Development of Iran's Electricity Transmission Capacity, Based on Forecasting the Demand Trend Using the System Dynamics Approach

Journal of Systems Thinking in Practice

دوره 3، شماره 3 - شماره پیاپی 10، آذر 2024، صفحه 91-118   

نوع مقاله: Research Article

شناسه دیجیتال (DOI): 10.22067/jstinp.2024.87596.1102

نویسندگان

Mohammad Taghi Farahnak¹؛ Mohammad Ali Afshar Kazemi¹؛ Ali Mohaghar^{* 2}؛ Mohammad Ali Keramati¹

¹Department of Industrial Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran.

²Department of Industrial management, Faculty of Management, University of Tehran, Tehran, Iran.

چکیده

This research models and simulates the development of transmission capacity considering electricity supply and demand dynamics. After presenting a causal loop diagram and designing a stock and flow diagram, the model's validity is confirmed using validation methods for system dynamics models. The analysis then proceeds to scenarios for the total electricity demand in Iran. Firstly, the country's electricity demand structure is broken into industrial, household, agricultural, and other sectors. By studying consumption trends in each sector, linear and nonlinear regression are used to predict total electricity demand. Next, three scenarios - optimistic, moderate, and pessimistic - are defined in terms of electricity demand, and the required transmission capacity is calculated and designed for 400, 230, 132, and 63-66 kilovolt substations to cover and meet future electricity demand over twenty years. The research findings over a 20-year horizon indicate that in the moderate scenario, where electricity demand increases by 90 percent, the transmission capacity needs to increase by 106 percent to meet the demand. In the optimistic scenario, where electricity demand increases by 71 percent, the transmission capacity needs to increase by 85 percent. In the pessimistic scenario, where electricity demand increases by 110 percent, the transmission capacity needs to increase by 126 percent.

کلیدواژه‌ها

System dynamics؛ Power transmission capacity؛ Expected power demand؛ Power transmission capacity development

مراجع

Ahmad, S., Tahar, R.M., Muhammad-Sukki, F., Munir, A.B. and Rahim, R.A., 2016. Application of system dynamics approach in electricity sector modelling: A review. Renewable and Sustainable Energy Reviews, 56, pp.29-37. https://doi.org/10.1016/j.rser.2015.11.034.

Ahmadvand, A.M., Kalantari Hermzi, M., 2019. Dynamic Investment Model in Power Distribution Capacity Development, In The Second National Conference of the Iranian System Dynamics Society, Tehran. [in Persian].

Contreras, J., Gross, G., Arroyo, J.M. and Muñoz, J.I., 2009. An incentive-based mechanism for transmission asset investment. Decision Support Systems, 47(1), pp.22-31. https://doi.org/10.1016/j.dss.2008.12.005.

Dehghan, H., Amin-Naseri, M.R. and Nahavandi, N., 2021. A system dynamics model to analyze future electricity supply and demand in Iran under alternative pricing policies. Utilities Policy, 69, p.101165. https://doi.org/10.1016/j.jup.2020.101165.

Dianat, F., Hosseini, S.H. and Shakouri Ganjavi, H., 2021. Systemic Modeling of Renewable Electricity Generation Expansion Planning in Competition with Conventional Electricity. Journal of Energy Planning And Policy Research, 7(1), pp.7-50. URL: http://epprjournal.ir/article-1-945-en.html.[in Persian].

Dismukes, D.E., Cope III, R.F. and Mesyanzhinov, D., 1998. Capacity and economies of scale in electric power transmission. Utilities Policy, 7(3), pp.155-162. https://doi.org/10.1016/S0957-1787(98)00010-1.

Ford, A., 2001. Waiting for the boom:: a simulation study of power plant construction in California. Energy policy, 29(11), pp.847-869. https://doi.org/10.1016/S0301-4215(01)00035-0.

Grandón, T.G., Schwenzer, J., Steens, T. and Breuing, J., 2024. Electricity demand forecasting with hybrid classical statistical and machine learning algorithms: Case study of Ukraine. Applied Energy, 355, p.122249. https://doi.org/10.1016/j.apenergy.2023.122249.

He, Y.X., Jiao, J., Chen, R.J. and Shu, H., 2018. The optimization of Chinese power grid investment based on transmission and distribution tariff policy: A system dynamics approach. Energy Policy, 113, pp.112-122. https://doi.org/10.1016/j.enpol.2017.10.062.

Kucuksayacigil, F. and Min, K.J., 2021. A lattice method for jump-diffusion process applied to transmission expansion investments under demand and distributed generation uncertainties. Energy Systems, 12, pp.773-800. https://doi.org/10.1007/s12667-020-00385-w.

Li, J., Luo, Y. and Wei, S., 2022. Long-term electricity consumption forecasting method based on system dynamics under the carbon-neutral target. Energy, 244, p.122572. https://doi.org/10.1016/j.energy.2021.122572.

Loh, J.R. and Bellam, S., 2024. Towards net zero: Evaluating energy security in Singapore using system dynamics modelling. Applied Energy, 358, p.122537. https://doi.org/10.1016/j.apenergy.2023.122537.

Mateo-Barcos, S., Ribó-Pérez, D., Rodríguez-García, J. and Alcázar-Ortega, M., 2024. Forecasting electricity demand of municipalities through artificial neural networks and metered supply point classification. Energy Reports, 11, pp.3533-3549. https://doi.org/10.1016/j.egyr.2024.03.023.

Meira, E., Lila, M.F. and Oliveira, F.L.C., 2023. A novel reconciliation approach for hierarchical electricity consumption forecasting based on resistant regression. Energy, 269, p.126794. https://doi.org/10.1016/j.energy.2023.126794.

Mohaghar, A. and Najafzadeh, K., 2017. A System Dynamics Model for Enhancing Capacity of Electricity Generation in Iran. Management and Development Process, 30(2), pp.145-172. http://dorl.net/dor/20.1001.1.17350719.1396.30.2.2.8. [in Persian].

Monjazeb, M. and Rezaei Movahed, B., 2019. Forcasting Electricity Losses in Transmission and Distribution Grids: System Dynamics Approach Compared to Econometric Method. Journal of Energy Planning And Policy Research, 5(3), pp.151-182. URL: http://epprjournal.ir/article-1-420-en.html. [in Persian].

Nahavandi, N. and Najafzadeh, K., 2012. Comparison of Demand Side Control and Supply Side Development Of Electricity Energy by System Dynamics Approach. International Journal of Industrial Engineering, 22(4), pp.341-358. [in Persian].

Pe, W.H.B., 2003. Analysis of transformer failures, In 36th Annual Conference of International Association of Engineering Insurers–Stockholm.

Pereira, A.J. and Saraiva, J.T., 2013. A long term generation expansion planning model using system dynamics–Case study using data from the Portuguese/Spanish generation system. Electric Power Systems Research, 97, pp.41-50. https://doi.org/10.1016/j.epsr.2012.12.001.

Pourkashani, H and Babaei, S., 2003. Recognition of Loss Factors in the Transmission and Sub-Distribution Network of Tehran. In 4th Electricity Industry Quality and Productivity Conference, Tehran, Iran. https://civilica.com/doc/70903. [in Persian].

Qudrat-Ullah, H., 2013. Understanding the dynamics of electricity generation capacity in Canada: A system dynamics approach. Energy, 59, pp.285-294. https://doi.org/10.1016/j.energy.2013.07.029.

Qureshi, M., Arbab, M.A. and Rehman, S.U., 2024. Deep learning-based forecasting of electricity consumption. Scientific Reports, 14(1), p.6489. https://doi.org/10.1038/s41598-024-56602-4.

Rajabi Mashhadi, M., 2018. Power Industry Strategies for Supplying Transformers in the Power Network of Iran, In 5th International Transformer Conference and Exhibition. Presidential Cultural Institution. [in Persian].

Rao, C., Zhang, Y., Wen, J., Xiao, X. and Goh, M., 2023. Energy demand forecasting in China: A support vector regression-compositional data second exponential smoothing model. Energy, 263, p.125955. https://doi.org/10.1016/j.energy.2022.125955.

Romero-Quete, A.A., Mombello, E.E. and Rattá, G., 2016. Assessing the loss-of-insulation life of power transformers by estimating their historical loads and ambient temperature profiles using ANNs and Monte Carlo simulations. Dyna, 83(197), pp.104-113.

Saad, N.M., Ibrahim, J., Husin, N.M. and Abdullah, Z., 2020. The Impact of Electricity Tariff towards Cost of Production among Sectors in Malaysia. Global Business & Management Research, 12(4).

Sha, M., Chen, S., Gao, M., Chen, Y., Wang, Z. and Tian, Y., 2018, July. Research on the Investments Allocation of Comprehensive Plan of Power Grid Enterprises under the Electricity Transmission and Distribution Price Reformation. In IOP Conference Series: Earth and Environmental Science (Vol. 170, No. 4, p. 042022). IOP Publishing. https://doi.org/10.1088/1755-1315/170/4/042022.

Shiu, H.Y., Lee, M., Lin, Z.E. and Chiueh, P.T., 2023. Dynamic life cycle assessment for water treatment implications. Science of the Total Environment, 860, p.160224. https://doi.org/10.1016/j.scitotenv.2022.160224.

Sterman, J., 2002. System Dynamics: systems thinking and modeling for a complex world. URI: http://hdl.handle.net/1721.1/102741.

Strbac, G., Pollitt, M., Konstantinidis, C.V., Konstantelos, I., Moreno, R., Newbery, D. and Green, R., 2014. Electricity transmission arrangements in Great Britain: Time for change?. Energy Policy, 73, pp.298-311. https://doi.org/10.1016/j.enpol.2014.06.014.

Tavanir, 2022. 55 Years of Iran’s Power Industry (1967-2021). [in Persian].

Ude, N.G., Yskandar, H. and Graham, R.C., 2019. A comprehensive state-of-the-art survey on the transmission network expansion planning optimization algorithms. IEEE Access, 7, pp.123158-123181. https://doi.org/10.1109/ACCESS.2019.2936682.

Zahari, T.N. and McLellan, B.C., 2023. Review of Policies for Indonesia’s Electricity Sector Transition and Qualitative Evaluation of Impacts and Influences Using a Conceptual Dynamic Model. Energies, 16(8), p.3406. https://doi.org/10.3390/en16083406.

Zambrano, C., Arango-Aramburo, S. and Olaya, Y., 2019. Dynamics of power-transmission capacity expansion under regulated remuneration. International Journal of Electrical Power & Energy Systems, 104, pp.924-932. https://doi.org/10.1016/j.ijepes.2018.07.029.