15. Alvehag, K., Söder, L.: ‘Risk-based method for distribution system reliability investment decisions under performance-based regulation’, IET Gener. Transm. Distrib., 2011, 5, (10), pp. 10621072.
    16. 16)
      • 16. Mohammadnezhad-Shourkaei, H., Abiri-Jahromi, A., Fotuhi-Firuzabad, M.: ‘Incorporating service quality regulation in distribution system maintenance strategy’, IEEE Trans. Power Deliv., 2011, 26, (4), pp. 24952504.
    17. 17)
      • 17. Aravinthan, V., Jewell, W.: ‘Optimized maintenance scheduling for budget-constrained distribution utility’, IEEE Trans. Smart Grid, 2013, 4, (4), pp. 23282338.
    18. 18)
      • 18. Moradkhani, A., Haghifam, M.R., Abedi, S.M.: ‘Risk-based maintenance scheduling in the presence of reward penalty scheme’, Electr. Power Syst. Res., 2015, 121, pp. 126133.
    19. 19)
      • 19. Larimi, S.M.M., Haghifam, M.R., Moradkhani, A.: ‘Risk-based reconfiguration of active electric distribution networks’, IET Gener. Transm. Distrib., 2016, 10, (4), pp. 10061015.
    20. 20)
      • 20. Ramanathan, B., Hennessy, D.A., Brown, R.E.: ‘Decision-making and policy implications of performance-based regulation’. Power Systems Conf. Exposition, Atlanta, GA, USA, October 2006, pp. 394401.
    21. 21)
      • 21. Abiri-Jahromi, A., Fotuhi-Firuzabad, M., Abbasi, E.: ‘An efficient mixed-integer linear formulation for long-term overhead lines maintenance scheduling in power distribution systems’, IEEE Trans. Power Deliv., 2009, 24, (4), pp. 20432053.
    22. 22)
      • 22. Alvehag, K., Awodele, K., ‘Impact of reward and penalty scheme on the incentives for distribution system reliability’, IEEE Trans. Power Syst., 2014, 29, (1), pp. 386394.
    23. 23)
      • 23. Simab, M., Alvehag, K., Söder, L., et al: ‘Designing reward and penalty scheme in performance-based regulation for electric distribution companies’, IET Gener. Transm. Distrib., 2012, 6, (9), pp. 893901.
    24. 24)
      • 24. Mohammadnezhad-Shourkaei, H., Fotuhi-Firuzabad, M.: ‘Impact of penalty–reward mechanism on the performance of electric distribution systems and regulator budget’, IET Gener. Transm. Distrib., 2010, 4, (7), pp. 770779.
    25. 25)
      • 25. Short, T.A.: ‘Electric power distribution handbook’ (CRC Press, Boca Raton, FL, USA, 2014).
    26. 26)
      • 26. Billinton, R., Pan, Z., ‘Historic performance-based distribution system risk assessment’, IEEE Trans. Power Deliv., 2004, 19, (4), pp. 17591765.
    27. 27)
      • 27. Allan, R. N., Billinton, R., Sjarief, I., et al: ‘A reliability test system for educational purposes-basic distribution system data and results’, IEEE Trans. Power Syst., 1991, 6, (2), pp. 813820.
    28. 28)
      • 28. Hejazi, H., Araghi, A.R., Vahidi, B., et al: ‘Independent distributed generation planning to profit both utility and DG investors’, IEEE Trans. Power Syst., 2013, 28, (2), pp. 11701178.
    29. 29)
      • 29. Küfeoğlu, S., Lehtonen, M.: ‘Comparison of different models for estimating the residential sector customer interruption costs’, Electr. Power Syst. Res., 2015, 122, pp. 5055.
    30. 30)
      • 30. Küfeoğlu, S., Lehtonen, M.: ‘Interruption costs of service sector electricity customers, a hybrid approach’, Int. J. Electr. Power Energy Syst., 2015, 64, pp. 588595.
    31. 31)
      • 31. Brown, R.E.: ‘System reliability and power quality: performance-based rates and guarantees’. Power Engineering Society Summer Meeting, Chicago, IL, USA, July 2002, pp. 784787.

Related content

This is a required field
Please enter a valid email address