Document Type : مقالات پژوهشی

Authors

1 Assistant Professor in Economics and Islamic Banking Department, Economics Faculty, Kharazmi University, Tehran, Iran

2 Management & Economic Sciences Faculty, Ferdowsi University of Mashhad

3 Electrical Engineering Faculty, Sadjad university of technology

Abstract

Renewable energy is derived from the natural processes that are replenished constantly. In its various forms, it derives directly from the sun, or from the deep heat generated from the earth. It isdefined as the electricity and heat being generated from solar, wind, ocean, hydropower, biomass, geothermal resources, biofuels, and the obtained hydrogen from the renewable resources. The renewable energy resources exist over the wide geographical areas in contrast to other energy sources, which are concentrated in a limited number of countries. The rapid deployment of the renewable energy and energy efficiency result in the significant energy security, climate change mitigation, and the economic benefits. The results of a recent review of the literature concluded that as the greenhouse gas (GG) emitters begin to be held liable for the damages emerging from GHG emissions in which lead to the climate change, the liability mitigation value would increase to provide powerful the incentives for the deployment of renewable energy technologies. At the national level, at least 30 nations around the world have already renewable energy contributing to more than 20% of energy supply. The national renewable energy markets are projected to continue to grow strongly in the coming decade and beyond while some 120 countries have various policy targets for the longer-term shares of the renewable energy including the 20 percent of the targeted electricity generated from the European Union by 2020. Some countries have much higher long-term policy targets of up to 100 percent renewables. Outside Europe, a diverse group of 20 or more other countries have targeted the renewable energy shares in the 2020-2030 rangimg from 10 to 50 percent.
This study is an investigation of the climatic characteristics of the regions of Khorasan and the neighboring areas within the interior regions (Semnan, Sistan, Yazd, and Mazandaran) as well as the foreign regions (Turkmenistan and Afghanistan). Besides, it is probingthe technical-economic conditions of the renewable-fossil hybrid power generation along with the impact of the implementation of 2030 renewable energy outlook policies of Khorasan regional electricity hybrid production system as well.
Methodology
Analytic programming was inspired by the numerical methods in Hilbert functional spaces and by GP. The principles of AP are somewhere between these two philosophies: The idea of the evolutionary creation of symbolic solutions arise from GP, whereas the general ideas of the functional spaces and the construction of the resulting function by means of a search process (usually done by the numerical methods such as Ritz or Galerkin method) are adopted from Hilbert spaces. Like GP or GE, AP is based on a set of functions, operators and so-called terminals, which are usually constants or independent variables. All these ‘mathematical’ objects create a set from which AP tries to synthesize an appropriate solution. The main principle of AP is based on Discrete Set Handling (DSH), proposed by Zelinka (2001). DSH can be seen as a universal interface between EA and the problem to be solved symbolically. That is, why AP can be carried out using almost any evolutionary algorithm. The set of the mathematical objects are functions, operators and so-called terminals (usually constants or independent variables). All these objects are mixed together consisting of functions with different number of arguments. Because of the variability of the content of this set, the article purposes of General Functional Set (GFS) is required. The structure of GFS is nested, for instance, it is created by the subsets of functions according to the number of their arguments. The content of GFS is dependent only on a user. Various functions and terminals can be mixed together. The subset structure presence in GFS is vitally important in AP. It is used to avoid the synthesis of the pathological programs, for instance, programs containing functions without arguments, etc. Performance of AP is, of course, improved if functions of GFS are expertly chosen based on the experiencies with the solved problem. The important part of the AP is the sequence of mathematical operations which are used for the program synthesis. These operations are used to categorize the individuals of the society into a suitable program. Mathematically saying, it is mapping the individual domain onto the program domain. This mapping consists of two main parts. The first part is called Discrete Set Handling (DSH) and the second one is the security procedures which do not allow for the pathological programs synthesis.
Results and discussion
Simulation results show that the implementation of 2030 renewable energyies outlook policies will lead to 18.62 TWh optimal inter-regional and trans-regional exports which 2.32 TWh of this optimal export will be generated because of implementation of 2030 renewable energy outlook policies. This 14 percent increase in the inter-regional and trans-regional exports creates 5,000 jobs in Khorasan and increases the associated cost by 32 percent, but there would be little impact on the environmental emissions’ reduction. The related reason for this insignificant reduction in the environmental emissions is the low limited renewable power generation in the production system. Besides, thereason for the significant increase in the price is the high capital cost of the solar and wind production which needs strong financial support from the technical-engineering wind and the solar projects as they share the cost of production with the customers. The maximum potential production capacity in order to cope with the fluctuating nature of the renewable generation, is thebasic attempt for the development of the renewable electricity generation.
Conclusion
Most of the world's leading countries in the field of renewable energy have used Feed-in Tariff to create an affordable price for the renewable power generation systems. It achieves this by offering long-term contracts to renewable energy producers, typically, based on the cost of generation of each technology. In addition, feed-in tariffs often include tariff degression which is amechanism according to which the price (or tariff) ratchets down over time. This is done in order to track and encourage the technological cost reductions. Also, developing the required financial incentives and promoting the standards for connecting the renewable sources to the grid is called for. In addition, the rules regarding the sharing of costs with the common network can also provide the necessary legal and technical infrastructure to make the hybrid production system.

Keywords

[1] Abdi, Hamdi, Hosseinzadeh Khonakdari, T., Zakeri, oven, Razmara, ancient Abbasi, Seyed Hassan Hashemi cotton skew, SE. (2011). Feasibility of 10-megawatt wind farm MoravehTappeh, Journal of Energy, Vol. XIV, No. 37. (in persian)
[2] Alberta Innovates – Technology Futures (AITF). (2011). Energy Storage: Making Intermittent Power Dispatchable, Final Report, Oct 27th, 2011.
[3] Annual Review 2012. (2012). Central Bank of the Islamic Republic of Iran, Tehran. (in persian)
[4] Eslamloyian, K. and Astadzad, A. H. (2012). determine the optimal share of renewable energies in a model of sustainable development: the case of Iran, Journal of Environmental Economics and Energy, Vol. II, No. 5. (in persian)
[5] Bilgen, S., Keles, S., Kaygusuz, A., Sari, A. and Kaygusuz, K. (2008). Global warming and renewable energy sources for sustainable development: a case study in Turkey, Renewable and Sustainable Energy Reviews, Volume 12, Issue 2, February 2008, PP 372–396.
[6] Bohn, R. E., Caramanis, M. C., & Schweppe, F. C. (1984). Optimal pricing in electrical networks over space and time. The Rand Journal of Economics, 360-376.
[7] Caballero, F., Sauma, E., Yanine, F. (2013). Business optimal design of a grid-connected hybrid PV (photovoltaic (- wind energy system without energy storage for an Easter Island’s block, Energy 61 (2013) 248-261.
[8] Connolly, D., Lund, H., Mathiesen, B.V., Pican, E., Leahy, M. (2012). the technical and economic implications of integrating fluctuating renewable energy using energy storage, Renewable Energy, 43 (2012) 47-60.
[9] Detailed statistics for the power production industry 2012 (For managers). (2013). Department of Energy, the holding company tavanir, Vice President of Human Resources and Research, Office of Information and Statistics, Department of Statistics and information science. (in persian)
[10] Emami Meybodi, A. and Haideri, K. (2012). The conversion of a simple gas turbine plants (SCGT) on the combined cycle (CCGT) and its impact on the consumption of fossil fuels, Journal of Economic Research (Research, Development and Sustainable Development), Vol. XII, No. 3. (in persian)
[11] Hamed, Mohammad sadegh, Habibi, Manuchehr. (2005). on the power industry in Iran, company research, education and electricity productivity of Tehran (tab niroo), Tehran. (in persian)
[12] Henning, H.M. and Palzer, A. (2014). A comprehensive model for the German electricity and heat sector in a future energy system with a dominant contribution from renewable energy technologies, Renewable and Sustainable Energy Reviews, 30. (2014). 1003–1018.
[13] Lund, H. (2014). Advanced Energy Systems Analysis Computer Model, Documentation Version 11.4, Aalborg University, Denmark.
[14] Kanase Patil, A. B., R. P. Saini, M. P. Sharma, “Sizing of integrated renewable energy system based on load profiles and reliability index for the state of Uttarakhand in India,” Renewable Energy, vol. 36, pp. 2809-2821, 2011.
[15] Ketabdari, MJ and Ahmedi, M. E. (2011). Feasibility study of energy absorption by numerical modeling of ocean waves on the southern coast of Iran, Journal of Marine Science and Technology, Vol. XVIII, No. 60. (in persian)
[16] Khorasan Regional Electricity Company. (2012). report on the development of renewable energy power company, Khorasan, Mashhad, release date: November 19, 2012. (in persian)
[17] Kowalski, K.; Stagl, S.; Madlener, R. and Omann, I. (2009). Sustainable energy futures: Methodological challenges in combining scenarios and participatory multi-criteria analysis, European Journal of Operational Research journal, Volume 197, Issue 3, 16 September 2009, PP 1063–1074 .
[18] Liu, W., Hu, W., Lund, H., Chen, Z. (2013). Electric vehicles and large-scale integration of wind power – The case of Inner Mongolia in China, Applied Energy, 104 (2013) 445–456
[19] Mahmoudi, M., behboodi, MH, Sadigh Zibari, S. Haditha. (2008). the role of nanotechnology in the construction industry to reduce environmental pollution, Journal of Environmental Science and Technology, Vol. I, No. 3 (s 38). (in persian)
[20] Martin, J. I. S., Zamora, I., Martin, J. J. S., Aperribay, V., Eguia, P. (2010). Hybrid fuel cells technologies for electrical microgrids, Electric Power Systems Research, 80 (2010), 993–1005.
[21] Namvar Bahraghani, B., Mr Shafiei, Mohammad; Moradi Dalvand, M., Ahmadian, M. (2012). determine the optimal size of the market in an interactive Ryzshbk•h to supply electricity and heat charge Ryzshbk•h to reduce dependence on fossil fuels, Journal of Engineering and energy management, Vol. II, No. 3 (row 5). (in persian)
[22] Mandil, C. “Oil crises and climate challenges-30 years of energy use in iea countries,” International Energy Agency, 2004.
[23] Mostofi, F., Shayeghi, H. and Kazemi Kargar, H. (2012). Potential assessment and design of renewable energy hybrid system to provide electricity for water pumping station site MeshkinShahr, Journal of Energy, Vol. XV, No. 43. (in persian)
[24] Moeni, Sam; Javadi, S., Kokabi, M. And Dehghan Manshadi, M. (2010). Estimation of solar radiation using an optimization model, Journal of Energy, Vol. XIII, No. 34. (in persian)
[25] Munasinghe, Mohan. (2009). Sustainable Development:Basic Concepts And Application To Energy, Munasinghe Institute For Development (Colombo, Sri Lanka)
[26] Paytakhti Oskuei, Ali and Nahidi, Mohammad. (2007). Environmental taxes (green taxes): theoretical, experience, Sixth Conference of Agricultural Economics, Mashhad, Agricultural Economics Association of Iran, Ferdowsi University of Mashhad, pp. 1-17. (in persian)
[27] Østergaard, P. A. (2010). Regulation strategies of cogeneration of heat and power (CHP) plants and electricity transit in Denmark, Energy 35, (2010) 2194-2202.
[28] Paytakhti Oskuei, Ali and Nahidi, Mohammad. (2007). Environmental taxes (green taxes): theoretical, experience, Sixth Conference of Agricultural Economics, Mashhad, Agricultural Economics Association of Iran, Ferdowsi University of Mashhad, pp. 1-17. (in persian)
[29] Perkovic, L., Silva, P., Ban, M., Kranjcevic, N., Duic, N. (2013). Harvesting high altitude wind energy for power production: The concept based on Magnus’ effect, Applied Energy, 101 (2013) 151–160.
[30] Pereza, I. O. and Østergaard, P. A. (2013). the influence of an estimated energy saving due to natural ventilation on the Mexican energy system, Energy 3 (2013), 1-12.
[31] Rahimi, Abdorahim, Saghafi, Majid, and Sarvghady, Zahra. (2008). investigated the use of renewable energy technology in the construction of a unit for Culture and Education, Mechanical Engineering Magazine, Issue 61, pp. 38-52. (in persian)
[32] Rahimi, N. (2005). Indicators for sustainable energy development in Iran, the Fourth National Energy Congress, Tehran, Islamic Republic of Iran's National Committee for Energy, Power and Energy Deputy Minister of Energy, pp. 1-24. (in persian)
[33] Renewable Energy Organization of Iran (SUNA). (2007). Report of potential biomass sources in Iran, Ministry of Energy, and Department of Energy. (in persian)
[34] Rostami, Soraya, Haghparast Kashani, A., Larry, HR. (2013). study estimated the cost of electricity from wind power plants, solar and biogas, National Energy Association Conference, Tehran, Iran Energy Research. (in persian)
[35] Shaditalab, Jaleh and Nayehdor, Mahdi. (2009). Analysis of factors affecting the adoption of domestic solar water heaters in rural areas - a case study Bardaskan city, autumn and winter, No. 36, pp. 67-88. (in persian)
[36] Sharifi, Alimorad; Kiani, G. and khoshakhlagh, rahman and Tudeshki Bagheri, Mohammad Mehdi. (2013). Evaluation of alternative renewable energy instead of fossil fuels in Iran: an optimal control approach, Journal of Economic Modeling Research, Vol. III, No. 11. (in persian)
[37] Suberua, M. Y., Mustafa, M.W., Bashir, N., Muhamad, N.A., Mokhtar, A.S. (2013). Power sector renewable energy integration for expanding access to electricity in sub-Saharan Africa, Renewable and Sustainable Energy Reviews, 25 (2013), 630–642.
[38] Taheri fard, Ali and Shahab, Samia. (2010). investigated the technical and economic aspects of geothermal electricity generation, Energy Economics, No. 125. (in persian)
[39] Tanrioven, M., “Reliability and cost-benefits of adding alternate power sources to an independent micro-grid community,” Journal of Power Source, vol. 150, pp. 136–149, 2005.
[40] Turner, R. K., Pearce, D., & Bateman, I. (1994). Environmental economics: an elementary introduction. Harvester Wheatsheaf.
[41] Vera, I. and Langlois, L. (2007). Energy indicators for sustainable development, Energy, Volume 32, Issue 6, June 2007, Pages 875–882.
[42] World Commission on Environment and Development. (1987). From One Earth to One World: An Overview. Oxford: Oxford University Press.
[43] Zhou, W. C. Z. Lou, Z. S. Li, L. Lu, H. X. Yang, “Current status of research on optimum sizing of stand-alone hybrid solar-wind power generation systems,” Applied Energy, vol. 87, pp. 380–389, 2010.
[44] Zhai, P., Larsen, P., Millstein, D., Menon, S., Masanet, E. (2012). the potential for avoided emissions from photovoltaic electricity in the United, Energy, 47 (2012), 443-450.
[45] Zelinka, I. (2001). Analytic programming by means of new evolutionary algorithms, Proceedings of 1st International Conference on New Trends in Physics’01, Brno, Czech Republic, pp. 210–214.
[46] Zelinka, I. (2002a). Analytic programming by means of soma algorithm, Proceedings of First International Conference on Intelligent Computing and Information Systems, Cairo, Egypt, pp. 148–154.
[47] Zelinka, I. (2002b). Analytic programming by means of soma algorithm, Proc. 8th International Conference on Soft Computing, VUT Brno, Mendel’02 Czech Republic, pp. 93–101.
CAPTCHA Image