IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v35y2010i12p4996-5007.html
   My bibliography  Save this article

AGA (Asset Governance Assessment) for analyzing affect of subsidy on MC (Marginal Cost) in electricity distribution sector

Author

Listed:
  • Dashti, Reza
  • Afsharnia, Saeed
  • Ghaderi, Farid

Abstract

Nowadays subsidy payments on electrical energy have to be managed and controlled to prevent any side effect particularly in developing countries. Effects of some external factors on Energy consumption and electricity distribution indices are analyzed in this paper. External factors are classified into three categories of social behavior, governance and urban planning. MC (Marginal Cost) of electricity in distribution is considered as the main index to be analyzed. Also, ANN (Artificial Neural Network) is applied to simulate effect of the mentioned factors on MC of distribution sector. Numerical investigation on the indices for a sample DISCO (Distribution Company) in Iran is made, results indicate that the more subsidies are allocated to consumers the more MC is increased. AGA (Asset Governance Assessment), which is proposed as a kind of governance decision, could improve the performance efficiency and avoid lose of activities done by DISCOs through subsidy management.

Suggested Citation

  • Dashti, Reza & Afsharnia, Saeed & Ghaderi, Farid, 2010. "AGA (Asset Governance Assessment) for analyzing affect of subsidy on MC (Marginal Cost) in electricity distribution sector," Energy, Elsevier, vol. 35(12), pages 4996-5007.
    • Handle: RePEc:eee:energy:v:35:y:2010:i:12:p:4996-5007
    DOI: 10.1016/j.energy.2010.08.022
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544210004585
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2010.08.022?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. Pilavachi, P.A. & Kalampalikas, N.G. & Kakouris, M.K. & Kakaras, E. & Giannakopoulos, D., 2009. "The energy policy of the Republic of Cyprus," Energy, Elsevier, vol. 34(5), pages 547-554.
    2. Moe, Espen, 2010. "Energy, industry and politics: Energy, vested interests, and long-term economic growth and development," Energy, Elsevier, vol. 35(4), pages 1730-1740.
    3. Clastres, C. & Ha Pham, T.T. & Wurtz, F. & Bacha, S., 2010. "Ancillary services and optimal household energy management with photovoltaic production," Energy, Elsevier, vol. 35(1), pages 55-64.
    4. Lam, Pun-Lee, 2004. "Pricing of electricity in China," Energy, Elsevier, vol. 29(2), pages 287-300.
    5. Woo, C.K. & Orans, Ren & Horii, Brian & Pupp, Roger & Heffner, Grayson, 1994. "Area- and time-specific marginal capacity costs of electricity distribution," Energy, Elsevier, vol. 19(12), pages 1213-1218.
    6. Yuan, Chaoqing & Liu, Sifeng & Xie, Naiming, 2010. "The impact on chinese economic growth and energy consumption of the Global Financial Crisis: An input–output analysis," Energy, Elsevier, vol. 35(4), pages 1805-1812.
    7. Kumar, Ujjwal & Jain, V.K., 2010. "Time series models (Grey-Markov, Grey Model with rolling mechanism and singular spectrum analysis) to forecast energy consumption in India," Energy, Elsevier, vol. 35(4), pages 1709-1716.
    8. Sheen, J.N., 2006. "Incentive pricing and economic profitability of load management program," Energy, Elsevier, vol. 31(12), pages 2193-2209.
    9. Deng, Shi-Jie & Xu, Li, 2009. "Mean-risk efficient portfolio analysis of demand response and supply resources," Energy, Elsevier, vol. 34(10), pages 1523-1529.
    10. Ekonomou, L., 2010. "Greek long-term energy consumption prediction using artificial neural networks," Energy, Elsevier, vol. 35(2), pages 512-517.
    11. Markovska, N. & Taseska, V. & Pop-Jordanov, J., 2009. "SWOT analyses of the national energy sector for sustainable energy development," Energy, Elsevier, vol. 34(6), pages 752-756.
    12. Wang, Jianzhou & Zhu, Suling & Zhang, Wenyu & Lu, Haiyan, 2010. "Combined modeling for electric load forecasting with adaptive particle swarm optimization," Energy, Elsevier, vol. 35(4), pages 1671-1678.
    13. Baarsma, Barbara E. & Hop, J. Peter, 2009. "Pricing power outages in the Netherlands," Energy, Elsevier, vol. 34(9), pages 1378-1386.
    14. Dixon, Gene & Abdel-Salam, Tarek & Kauffmann, Paul, 2010. "Evaluation of the effectiveness of an energy efficiency program for new home construction in eastern North Carolina," Energy, Elsevier, vol. 35(3), pages 1491-1496.
    15. Warr, B.S. & Ayres, R.U., 2010. "Evidence of causality between the quantity and quality of energy consumption and economic growth," Energy, Elsevier, vol. 35(4), pages 1688-1693.
    16. Zhu, Lei & Fan, Ying, 2010. "Optimization of China's generating portfolio and policy implications based on portfolio theory," Energy, Elsevier, vol. 35(3), pages 1391-1402.
    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. Dashti, Reza & Yousefi, Shaghayegh & Parsa Moghaddam, Mohsen, 2013. "Comprehensive efficiency evaluation model for electrical distribution system considering social and urban factors," Energy, Elsevier, vol. 60(C), pages 53-61.
    2. Kim, Jin-Ho & Shcherbakova, Anastasia, 2011. "Common failures of demand response," Energy, Elsevier, vol. 36(2), pages 873-880.
    3. Zohreh Salimian & Marjan Kordbacheh & Mehdi Sadeghi Shahdani & Vahab Mokarizadeh, 2012. "Analyzing the Effects of the Iranian Energy Subsidy Reform Plan on Short-Run Marginal Generation Cost of Electricity Using Extended Input-Output Price Model," International Journal of Energy Economics and Policy, Econjournals, vol. 2(4), pages 250-262.
    4. Daneshzand, Farzaneh & Asali, Mehdi & Al-Sobhi, Saad A. & Diabat, Ali & Elkamel, Ali, 2022. "A simulation-based optimization scheme for phase-out of natural gas subsidies considering welfare and economic measures," Energy, Elsevier, vol. 259(C).
    5. Ghasemi, Mostafa & Dashti, Reza, 2018. "Designing a decision model to assess the reward and penalty scheme of electric distribution companies," Energy, Elsevier, vol. 147(C), pages 329-336.

    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. Wu, Zhibin & Xu, Jiuping, 2013. "Predicting and optimization of energy consumption using system dynamics-fuzzy multiple objective programming in world heritage areas," Energy, Elsevier, vol. 49(C), pages 19-31.
    2. Gholami, M. & Barbaresi, A. & Torreggiani, D. & Tassinari, P., 2020. "Upscaling of spatial energy planning, phases, methods, and techniques: A systematic review through meta-analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
    3. An, Ning & Zhao, Weigang & Wang, Jianzhou & Shang, Duo & Zhao, Erdong, 2013. "Using multi-output feedforward neural network with empirical mode decomposition based signal filtering for electricity demand forecasting," Energy, Elsevier, vol. 49(C), pages 279-288.
    4. Kim, Jin-Ho & Shcherbakova, Anastasia, 2011. "Common failures of demand response," Energy, Elsevier, vol. 36(2), pages 873-880.
    5. Suganthi, L. & Samuel, Anand A., 2012. "Energy models for demand forecasting—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(2), pages 1223-1240.
    6. Debnath, Kumar Biswajit & Mourshed, Monjur, 2018. "Forecasting methods in energy planning models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 297-325.
    7. Min, Daiki & Chung, Jaewoo, 2013. "Evaluation of the long-term power generation mix: The case study of South Korea's energy policy," Energy Policy, Elsevier, vol. 62(C), pages 1544-1552.
    8. Movagharnejad, Kamyar & Mehdizadeh, Bahman & Banihashemi, Morteza & Kordkheili, Masoud Sheikhi, 2011. "Forecasting the differences between various commercial oil prices in the Persian Gulf region by neural network," Energy, Elsevier, vol. 36(7), pages 3979-3984.
    9. Wu, Qunli & Peng, Chenyang, 2017. "A hybrid BAG-SA optimal approach to estimate energy demand of China," Energy, Elsevier, vol. 120(C), pages 985-995.
    10. Yuan, Chaoqing & Liu, Sifeng & Fang, Zhigeng, 2016. "Comparison of China's primary energy consumption forecasting by using ARIMA (the autoregressive integrated moving average) model and GM(1,1) model," Energy, Elsevier, vol. 100(C), pages 384-390.
    11. DeBenedictis, A. & Hoff, T.E. & Price, S. & Woo, C.K., 2010. "Statistically adjusted engineering (SAE) modeling of metered roof-top photovoltaic (PV) output: California evidence," Energy, Elsevier, vol. 35(10), pages 4178-4183.
    12. Emre Yakut & Ezel Özkan, 2020. "Modeling of Energy Consumption Forecast with Economic Indicators Using Particle Swarm Optimization and Genetic Algorithm: An Application in Turkey between 1979 and 2050," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 8(1), pages 59-78, June.
    13. Reza Hafezi & Amir Naser Akhavan & Mazdak Zamani & Saeed Pakseresht & Shahaboddin Shamshirband, 2019. "Developing a Data Mining Based Model to Extract Predictor Factors in Energy Systems: Application of Global Natural Gas Demand," Energies, MDPI, vol. 12(21), pages 1-22, October.
    14. Tyralis, Hristos & Karakatsanis, Georgios & Tzouka, Katerina & Mamassis, Nikos, 2017. "Exploratory data analysis of the electrical energy demand in the time domain in Greece," Energy, Elsevier, vol. 134(C), pages 902-918.
    15. Pérez Odeh, Rodrigo & Watts, David & Flores, Yarela, 2018. "Planning in a changing environment: Applications of portfolio optimisation to deal with risk in the electricity sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3808-3823.
    16. Carvalho, Ariovaldo Lopes de & Antunes, Carlos Henggeler & Freire, Fausto & Henriques, Carla Oliveira, 2015. "A hybrid input–output multi-objective model to assess economic–energy–environment trade-offs in Brazil," Energy, Elsevier, vol. 82(C), pages 769-785.
    17. Yu, Shi-wei & Zhu, Ke-jun, 2012. "A hybrid procedure for energy demand forecasting in China," Energy, Elsevier, vol. 37(1), pages 396-404.
    18. Chaturvedi, Shobhit & Rajasekar, Elangovan & Natarajan, Sukumar & McCullen, Nick, 2022. "A comparative assessment of SARIMA, LSTM RNN and Fb Prophet models to forecast total and peak monthly energy demand for India," Energy Policy, Elsevier, vol. 168(C).
    19. Che, Jinxing & Wang, Jianzhou & Wang, Guangfu, 2012. "An adaptive fuzzy combination model based on self-organizing map and support vector regression for electric load forecasting," Energy, Elsevier, vol. 37(1), pages 657-664.
    20. Huang, Liqiao & Liao, Qi & Qiu, Rui & Liang, Yongtu & Long, Yin, 2021. "Prediction-based analysis on power consumption gap under long-term emergency: A case in China under COVID-19," Applied Energy, Elsevier, vol. 283(C).

    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:35:y:2010:i:12:p:4996-5007. 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.