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access icon free Economic feasibility of hybrid energy generation with reduced carbon emission

© The Institution of Engineering and Technology
Received 29/04/2017, Accepted 19/03/2018, Revised 14/02/2018, Published 22/03/2018

Increasing concern about the shortage of energy resources and harmful outcome of fossil fuel emission has initiated new requirement of reliable and cleaner green power sources. Hence, solar photovoltaic and wind power system are fastest developing sources among different renewable energy sources. In the proposed work, the urgency of the national policy to upgrade the existing coal-based plant as integrated solar, wind and coal-based power plant to reduce the carbon emission and to evaluate the feasibility of developing grid-connected hybrid energy system in Ramapuram Chennai, India has been presented. Moreover, the regression models for estimation of global solar radiation using different metrological parameters are developed and compared with the results of other models. In this work, Ramapuram, Chennai, India area is chosen to install the wind and solar photovoltaic systems to feed three types of load (residential, commercial and industrial). In this study, ENNORE thermal power station, Chennai is considered to reduce the carbon emission as the integration of solar photovoltaic system and wind system to the grid reduce the units generation from this plant. Hence, study shows that 110329.56 kg emission is reduced from ENNORE thermal power station by using this system.

Inspec keywords: solar power stations; power generation economics; power grids; air pollution control; wind power plants; photovoltaic power systems; carbon; steam power stations; hybrid power systems; global warming; regression analysis

Other keywords: Rangarajan model; cleaner green power sources; wind power system; integrated solar power plant; Veeran model; reduced carbon emission; Kumar models; coal-based power plant; economic feasibility; Sukhatme model; Chennai; regression models; fossil fuel emission; grid-connected hybrid energy system; Modi model; Mani model; global solar radiation estimation; global warming; wind power plant; metrological parameters; national policy; solar PV systems; solar photovoltaic system; India; Ramapuram; hybrid energy generation; low-carbon emission plant; renewable energy sources; ENNORE thermal power station

Subjects: Wind power plants; Steam power stations and plants; Power system management, operation and economics; Solar power stations and photovoltaic power systems; Other topics in statistics

References

    1. 1)
      • 15. Korada, N., Mishra, M. K.: ‘Grid adaptive power management strategy for an integrated microgrid with hybrid energy storage’, IEEE Trans. Ind. Electron., 2017, 64, (4), pp. 2884–2892.
    2. 2)
      • 25. Almorox, J, Hontoria, C: ‘Global solar radiation estimation using sunshine duration in Spain’, Energy Convers. Manage., 2004, 45, pp. 1529–1535.
    3. 3)
      • 22. Ampratwum, D.A., Dorvlo, A.S.S.: ‘Estimation of solar radiation from the number of sunshine hours’, Appl. Energy, 1999, 63, pp. 161–167.
    4. 4)
      • 24. Akpabio, L.E., Etuk, S.E.: ‘Relationship between global solar radiation and sunshine duration for Onne, Nigeria’, J. Phys., 2003, 27, pp. 161–167.
    5. 5)
      • 12. Sachs, J., Sawodny, O.: ‘A two-stage model predictive control strategy for economic diesel-PV-battery island microgrid operation in rural areas’, IEEE Trans. Sustain. Energy, 2016, 7, (3), pp. 903–913.
    6. 6)
      • 20. Hu, H., Kavan, P.: ‘Energy consumption and carbon dioxide emissions of China's non-metallic mineral products industry: present state, prospects and policy analysis’, Sustainability, 2014, 6, (11), pp. 8012–8028.
    7. 7)
      • 6. Ramos, L.F., Krüger, C., Farret, F.A.: ‘Economical feasibility of alternative sources as secondary means for electricity generation in Brazilian gas stations’, IEEE Latin Am. Trans., 2016, 14, (4), pp. 1717–1723.
    8. 8)
      • 18. Mohan, V., Suresh, R., Singh, J.G., et al: ‘Microgrid energy management combining sensitivities, interval and probabilistic uncertainties of renewable generation and loads’, IEEE J. Emerg. Sel. Top. Circuits Syst., 2017, 7, (2), pp. 262–270.
    9. 9)
      • 29. Mani, A.: ‘Solar radiation handbook’ (SEC & IMD, Pune, 2008).
    10. 10)
      • 13. Zeng, Z., Shao, W.: ‘Reconnection of micro-grid from islanded mode to grid-connected mode used sliding Goertzel transform based filter’, IET Renew. Power Gener., 2017, 11, (7), pp. 1041–1048.
    11. 11)
      • 28. Mani, A.: ‘Handbook of solar radiation data for India’ (Allied Publishers, New Delhi, 1980).
    12. 12)
      • 23. Falayi, E.O., Adepitan, J.O., Rabiu, A.B.: ‘Empirical models for the correlation of global solar radiation with meteorological data for Iseyin, Nigeria’, Int. J. Phys. Sci., 2008, 3, pp. 210–216.
    13. 13)
      • 2. Wang, C., Lu, Z., Qiao, Y.: ‘A consideration of the wind power benefits in day-ahead scheduling of wind-coal intensive power systems’, IEEE Trans. Power Syst., 2013, 28, (1), pp. 236–245.
    14. 14)
      • 9. Zhuo, Y., Xu, J., Wei, F., et al: ‘Design of power supply network based on 500/110 kV for load center and comprehensive accessibility evaluation’, CSEE J. Power Energy Syst., 2016, 2, (1), pp. 30–39.
    15. 15)
      • 4. Oh, H.: ‘Optimal planning to include storage devices in power systems’, IEEE Trans. Power Syst., 2011, 26, (3), pp. 1118–1128.
    16. 16)
      • 17. Kotra, S., Mishra, M. K.: ‘A supervisory power management system for a hybrid microgrid with HESS’, IEEE Trans. Ind. Electron., 2017, 64, (5), pp. 3640–3649.
    17. 17)
      • 5. Liu, C., Botterud, A., Zhou, Z., et al: ‘Fuzzy energy and reserve co-optimization with high penetration of renewable energy’, IEEE Trans. Sustain. Energy, 2017, 8, (2), pp. 782–791.
    18. 18)
      • 21. Benghanem, M., Mellit, A., Alamri, S.L.: ‘ANN based modeling and estimation of daily global solar radiation data: a case study’, Energy Convers. Manage., 2009, 50, pp. 1644–1655.
    19. 19)
      • 8. Bucksteeg, M., Niesen, L., Weber, C.: ‘Impacts of dynamic probabilistic reserve sizing techniques on reserve requirements and system costs’, IEEE Trans. Sustain. Energy, 2016, 7, (4), pp. 1408–1420.
    20. 20)
      • 16. Zhang, C., Xu, Y., Dong, Z.Y., et al: ‘Robust operation of microgrids via two-stage coordinated energy storage and direct load control’, IEEE Trans. Power Syst., 2017, 32, (4), pp. 2858–2868.
    21. 21)
      • 11. Shadmand, M.B., Balog, R.S.: ‘Multi-objective optimization and design of photovoltaic-wind hybrid system for community smart DC microgrid’, IEEE Trans. Smart Grid, 2014, 5, (5), pp. 2635–2643.
    22. 22)
      • 19. Yuan, C., Illindala, M., Khalsa, A.: ‘Co-optimization scheme for distributed energy resource planning in community microgrids’, IEEE Trans. Sustain. Energy, 2017, 8, (4), p. 1.
    23. 23)
      • 3. Foster, J.M., Trevino, G., Kuss, M., et al: ‘Plug-in electric vehicle and voltage support for distributed solar: theory and application’, IEEE Syst. J., 2013, 7, (4), pp. 881–888.
    24. 24)
      • 27. Katiyar, A.K., Katiyar, V.K.: ‘Estimation of global solar radiation using sunshine hours and meteorological parameters for Uttar Pradesh’. Proc. Int. Conf. Solar Radiation and Day Lighting, Delhi, 2007.
    25. 25)
      • 7. Konda, S.R., Panwar, L.K., Panigrahi, B.K., et al: ‘A multiple emission constrained approach for self-scheduling of GENCO under renewable’, CSEE J. Power Energy Syst., 2017, 3, (1), pp. 63–73.
    26. 26)
      • 26. Chandel, S.S., Agarwal, R.K., Pandey, A.N.: ‘New correlation to estimate global solar radiation on horizontal surfaces using sunshine hour and temperature data for Indian sites’, J. Solar Eng., 2005, 127, pp. 417–420.
    27. 27)
      • 30. Duffie, J.A., Bechman, W.A.: ‘Solar engineering of thermal processes’ (John Wiley & Sons, New York, 1980), pp. 6–65.
    28. 28)
      • 14. Sun, K., Wang, X., Li, Y.W., et al: ‘Parallel operation of bidirectional interfacing converters in a hybrid AC/DC microgrid under unbalanced grid voltage conditions’, IEEE Trans. Power Electron., 2017, 32, (3), pp. 1872–1884.
    29. 29)
      • 1. Forouzandehmehr, N., Han, Z., Zheng, R.: ‘Stochastic dynamic game between hydropower plant and thermal power plant in smart grid networks’, IEEE Syst. J., 2016, 10, (1), pp. 88–96.
    30. 30)
      • 10. Wei, W., Liu, F., Mei, S., et al: ‘Robust energy and reserve dispatch under variable renewable generation’, IEEE Trans. Smart Grid, 2015, 6, (1), pp. 369–380.
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