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Khalili, Saeed, Abbasi, Ebrahim, Behnia, Bardia, Amirkhan, Mohammad. (1400). Proposing a New Mathematical Model for Optimizing the Purchase of Electricity Required by Large Consumers Based on Modern Portfolio Theory: A Case Study of the Iranian Electricity Market. , 56(1), 87-113. doi: 10.22059/aie.2022.339757.1829
Saeed Khalili; Ebrahim Abbasi; Bardia Behnia; Mohammad Amirkhan. "Proposing a New Mathematical Model for Optimizing the Purchase of Electricity Required by Large Consumers Based on Modern Portfolio Theory: A Case Study of the Iranian Electricity Market". , 56, 1, 1400, 87-113. doi: 10.22059/aie.2022.339757.1829
Khalili, Saeed, Abbasi, Ebrahim, Behnia, Bardia, Amirkhan, Mohammad. (1400). 'Proposing a New Mathematical Model for Optimizing the Purchase of Electricity Required by Large Consumers Based on Modern Portfolio Theory: A Case Study of the Iranian Electricity Market', , 56(1), pp. 87-113. doi: 10.22059/aie.2022.339757.1829
Khalili, Saeed, Abbasi, Ebrahim, Behnia, Bardia, Amirkhan, Mohammad. Proposing a New Mathematical Model for Optimizing the Purchase of Electricity Required by Large Consumers Based on Modern Portfolio Theory: A Case Study of the Iranian Electricity Market. , 1400; 56(1): 87-113. doi: 10.22059/aie.2022.339757.1829

Proposing a New Mathematical Model for Optimizing the Purchase of Electricity Required by Large Consumers Based on Modern Portfolio Theory: A Case Study of the Iranian Electricity Market

Advances in Industrial Engineering
دوره 56، شماره 1، فروردین 2022، صفحه 87-113    اصل مقاله (1.11 M)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22059/aie.2022.339757.1829
نویسندگان
Saeed Khalili1؛ Ebrahim Abbasi* 2؛ Bardia Behnia3؛ Mohammad Amirkhan4
1Department of Industrial Management, Aliabad Katoul Branch, Islamic Azad University, Aliabad Katoul, Iran.
2Department of Management, Faculty of Social Sciences and Economics, Alzahra University, Tehran, Iran.
3Department of Industrial Engineering and Management, Rouzbahan Educational Institute, Sari, Iran.
4Department of Industrial Engineering, Aliabad Katoul Branch, Islamic Azad University, Aliabad Katoul, Iran
چکیده
In deregulated electricity markets, the electricity consumer should optimally divide the necessary electrical energy into different markets such as cash markets with spot prices and bilateral contract markets. This study aims to design a model to optimally select the electrical energy portfolio to minimize purchase costs by considering a risk level. For this purpose, an optimization model is proposed through the modern portfolio theory (MPT), mean-variance analysis, and conditional value-at-risk (CVaR) for cost minimization and risk reduction in the electricity supply problem. The mean-variance and CVaR were used as appropriate criteria for reducing unfavorable states in decision-making under uncertainty. Moreover, an artificial neural network was employed to predict the spot prices of the energy pool and the Iran Energy Exchange (IRENEX). The simulation was based on the actual data of Iran for 2018 and 2019. The entire statistical population was analyzed due to the small number of industrial subscribers, and the proposed model was implemented and executed in MATLAB software. Different sensitivity analyses proved the efficiency of the proposed models. According to the results, if an energy purchaser evades more risks, — i.e., the risk evasion coefficient increases a lower ratio of the electrical energy portfolio is allocated to cash markets, especially the IRENEX. In addition, the CVaR provided electricity markets with a more stable energy allocation than the mean-variance model
کلیدواژه‌ها
Portfolio Optimization؛ Electrical Energy Market؛ Uncertainty؛ Modern Portfolio Theory (MPT)؛ Conditional Value-at-Risk (CVAR)
مراجع
 

       [1]        SafariFarmad, Hadi. "A Novel Risk-based Energy Acquisition Model for a Distribution Company", Iranian Electric Industry Journal of Quality and Productivity.4.(1), pp. 3-13 (2015).

       [2]        Golmohamadi, H., Keypour, R., & Hassanpour, A. "Optimization of a Green Energy Portfolio in a Retail Electricity Market Considering Consumers’ Elasticity", 46 (1) (2016).

       [3]        Sadeghih Hossain, biabany khameneh Kazemi. "Financial Optimization in the Electricity Market", Application of portfolio theory, Iran Journal of Energy., 18 (1) (2015).

       [4]        Mosavizadeh Mirsaeed. "Investigating the efficiency of the energy exchange from the viewpoint of manufacturing companies", Iran Grid Management Company., (2018).   

       [5]        Baraty Masood, Nikkhah Mojdehi Mohammad and Kazemi Ahad. "Optimal Price and Quantity Determination of Retailer Electric Contract and maximizing social welfare in Retail Electrical Power Markets with DG", Optimization and Control., pp. 1-6 (2005).

       [6]        Liu, Min, and Felix F. Wu. "Portfolio optimization in electricity markets." Electric Power systems research, 77(8), pp.1000-1009. (2007):

       [7]        Liu, M., & Wu, F. F. "Risk management in a competitive electricity market", International Journal of Electrical Power & Energy Systems., 29(9), pp. 690-697 (2007).

       [8]        Fabozzi, F. J., Kolm, P. N., Pachamanova, D. A., & Focardi, S. M. Robust "portfolio optimization" The Journal of portfolio management., 33(3), pp. 40-48 (2007).

       [9]        Gökgöz, Fazıl, and Mete Emin Atmaca. "Portfolio optimization under lower partial moments in emerging electricity markets: Evidence from Turkey." Renewable and Sustainable Energy Reviews 67, pp 437-449 (2017)

     [10]      Eichhorn, A., & Romisch, W. "Dynamic risk management in electricity portfolio optimization via polyhedral risk functionals", In 2008 IEEE Power and Energy Society General Meeting-Conversion and Delivery of Electrical Energy in the 21st Century., pp. 1-8 (2008).

     [11]      Zare, K., Conejo, A. J., Carrión, M., & Moghaddam, M. P. "Multi-market energy procurement for a large consumer using a risk-aversion procedure", Electric Power Systems Research., 80(1), pp. 63-70 (2010).

     [12]      Rebennack, S., Kallrath, J., & Pardalos, P. M. "Energy portfolio optimization for electric utilities: case study for Germany", In Energy, Natural Resources and Environmental Economics,. pp. 221-246 (2010).

     [13]      Kettunen, J., Salo, A., & Bunn, D. W. "Optimization of electricity retailer's contract portfolio subject to risk preferences", IEEE Transactions on Power Systems., 25(1), pp. 117-128 (2009).

     [14]      Zare, K., Moghaddam, M. P., & Sheikh-El-Eslami, M. K. "Risk-based electricity procurement for large consumers", IEEE Transactions on Power Systems., 26(4), pp. 1826-1835 (2011).

     [15]      Manotas-Duque, D. F., Oliveros, D. A., Taborda, H. F., Vidal-Holguín, C. J., & Lozano, C. A. "Energy supply optimization for unregulated consumers", Ingeniería y Competitividad., 16(1), pp. 97-107 (2014)

     [16]      Ericsson, Oskar. "Risk Analysis Against Electricity Market Index and Portfolio Optimisation." (2014).

     [17]      Kim, J. H., Kim, W. C., & Fabozzi, F. J. "Recent developments in robust portfolios with a worst-case approach" Journal of Optimization Theory and Applications., 161(1), pp. 103-121 (2014).

     [18]      Mathuria, P., & Bhakar, R. "Integrated risk management model for portfolio selection in multiple markets" In 2014 IEEE PES General Meeting Conference & Exposition., pp.1-5 (2014).

     [19]      Lorca, Á, & Prina, J. "Power portfolio optimization considering locational electricity prices and risk management"  Electric Power Systems Research., 109, pp. 80-89 (2014).

     [20]      Glensk Barbara and Reinhard Madlener "Review of selected Methods for portfolio optimization and Irreversible investment in power generation under uncertainly" Central European Journal of Social Sciences and Humanities., 247. pp. 20-42 (2015).

     [21]      Marrero, G. A., Puch, L. A., & Ramos-Real, F. J. "Mean-variance portfolio methods for energy policy risk management" International Review of Economics & Finance., 40, pp. 246-264 (2015)

     [22]      Garcia, R. C., González, V., Contreras, J., & Custodio, J. E. "Applying modern portfolio theory for a dynamic energy portfolio allocation in electricity markets" Electric Power Systems Research., 150, pp. 11-23 (2017).

     [23]      Algarvio, H., Lopes, F., Sousa, J., & Lagarto, J. "Multi-agent electricity markets: Retailer portfolio optimization using Markowitz theory". Electric Power Systems Research., 148, pp. 282-294 (2017).

     [24]      De Filippo, A., Lombardi, M., & Milano, M. "User-aware electricity price optimization for the competitive market" Energies., 10(9), 1378 (2017).

     [25]      Rocha, P., & Kuhn, D. "Multistage stochastic portfolio optimization in deregulated electricity markets using linear decision rules"  European Journal of Operational Research., 216(2), pp. 397-408  (2012)

     [26]      Ahmadi, S. A., Mirlohi, S. M., Ahmadi, M. H., & Ameri, M. "Portfolio optimization of power plants by using renewable energy in Iran. International Journal of Low-Carbon Technologies"., 16(2), pp. 463-475 (2021)

     [27]      Ah, B., Wang, F., Xie, J., & Sun, X. Electricity Retailer trading portfolio optimization considering risk assessment in the Chinese electricity market" Electric Power Systems Research., 190, 106833, (2021).

     [28]      Faia, R., Pinto, T., Vale, Z., & Corchado, J. M. "Portfolio optimization of electricity markets participation using forecasting error in risk formulation" International Journal of Electrical Power & Energy Systems., 129, 106739, (2021).

     [29]      Ray, J., Bhattacharyya, S., & Singh, N. B. "Conditional Value-at-Risk-Based Portfolio Optimization: An Ant Colony Optimization Approach" In Metaheuristic Approaches to Portfolio Optimization., pp. 82-108, (2019).

     [30]      Faramarz Separi, Abdolreza Sheikholeslami, Taghi Barforoshi. " Risk-Based Optimal Decision-Making by the Retailer in A Mixed Local and Wholesale Market Environment Considering Demand Response Solution" Scientia Iranica., (2021).

     [31]      Hosseini, Seyyed Ebrahim, Mojtaba Najafi, and Ali Akhavein. "Improvement of Regional-Market Management Considering Reserve, Information Gap Decision Theory and Emergency Demand Response Program" Scientia Iranica., (2021).

     [32]      Kavoosi Davoodi, S. M., et al. "An accurate analysis of the parameters affecting consumption and price fluctuations of electricity in the Iranian market in summer" Scientia Iranica., pp. 3538-3550, (2021).

     [33]      Azadi Hematabadi, Ahmad, and Asghar Akbari Foroud. "A New Solution Approach for Supply Function Equilibrium-based Bidding Strategy in Electricity Markets" Scientia Iranica 24.6 3231-3246, (2017).

     [34]      Ghoreishi, S. A., & Khaloozadeh, H. "Optimal Portfolio Allocation based on two Novel Risk Measures and Genetic Algorithm" International Journal of Business and Development Studies., 10(1), pp. 95-113, (2018).

     [35]      Ray, J., Bhattacharyya, S., & Singh, N. B. "Conditional Value-at-Risk-Based Portfolio Optimization: An Ant Colony Optimization Approach" In Metaheuristic Approaches to Portfolio Optimization, IGI Global., pp. 82-108, (2019).

     [36]      Rezaei, F., Najafi, A. A., & Ramezanian, R. "Mean-conditional value at risk model for the stochastic project scheduling problem" Computers & Industrial Engineering., 142, p.106356, (2020).

     [37]      Nazemi, Ali, Siab Mamipour, and Salman Rahimi. "Forecasting the Electricity Price Emphasizing Prices Jumps by Using Combination of Neural and Fuzzy Network with Particle Swarm Optimization Algorithm." Advances in Industrial Engineering 52(2), pp277-290 (2018).

     [38]      Raeiszadeh, Sayyed Ali, Mohammad Ali Dehghan Dehnavi, Mohammad Mahdi Bahrololoum, and Moslem Peymany Foroushany. "Portfolio Selection Optimization Problem Under Systemic Risks." Advances in Industrial Engineering 54(2), 121-140 (2020).
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تعداد مشاهده مقاله: 365
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