Determining the sizes of renewable DGs considering seasonal variation of generation and load and their impact on system load growth

Determining the sizes of renewable DGs considering seasonal variation of generation and load and their impact on system load growth

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In this study, a methodology for determining the solar and wind DG (distributed generation) capacity is proposed by using sequential optimisation method considering a seasonal variation of load demand, seasonal solar, and wind variations. The load demand profile is collected from state load dispatch centre; whereas solar data are collected from Indian Institute of Technology Kharagpur and wind data are collected from a weather station. Along with the DGs, the shunt capacitors are also placed to improve the voltage profile and energy loss reduction with different scenarios. For this purpose, minimisation of a multi-objective function is considered. The proposed methodology is applied to a 69-bus distribution network. The results for different scenarios show the substantial reduction in the annual energy loss and improvement of voltage profile. The result also shows that maximum amount of profit is gained with both renewable DGs and shunt capacitors. The impact of load growth on the distribution network with and without renewable DGs and shunt capacitors are compared. The analysis reveals that with integrating the renewable DGs and shunt capacitors in the system, the distribution network can take load growth for few more years without violating the system constraints.


    1. 1)
      • 1. Ackermann, T., Andersson, G., Soder, L.: ‘Distributed generation: a definition’, Electr. Power Syst. Res., 2001, 57, (3), pp. 195204.
    2. 2)
      • 2. Patnaik, B., Sattianadan, D., Sudhakaran, M., et al: ‘Optimal placement and sizing of solar and wind based DGs in distribution systems for power loss minimization and economic operation’, in Kamalakannan, C., Padma Suresh, L., Dash, S.S., et al (Eds.): ‘Power electronics and renewable energy systems’ (Springer, New Delhi, India, 2015), ch. 36, pp. 351360.
    3. 3)
      • 3. Lin, C.H., Shieh, W.L., Chen, C.S., et al: ‘Financial analysis of a large-scale photovoltaic system and its impact on distribution feeders’, IEEE Trans. Ind. Appl., 2011, 47, (4), pp. 18841891.
    4. 4)
      • 4. Porkar, S., Poure, P., Abbaspour-Tehrani-fard, A., et al: ‘A novel optimal distribution system planning framework implementing distributed generation in a deregulated electricity market’, Electr. Power Syst. Res., 2010, 80, (7), pp. 828837.
    5. 5)
      • 5. Safigianni, A.S., Koutroumpezis, G.N., Poulios, V.C.: ‘Mixed distributed generation technologies in a medium voltage network’, Electr. Power Syst. Res., 2013, 96, pp. 7580.
    6. 6)
      • 6. Hung, D.Q., Mithulanathan, N., Lee, K.Y.: ‘Optimal placement of dispatchable and nondispatchable renewable DG units in distribution networks for minimizing energy loss’, Int. J. Electr. Power Energy Syst., 2014, 55, pp. 179186.
    7. 7)
      • 7. Al Abri, R.S., El-Saadany, E.F., Atwa, Y.M.: ‘Optimal placement and sizing method to improve the voltage stability margin in a distribution system using distributed generation’, IEEE Trans. Power Syst., 2013, 28, (1), pp. 326334.
    8. 8)
      • 8. Abu-Mauti, F.S., El-Hawary, M.E.: ‘Heuristic curve-fitted technique for distributed generation optimisation in radial distribution feeder systems’, IET Gener. Transm. Distrib., 2011, 5, (2), pp. 172180.
    9. 9)
      • 9. Vatani, M., Alkaran, D.S., Sanjari, M.J., et al: ‘Multiple distributed generation units allocation in distribution network for loss reduction based on a combination of analytical and genetic algorithm methods’, IET Gener. Transm. Distrib., 2016, 10, (1), pp. 6672.
    10. 10)
      • 10. Atwa, Y.M., El-Saadany, E.F., Salama, M.M.A., et al: ‘Optimal renewable resources mix for distribution system energy loss minimization’, IEEE Trans. Power Syst., 2010, 25, (1), pp. 360370.
    11. 11)
      • 11. Acharya, N., Mahat, P., Mithulananthan, N.: ‘An analytical approach for DG allocation in primary distribution network’, Int. J. Electr. Power Energy Syst., 2006, 20, (10), pp. 669678.
    12. 12)
      • 12. Oda, E.S., Abdelsalam, A.A., Abdel-Wahab, M.N., et al: ‘Distributed generations planning using flower pollination algorithm for enhancing distribution system voltage stability’, Ain Shams Eng. J., 2015, 8, pp. 593603.
    13. 13)
      • 13. Tan, W.-S., Hassan, M.Y., Majid, M.S., et al: ‘Optimal distributed renewable generation planning: a review of different approaches’, Renew. Sust. Energy Rev., 2013, 18, pp. 626645.
    14. 14)
      • 14. García, J.A.M., Mena, A.J.G.: ‘Optimal distributed generation location and size using a modified teaching-learning based optimization algorithm’, Int. J. Electr. Power Energy Syst., 2013, 50, pp. 6575.
    15. 15)
      • 15. Kaur, S., Kumbhar, G., Sharma, J.: ‘A MINLP technique for optimal placement of multiple DG units in distribution systems’, Int. J. Electr. Power Energy Syst., 2014, 63, pp. 609617.
    16. 16)
      • 16. Mohammadi, M., Hosseinian, S.H., Gharehpetian, G.B.: ‘Optimization of hybrid solar energy sources/wind turbine systems integrated to utility grids as microgrid (MG) under pool/bilateral/hybrid electricity market using PSO’, Sol. Energy, 2012, 86, (1), pp. 112125.
    17. 17)
      • 17. Hung, D.Q., Mithulananthan, N.: ‘Multiple distributed generator placement in primary distribution networks for loss reduction’, IEEE Trans. Ind. Electron., 2013, 60, (4), pp. 17001708.
    18. 18)
      • 18. Kansal, S., Kumar, V., Tyagi, B.: ‘Hybrid approach for optimal placement of multiple DGs of multiple types in distribution networks’, Int. J. Electr. Power Energy Syst., 2016, 75, pp. 226235.
    19. 19)
      • 19. Nayanatara, C., Baskaran, J., Kothari, D.P.: ‘Hybrid optimization implemented for distributed generation parameters in a power system network’, Int. J. Electr. Power Energy Syst., 2016, 78, pp. 690699.
    20. 20)
      • 20. Jamil, M., Anees, A.S.: ‘Optimal sizing and location of SPV (solar photovoltaic) based MLDG (multiple location distributed generator) in distribution system for loss reduction, voltage profile improvement with economical benefits’, Energy, 2016, 103, pp. 231239.
    21. 21)
      • 21. Mahmoud, K., Yorino, N., Ahmed, A.: ‘Optimal distributed generation allocation in distribution systems for loss minimization’, IEEE Trans. Power Syst., 2016, 31, (2), pp. 960969.
    22. 22)
      • 22. Bhandari, B., Poudel, S.R., Lee, K.-T., et al: ‘Mathematical modeling of hybrid renewable energy system: a review on small hydro-solar-wind power generation’, Int. J. Prec. Eng. Manuf.-Green Technol., 2014, 1, (2), pp. 157173.
    23. 23)
      • 23. Tamura, J.: ‘Calculation method of losses and efficiency of wind generators’, in Muyeen, S.M. (Ed.): ‘Wind energy conversion systems’ (Springer, London, 2012), pp. 2551.
    24. 24)
      • 24. Margaret Amutha, W., Rajini, V.: ‘Cost benefit and technical analysis of rural electrification alternatives in southern India using HOMER’, Renew. Sust. Energy Rev., 2016, 62, pp. 236246.
    25. 25)
      • 25. Blaabjerg, F., Ionel, D.M.: ‘Renewable energy devices and systems-state-of-the-art technology, research and development, challenges and future trends’, Electr. Power Compon. Syst., 2015, 43, (12), pp. 13191328.
    26. 26)
      • 26. Colmenar-Santos, A., Reino-Rio, C., Borge-Diez, D., et al: ‘Distributed generation: a review of factors that can contribute most to achieve a scenario of DG units embedded in the new distribution networks’, Renew. Sust. Energy Rev., 2016, 59, pp. 11301148.
    27. 27)
      • 27. Jordehi, A.R.: ‘Allocation of distributed generation units in electric power systems: a review’, Renew. Sust. Energy Rev., 2016, 56, pp. 893905.
    28. 28)
      • 28. Sfikas, E.E., Katsigiannis, Y.A., Georgilakis, P.S.: ‘Simultaneous capacity optimization of distributed generation and storage in medium voltage microgrids’, Int. J. Electr. Power Energy Syst., 2015, 67, pp. 101113.
    29. 29)
      • 29. Daud, A.-K., Ismail, M.S.: ‘Design of isolated hybrid systems minimizing costs and pollutant emissions’, Renew. Energy, 2012, 44, pp. 215224.
    30. 30)
      • 30. Elsheikh, A., Helmy, Y., Abouelseoud, Y., et al: ‘Optimal capacitor placement and sizing in radial electric power systems’, Alexandria Eng. J., 2014, 53, pp. 809816.
    31. 31)
      • 31. Abdelaziz, A.Y., Ali, E.S., Abd Elazim, S.M.: ‘Optimal sizing and locations of capacitors in radial distribution systems via flower pollination optimization algorithm and power loss index’, Eng. Sci. Technol. Int. J., 2016, 19, (1), pp. 610618.
    32. 32)
      • 32. Chiou, J.-P., Chang, C.-F.: ‘Development of a novel algorithm for optimal capacitor placement in distribution systems’, Int. J. Electr. Power Energy Syst., 2015, 73, pp. 684690.
    33. 33)
      • 33. Sultana, S., Roy, P.K.: ‘Optimal capacitor placement in radial distribution systems using teaching learning based optimization’, Int. J. Electr. Power Energy Syst., 2014, 54, pp. 387398.
    34. 34)
      • 34. Ramalinga Raju, M., Ramachandra Murthy, K.V.S., Ravindra, K.: ‘Direct search algorithm for capacitive compensation in radial distribution systems’, Int. J. Electr. Power Energy Syst., 2012, 42, (1), pp. 2430.
    35. 35)
      • 35. Vuleti, J., Todorovski, M.: ‘Optimal capacitor placement in distorted distribution networks with different load models using penalty free genetic algorithm’, Int. J. Electr. Power Energy Syst., 2016, 78, pp. 174182.
    36. 36)
      • 36. Abul'Wafa, A.R.: ‘Optimal capacitor allocation in radial distribution systems for loss reduction: a two stage method’, Electr. Power Syst. Res., 2013, 95, pp. 168174.
    37. 37)
      • 37. El-Fergany, A.A., Abdelaziz, A.Y.: ‘Artificial bee colony algorithm to allocate fixed and switched static shunt capacitors in radial distribution networks’, Electr. Power Compon. Syst., 2014, 42, (5), pp. 427438.
    38. 38)
      • 38. Ramadan, H.S., Bendray, A.F., Nagy, S.: ‘Particle swarm optimization algorithm for capacitor allocation problem in distribution systems with wind turbine generators’, Int. J. Electr. Power Energy Syst., 2017, 84, pp. 143152.
    39. 39)
      • 39. Sedighizadeh, M., Dakhem, M., Sarvi, M., et al: ‘Optimal reconfiguration and capacitor placement for power loss reduction of distribution system using improved binary particle swarm optimization’, Int. J. Energy Environ. Eng., 2014, 5, (1), p. 73.
    40. 40)
      • 40. Moradi, M.H., Zeinalzadeh, A., Mohammadi, Y., et al: ‘An efficient hybrid method for solving the optimal sitting and sizing problem of DG and shunt capacitor banks simultaneously based on imperialist competitive algorithm and genetic algorithm’, Int. J. Electr. Power Energy Syst., 2014, 54, pp. 101111.
    41. 41)
      • 41. Khodabakhshian, A., Andishgar, M.H.: ‘Simultaneous placement and sizing of DGs and shunt capacitors in distribution systems by using IMDE algorithm’, Int. J. Electr. Power Energy Syst., 2016, 82, pp. 599607.
    42. 42)
      • 42. Kanwar, N., Gupta, N., Niazi, K.R., et al: ‘Improved meta-heuristic techniques for simultaneous capacitor and DG allocation in radial distribution networks’, Int. J. Electr. Power Energy Syst., 2015, 73, pp. 653664.
    43. 43)
      • 43. Rahmani-andebili, M.: ‘Simultaneous placement of DG and capacitor in distribution network’, Electr. Power Syst. Res., 2016, 131, pp. 110.
    44. 44)
      • 44. Gholami, R., Shahabi, M., Haghifam, M.-R.: ‘An efficient optimal capacitor allocation in DG embedded distribution networks with islanding operation capability of micro-grid using a new genetic based algorithm’, Int. J. Electr. Power Energy Syst., 2015, 71, pp. 335343.
    45. 45)
      • 45. Zeinalzadeh, A., Mohammadi, Y., Moradi, M.H.: ‘Optimal multi objective placement and sizing of multiple DGs and shunt capacitor banks simultaneously considering load uncertainty via MOPSO approach’, Int. J. Electr. Power Energy Syst., 2015, 67, pp. 336349.
    46. 46)
      • 46. Chandel, M., Agrawal, G.D., Mathur, S., et al: ‘Techno-economic analysis of solar photovoltaic power plant for garment zone of Jaipur city’, Case Stud. Therm. Eng., 2014, 2, pp. 17.
    47. 47)
      • 47. Mistry, K.D., Roy, R.: ‘Enhancement of loading capacity of distribution system through distributed generator placement considering techno-economic benefits with load growth’, Int. J. Electr. Power Energy Syst., 2014, 54, pp. 505515.
    48. 48)
      • 48. Tanwar, S.S., Khatod, D.K.: ‘Techno-economic and environmental approach for optimal placement and sizing of renewable DGs in distribution system’, Energy, 2017, 127, pp. 5267.
    49. 49)
      • 49. El-Fergany, A.: ‘Optimal allocation of multi-type distributed generators using backtracking search optimization algorithm’, Int. J. Electr. Power Energy Syst., 2015, 64, pp. 11971205.
    50. 50)
      • 50. Ali, E.S., Elazim, S.M., Abdelaziz, A.Y.: ‘Ant lion optimization algorithm for renewable distributed generations’, Energy, 2016, 116, pp. 445458.
    51. 51)
      • 51. Rahiminejad, A., Vahidi, B., Hejazi, M.A., et al: ‘Optimal scheduling of dispatchable distributed generation in smart environment with the aim of energy loss minimization’, Energy, 2016, 116, pp. 190201.
    52. 52)
      • 52.
    53. 53)
      • 53.
    54. 54)
      • 54.
    55. 55)
      • 55.

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