Skip to main content

Advertisement

SpringerLink
Log in

Generation dispatch of combined solar thermal systems using dragonfly algorithm

  • Published:
Computing Aims and scope Submit manuscript

Abstract

This paper presents a method to solve Static Economic dispatch incorporating solar energy using Dragonfly algorithm. Economic dispatch is carried out considering valve point loading and prohibited operating zone constraints. Solar energy system is modelled using Beta distribution function and included in the objective function. The output power of solar farm is forecasted for four seasons. Different loading conditions are assumed in various seasons for the detailed analysis. Dragonfly algorithm, an emerging optimization technique for constrained optimization problems is applied as the optimization tool here. The proposed method is validated in 6 generator, 15 generator and 17 generator practical south Indian test systems. The results are compared with the state of art heuristic optimization method available in the literature.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Dodu JC, Martin P, Merlin A, Pouget J (1972) An optimal formulation and solution of short-range operating problems for a power system with flow constraints. Proc IEEE 60(1):54–63

    Article  Google Scholar 

  2. Aravindhababu P, Nayar KR (2002) Economic dispatch based on optimal lambda using radial basis function network. Int J Electr Power Energy Syst 24(7):551–556

    Article  Google Scholar 

  3. Parikh J, Chattopadhyay D (1996) A multi-area linear programming approach for analysis of economic operation of the Indian power system. IEEE Trans Power Syst 11(1):52–58

    Article  Google Scholar 

  4. Fan JY, Zhang L (1998) Real-time economic dispatch with line flow and emission constraints using quadratic programming. IEEE Trans Power Syst 13(2):320–325

    Article  Google Scholar 

  5. Lu H, Sriyanyong P, Song YH, Dillon T (2010) Experimental study of a new hybrid PSO with mutation for economic dispatch with non-smooth cost function. Int J Electr Power Energy Syst 32(9):921–935

    Article  Google Scholar 

  6. Basu M, Chowdhury A (2013) Cuckoo search algorithm for economic dispatch. Energy 60:99–108

    Article  Google Scholar 

  7. Mandal B, Roy PK, Mandal S (2014) Economic load dispatch using krill herd algorithm. Int J Electr Power Energy Syst 57:1–10

    Article  Google Scholar 

  8. Pothiya S, Ngamroo I, Kongprawechnon W (2010) Ant colony optimisation for economic dispatch problem with non-smooth cost functions. Int J Electr Power Energy Syst 32(5):478–487

    Article  Google Scholar 

  9. Han L, Romero CE, Yao Z (2015) Economic dispatch optimization algorithm based on particle diffusion. Energy Convers Manag 105:1251–1260

  10. Yang XS, Hosseini SSS, Gandomi AH (2012) Firefly algorithm for solving non-convex economic dispatch problems with valve loading effect. Appl Soft Comput 12(3):1180–1186

    Article  Google Scholar 

  11. Morshed MJ, Asgharpour A (2014) Hybrid imperialist competitive-sequential quadratic programming (HIC-SQP) algorithm for solving economic load dispatch with incorporating stochastic wind power: A comparative study on heuristic optimization techniques. Energy Convers Manag 84:30–40

  12. Khamsawang S, Jiriwibhakorn S (2010) DSPSO-TSA for economic dispatch problem with nonsmooth and noncontinuous cost functions. Energy Convers Manag 51(2):365–375

    Article  Google Scholar 

  13. Jeddi B, Vahidinasab V (2014) A modified harmony search method for environmental/economic load dispatch of real-world power systems. Energy Convers Manag 78:661–675

    Article  Google Scholar 

  14. Aragón VS, Esquivel SC, Coello Coello CA (2015) An immune algorithm with power redistribution for solving economic dispatch problems. Inf Sci 295:609–632

    Article  MathSciNet  Google Scholar 

  15. Bhattacharya A, Chattopadhyay PK (2010) Biogeography-based optimization for different economic load dispatch problems. IEEE Trans Power Syst 25(2):1064–1077

    Article  Google Scholar 

  16. Vlachogiannis JG, Lee KY (2009) Economic load dispatch—a comparative study on heuristic optimization techniques with an improved coordinated aggregation-based PSO. IEEE Trans Power Syst 24(2):991–1001

    Article  Google Scholar 

  17. Pandi VR, Panigrahi BK, Mallick MK, Abraham A, Das S (2009) Improved harmony search for economic power dispatch. In: Ninth International Conference on Hybrid Intelligent Systems, 2009. HIS’09, vol 3, pp 403–408. IEEE

  18. Kuo CC (2008) A novel coding scheme for practical economic dispatch by modified particle swarm approach. IEEE Trans Power Syst 23(4):1825–1835

    Article  Google Scholar 

  19. Panigrahi BK, Yadav SR, Agrawal S, Tiwari MK (2007) A clonal algorithm to solve economic load dispatch. Electr Power Syst Res 77(10):1381–1389

    Article  Google Scholar 

  20. Noman N, Iba H (2008) Differential evolution for economic load dispatch problems. Electr Power Syst Res 78(8):1322–1331

    Article  Google Scholar 

  21. Secui DC (2015) A new modified artificial bee colony algorithm for the economic dispatch problem. Energy Conver Manag 89:43–62

  22. Wang L, Li LP (2013) An effective differential harmony search algorithm for the solving non-convex economic load dispatch problems. Int J Electr Power Energy Syst 44(1):832–843

    Article  Google Scholar 

  23. Gaing ZL (2003) Particle swarm optimization to solving the economic dispatch considering the generator constraints. IEEE Trans Power Syst 18(3):1187–1195

    Article  Google Scholar 

  24. Thanushkodi K (2007) A new particle swarm optimization solution to nonconvex economic dispatch problems. IEEE Trans Power Syst 22(1):42–51

    Google Scholar 

  25. Pothiya S, Ngamroo I, Kongprawechnon W (2008) Application of multiple tabu search algorithm to solve dynamic economic dispatch considering generator constraints. Energy Convers Manag 49(4):506–516

    Article  Google Scholar 

  26. Park JB, Jeong YW, Shin JR, Lee KY (2010) An improved particle swarm optimization for nonconvex economic dispatch problems. IEEE Trans Power Syst 25(1):156–166

    Article  Google Scholar 

  27. Amjady N, Sharifzadeh H (2010) Solution of non-convex economic dispatch problem considering valve loading effect by a new Modified Differential Evolution algorithm. IEEE Trans Power Syst 32(8):893–903

    Google Scholar 

  28. Panigrahi BK, Ravikumar Pandi V (2008) Bacterial foraging optimisation: Nelder-Mead hybrid algorithm for economic load dispatch. IET Gener Transm Distrib 2(4):556–565

    Article  Google Scholar 

  29. Pereira-Neto A, Unsihuay C, Saavedra OR (2005) Efficient evolutionary strategy optimisation procedure to solve the nonconvex economic dispatch problem with generator constraints. IEE Proc Gener Transm Distrib 152(5):653–660

    Article  Google Scholar 

  30. Reddy SS, Bijwe PR, Abhyankar AR (2015) Real-time economic dispatch considering renewable power generation variability and uncertainty over scheduling period. IEEE Syst J 9(4):1440–1451

    Article  Google Scholar 

  31. Khan NA, Awan AB, Mahmood A, I.E.E.E. Member, Razzaq S, Zafar A, Sidhu GAS (2015) Combined emission economic dispatch of power system including solar photo voltaic generation. Energy Convers Manag 92:82–91

  32. ElDesouky AA (2013) Security and stochastic economic dispatch of power system including wind and solar resources with environmental consideration. Int J Renew Energy Res (IJRER) 3(4):951–958

    Google Scholar 

  33. Geetha K, Sharmila Deve V, Keerthivasan K (2015) Design of economic dispatch model for Gencos with thermal and wind powered generators. Int J Electr Power Energy Syst 68:222–232

    Article  Google Scholar 

  34. Liu X, Wilsun X (2010) Economic load dispatch constrained by wind power availability: a here-and-now approach. IEEE Trans Sustain Energy 1(1):2–9

    Article  Google Scholar 

  35. Reddy SS, Abhyankar AR, Bijwe PR (2012) Market clearing for a wind-thermal power system incorporating wind generation and load forecast uncertainties. In: Power and Energy Society General Meeting, 2012 IEEE, pp 1–8

  36. Gholami A, Ansari J, Jamei M, Kazemi A (2014) Environmental/economic dispatch incorporating renewable energy sources and plug-in vehicles. IET Gener Transm Distrib 8(12):2183–2198

    Article  Google Scholar 

  37. Reddy SS, Surender BK, Kundu R, Mukherjee R, Debchoudhury S (2013) Energy and spinning reserve scheduling for a wind-thermal power system using CMA-ES with mean learning technique. Int J Electr Power Energy Syst 53:113–122

    Article  Google Scholar 

  38. Mirjalili S (2016) Dragonfly algorithm: a new meta-heuristic optimization technique for solving single-objective, discrete, and multi-objective problems. Neural Comput Appl 27(4):1053–1073

    Article  Google Scholar 

  39. Azizipanah-Abarghooee R, Niknam T, Roosta A, Malekpour AR, Zare M (2012) Probabilistic multiobjective wind-thermal economic emission dispatch based on point estimated method. Energy 37(1):322–335

    Article  Google Scholar 

  40. Meng J, Li G, Du Y (2013) Economic dispatch for power systems with wind and solar energy integration considering reserve risk. In: Power and Energy Engineering Conference (APPEEC), 2013 IEEE PES Asia-Pacific. IEEE, 2013, pp 1–5

  41. Panigrahi BK, Ravikumar Pandi V, Das S (2008) Adaptive particle swarm optimization approach for static and dynamic economic load dispatch. Energy Convers Manag 49(6):1407–1415

    Article  Google Scholar 

  42. Bhattacharya A, Chattopadhyay PK (2010) Hybrid differential evolution with biogeography-based optimization for solution of economic load dispatch. IEEE Trans Power Syst 25(4):1955–1964

    Article  Google Scholar 

  43. Chaturvedi KT, Pandit M, Srivastava L (2008) Self-organizing hierarchical particle swarm optimization for nonconvex economic dispatch. IEEE Trans Power Syst 23(3):1079–1087

  44. http://rredc.nrel.gov/solar/new_data/India/nearestcell.cgi

  45. Teng JH, Luan SW, Lee DJ, Huang YQ (2013) Optimal charging/discharging scheduling of battery storage systems for distribution systems interconnected with sizeable PV generation systems. IEEE Trans Power Syst 28(2):1425–1433

    Article  Google Scholar 

  46. http://de.enfsolar.com/pv/panel-datasheet/Polycrystalline/12187

  47. Sreejith S, Simon SP (2014) Cost benefit analysis on SVC and UPFC in a dynamic economic dispatch problem. Int J Energy Sector Manag 8(3):395–428

    Article  Google Scholar 

  48. Salameh ZM, Borowy BS, Amin ARA (1995) Photovoltaic module-site matching based on the capacity factors. IEEE Trans Energy Convers 10(2):326–332

    Article  Google Scholar 

  49. Kamboj VK, Bhadoria A, Bath SK (2016) Solution of non-convex economic load dispatch problem for small-scale power systems using ant lion optimizer. Neural Comput Appl 1–12

  50. Jayabarathi T, Raghunathan T, Adarsh BR, Suganthan PN (2016) Economic dispatch using hybrid grey wolf optimizer. Energy 111:630–641

Download references

Author information

Authors and Affiliations

  1. School of Electrical Engineering, VIT University, Vellore, 632 014, Tamil Nadu, India

    Velamuri Suresh & S. Sreejith

Authors
  1. Velamuri Suresh
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. S. Sreejith
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Velamuri Suresh.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Suresh, V., Sreejith, S. Generation dispatch of combined solar thermal systems using dragonfly algorithm. Computing 99, 59–80 (2017). https://doi.org/10.1007/s00607-016-0514-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00607-016-0514-9

Keywords

Mathematics Subject Classification

Search

Navigation