An Approach for Evaluating Incentive Policy of Wind Resources Considering the Uncertainties in the Deregulated Power Market

Tolou Askari, M.

doi:10.22061/jecei.2022.8980.563

تعداد نشریات	11
تعداد شماره‌ها	237
تعداد مقالات	2,398
تعداد مشاهده مقاله	3,830,612
تعداد دریافت فایل اصل مقاله	2,775,223

	An Approach for Evaluating Incentive Policy of Wind Resources Considering the Uncertainties in the Deregulated Power Market
Journal of Electrical and Computer Engineering Innovations (JECEI)
دوره 11، شماره 1، فروردین 2023، صفحه 203-216 اصل مقاله (963.25 K)
نوع مقاله: Original Research Paper
شناسه دیجیتال (DOI): 10.22061/jecei.2022.8980.563
نویسنده
M. Tolou Askari^*
Department of Electrical and Electronic Engineering, Semnan Branch, Islamic Azad University, Semnan, Iran.
تاریخ دریافت: 03 تیر 1401، تاریخ بازنگری: 24 مرداد 1401، تاریخ پذیرش: 04 مهر 1401
چکیده
Background and Objectives: Development of intermittent wind generation has necessitated the inclusion of several creative approaches in modeling the deregulated power market with presence of wind sources. The uncertain nature of wind resources will cause the private companies meet several risk in their medium and long term planning in a restructured power market. In addition to considering the uncertainties such as load, fuel costs, wind power generation and technical actions of rivals for modeling the restructured power market, the regulatory policies i.e incentive policy for wind resources and Carbon tax should be assumed in this approach. Methods: The first contribution of this article is to propose a developed mathematical model in order to evaluate the medium term deregulated power market by assuming the hybrid wind-thermal power plants. The second contribution is to evaluate the impact of different types of Feed in Tariff supports on Market Clearing Price, Expected Cost for Government, profits and contribution of each firm in electricity generation in the restructured power market. Also the scenario based method has been used to generate the scenarios for wind uncertainties and then their reliability validate based on the statistical methods. Results: The proposed mathematical model in the first contribution is calculated for each season and load levels based on the proposed wind scenarios. The functionality and feasibility of this model is demonstrated by simulation studies. Conclusion: The proposed model in this article can be so useful for evaluating the different types of incentive policies for renewable energies. Moreover, this study confirms the previous researches that selected the Feed in Tariff as an efficient approach for developing the wind resources.
کلیدواژه‌ها
Restructured power market؛ Wind resources؛ Feed in Tariff؛ Game theory

مراجع
[1] P. Brown, "European Union Wind and Solar Electricity Policies: Overview and Considerations," 2013. [2] C.-D. Yue, C.-M. Liu, E. M. Liou, "A transition toward a sustainable energy future: feasibility assessment and development strategies of wind power in Taiwan," Energy Policy, 29: 951-963, 2001. [3] R. Saidur, M. Islam, N. Rahim, K. Solangi, "A review on global wind energy policy," Renewable Sustainable Energy Rev., 14: 1744-1762, 2010. [4] M. Askari, M. Ab Kadir, H. Hizam, J. Jasni, "A new comprehensive model to simulate the restructured power market for seasonal price signals by considering on the wind resources," J. Renewable Sustainable Energy, 6: 023104, 2014. [5] M. Askari et al., “Modeling optimal long-term investment strategies of hybrid wind-thermal companies in restructured power market,” J. Mod. Power Syst. Clean Energy, 7: 1267–1279, 2019. [6] P. Harborne, C. Hendry, "Pathways to commercial wind power in the US, Europe and Japan: The role of demonstration projects and field trials in the innovation process," Energy Policy, 37: 3580-3595, 2009. [7] T. Ackermann, L. Söder, "An overview of wind energy-status 2002," Renewable Sustainable Energy Rev., 6: 67-127, 2002. [8] T. Barforoushi, M. Parsa Moghaddam, M. Javidi, M. Sheik-El-Eslami, "A new model considering uncertainties for power market simulation in medium-term generation planning," Iran. J. Electr. Electron. Eng. (IJEEE), 2: 71-81, 2006. [9] T. Barforoushi, M. P. Moghaddam, M. H. Javidi, M. K. Sheikh-El-Eslami, "Evaluation of regulatory impacts on dynamic behavior of investments in electricity markets: a new hybrid DP/GAME framework," IEEE Trans. Power Syst., 25: 1978-1986, 2010. [10] D. Kothari, I. Nagrath, Modern power system analysis: McGraw-Hill Europe, 2003. [11] A. S. Chuang, F. Wu, P. Varaiya, "A game-theoretic model for generation expansion planning: problem formulation and numerical comparisons," IEEE Trans. Power Syst., 16: 885-891, 2001. [12] J. B. Park, J. H. Kim, K. Y. Lee, "Generation expansion planning in a competitive environment using a genetic algorithm," 3: 1169-1172, 2002. [13] W. M. Lin, T. S. Zhan, M. T. Tsay, W. C. Hung, "The generation expansion planning of the utility in a deregulated environment," 2: 702-707, 2004. [14] J. Zhu, M. Chow, "A review of emerging techniques on generation expansion planning," IEEE Trans. Power Syst., 12: 1722-1728, 1997. [15] E. Alishahi, M. P. Moghaddam, M. Sheikh-El-Eslami, "A system dynamics approach for investigating impacts of incentive mechanisms on wind power investment," Renewable Energy, 37: 310-317, 2012. [16] G. Richards, B. Noble, K. Belcher, "Barriers to renewable energy development: A case study of large-scale wind energy in Saskatchewan, Canada," Energy Policy, 42: 691-698, 2012. [17] J. M. Kissel, S. C. Krauter, "Adaptations of renewable energy policies to unstable macroeconomic situations—Case study: Wind power in Brazil," Energy Policy, 34: 3591-3598, 2006. [18] V. Di Dio, S. Favuzza, D. La Cascia, R. Miceli, "Economical Incentives and systems of certification for the production of electrical energy from renewable energy resources," in Proc. International Conference on Clean Electrical Power (ICCEP'07): 277-282, 2007. [19] J. P. Painuly, "Barriers to renewable energy penetration; a framework for analysis," Renewable Energy, 24: 73-89, 2001. [20] L. Ying, C. Yin, R. Yuan, H. Yong, "Economic incentive mechanism of renewable energy generation," in Proc. International Conference on Electrical Machines and Systems (ICEMS): 2689-2694, 2008. [21] L. A. Barroso, H. Rudrick, F. Sensfuss, P. Linares, "The green effect," IEEE Power Energy Magazine, 8: 22-35, 2010. [22] J. Sawin, "National policy instruments: Policy lessons for the advancement & diffusion of renewable energy technologies around the world," Renewable Energy, A Global Review of Technologies, Policies and Markets, 2006. [23] J. Lipp, "Lessons for effective renewable electricity policy from Denmark, Germany and the United Kingdom," Energy Policy, 35: 5481-5495, 2007. [24] V. Lauber, L. Mez, "Three decades of renewable electricity policies in Germany," Energy & Environment, 15: 599-623, 2004. [25] M. Askari, M. Ab Kadir, E. Bolandifar, "Evaluation of FIT impacts on market clearing price in the restructured power market," in Proc. 2015 IEEE Student Conference on Research and Development (SCOReD): 224-227, 2015. [26] S. Ahmad, R. M. Tahar, F. Muhammad-Sukki, A. B. Munir, R. A. Rahim, "Application of system dynamics approach in electricity sector modelling: A review," Renewable Sustainable Energy Rev., 56: 29-37, 2016. [27] A. Ibanez-Lopez, J. Martinez-Val, B. Moratilla-Soria, "A dynamic simulation model for assessing the overall impact of incentive policies on power system reliability, costs and environment," Energy Policy, 102: 170-188, 2017. [28] F. Zia, M. Nasir, A. A. Bhatti, "Optimization methods for constrained stochastic wind power economic dispatch," in Proc. 7th IEEE International Power Engineering and Optimization Conference (PEOCO): 129-133, 2013. [29] X. Liu, W. Xu, "Economic load dispatch constrained by wind power availability: A here-and-now approach," IEEE Trans. Sustainable Energy, 1(1): 2-9, 2010. [30] L. A. Barroso, A. J. Conejo, "Decision making under uncertainty in electricity markets," in Proc. IEEE Power Engineering Society General Meeting, 2006. [31] A.J. Conejo, M. Carriâon, J. M. Morales, Decision making under uncertainty in electricity markets , 153: Springer, 2010. [32] R. Karki, P. Hu, R. Billinton, "A simplified wind power generation model for reliability evaluation," IEEE Trans. Energy Convers., 21: 533-540, 2006. [33] (2006). Canada’s National Climate Archive [online]. [34] M.J. Osborne, An introduction to game theory vol. 3: Oxford University Press New York, 2004. [35] A.S. Chuang, F. Wu, P. Varaiya, "A game-theoretic model for generation expansion planning: problem formulation and numerical comparisons," IEEE Trans. Power Syst., 16: 885-891, 2001. [36] D. Kirschen, G. Strbac, Front Matter: Wiley Online Library, 2005. [37] H. Singh, "Introduction to game theory and its application in electric power markets," IEEE Comput. Appl. Power, 12(4): 18-20, 1999. [38] C. Grigg, P. Wong, P. Albrecht, R. Allan, M. Bhavaraju, R. Billinton, et al., "The IEEE reliability test system-1996. A report prepared by the reliability test system task force of the application of probability methods subcommittee," IEEE Trans. Power Syst., 14: 1010-1020, 1999. [39] E. Gnansounou, J. Dong, S. Pierre, A. Quintero, "Market oriented planning of power generation expansion using agent-based model," in Proc. IEEE Power Systems Conference and Exposition: 1306-1311, 2004. [40] M. Shahidehpour, H. Yamin, Z. Li, "Market operations in electric power systems, 2002," ed: John Wiley & Sons, Inc. New York. [41] T. Barforoushi, M. P. Moghaddam, M. H. Javidi, M. K. Sheikh-El-Eslami, "Evaluation of regulatory impacts on dynamic behavior of investments in electricity markets: a new hybrid DP/GAME framework," IEEE Trans. Power Syst., 25: 1978-1986, 2010.
آمار تعداد مشاهده مقاله: 435 تعداد دریافت فایل اصل مقاله: 416

سامانه مدیریت نشریات علمی. طراحی و پیاده سازی از سیناوب

پیوندهای مفید

آمار

An Approach for Evaluating Incentive Policy of Wind Resources Considering the Uncertainties in the Deregulated Power Market