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Bio-inspired heuristics hybrid with sequential quadratic programming and interior-point methods for reliable treatment of economic load dispatch problem

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Abstract

In the present study, bio-inspired computational heuristics are exploited for finding the solution of economic load dispatch (ELD) problem with valve point loading effect using variants of genetic algorithm (GA) hybrid with sequential quadratic programming (SQP) and interior-point algorithms (IPAs). Variants of GAs are constructed using different sets of routines for its fundamental operators in order to explore the entire search space for global optimum solutions while SQP and IPA are integrated with GAs for rapid local convergence. Nine variants of each design scheme based on GAs, GA-SQP and GA-IPAs are applied on three different ELD problems of thermal power plant systems. Comparative studies of the proposed schemes are performed through the results of statistical performance indices in order to establish the worth and effectiveness in terms of accuracy, convergence and complexity measures.

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References

  1. Kirschen D (2010). Fundamentals of Power System Economics. Wiley

  2. ZHU J (2009) Optimization of power system operation: theory and practice. 4th ed. Chichester: Wiley. IEEE

  3. Kumar S, Chaturvedi DK (2013) Optimal power flow solution using fuzzy evolutionary and swarm optimization. Journal of Electrical Power and Energy Systems 47:416–423

    Article  Google Scholar 

  4. Chatterjee K, Shankar R, Chatterjee TK (2015) Load frequency control considering very short-term load prediction and economic load dispatch using neural network and its application. Systems Thinking Approach for Social Problems, Springer India:75–89

  5. Momoh JA, Elhawary ME, Adapa R (1999) A review of selected optimal power flow literature to 1993 part1: nonlinear and quadratic programming approaches. IEEE Trans Power System 4(1):96–104

    Article  Google Scholar 

  6. Xia X, Elaiw AM (2010) Optimal dynamic economic dispatch of generation: a review. Electr Power Syst Res 80(8):975–986

    Article  Google Scholar 

  7. Elattar EE (2015) A hybrid genetic algorithm and bacterial foraging approach for dynamic economic dispatch problem. Int J Electr Power Energy Syst 69:18–26

    Article  Google Scholar 

  8. Ramzanpour M, Abdi H (2014) Economic load dispatch with considering the valve-point effects and ramp rate limits of generators using evolutionary algorithms. Journal of Advances in Computer Research 5(3):69–84

    Google Scholar 

  9. Augusteen WA, Rengaraj R, Muthu Selvan NB (2015) Phenotypic evolutionary programming for economic operation of thermal—wind coordination. Power Electronics and Renewable Energy Systems. Springer India. 1425–1436

  10. Sinha N, Chakrabarti R, Chattopadhyay PK (2003) Evolutionary programming techniques for economic load dispatch. Evolutionary Computation, IEEE Transactions on 7.1:83–94

    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

    Article  Google Scholar 

  12. Xiong G, Shi D, Duan X (2013) Multi-strategy ensemble biogeography-based optimization for economic dispatch problems. Appl Energy 111:801–811

    Article  Google Scholar 

  13. Kavousi-Fard A et al (2014) A novel sufficient bio-inspired optimisation method based on modified krill herd algorithm to solve the economic load dispatch. International Journal of Bio-Inspired Computation 6(6):416–423

    Article  MathSciNet  Google Scholar 

  14. 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 

  15. Mouassa S, Bouktir T (2015) Artificial Bee Colony Algorithm for Solving OPF Problem Considering the Valve Point Effect. Int J Comput Appl 112.1

  16. Herbadji O, Bouktir T (2015) Optimal power flow using firefly algorithm with consideration of FACTS devices UPFC. International Journal on Electrical Engineering and Informatics 7(1):12

    Article  Google Scholar 

  17. Mahdad B, Srairi K, Bouktir T (2013) Interactive DE for solving combined security environmental economic dispatch considering FACTS technology. Frontiers in Energy 7(4):429–447

    Article  Google Scholar 

  18. Tran CD et al (2015) Economic load dispatch with multiple fuel options and valve point effect using cuckoo search algorithm with different distributions. International Journal of Hybrid Information Technology 8(1):305–316

    Article  Google Scholar 

  19. Hosseinnezhad V et al (2014) Species-based quantum particle swarm optimization for economic load dispatch. Int J Electr Power Energy Syst 63:311–322

    Article  Google Scholar 

  20. Basu M (2014) Teaching–learning-based optimization algorithm for multi-area economic dispatch. Energy 68:21–28

    Article  Google Scholar 

  21. Modiri-Delshad M, Rahim NA (2014) Solving non-convex economic dispatch problem via backtracking search algorithm. Energy 77:372–381

    Article  Google Scholar 

  22. Hooshmand R-A, Parastegari M, Morshed MJ (2012) Emission, reserve and economic load dispatch problem with non-smooth and non-convex cost functions using the hybrid bacterial foraging-Nelder–mead algorithm. Appl Energy 89(1):443–453

    Article  Google Scholar 

  23. Jadoun VK et al (2015) Modulated particle swarm optimization for economic emission dispatch. Int J Electr Power Energy Syst 73:80–88

    Article  Google Scholar 

  24. Vlachogiannis JG, Lee KY (2009) Economic load dispatch—a comparative study on heuristic optimization techniques with an improved coordinated aggregation-based PSO. Power Systems, IEEE Transactions on 24.2:991–1001

    Article  Google Scholar 

  25. Kim J, Kim CS, Geem ZW (2014) A memetic approach for improving minimum cost of economic load dispatch problems. Math Prob Eng

  26. Jiang S, Ji Z, Shen Y (2014) A novel hybrid particle swarm optimization and gravitational search algorithm for solving economic emission load dispatch problems with various practical constraints. Int J Electr Power Energy Syst 55:628–644

    Article  Google Scholar 

  27. Niu Q, Li K, Irwin GW (2015) Differential evolution combined with clonal selection for dynamic economic dispatch. Journal of Experimental & Theoretical Artificial Intelligence 27(3):325–350

    Article  Google Scholar 

  28. Sivasubramani S, Ahmad M (2014) Hybrid harmony search algorithm and interior point method for economic dispatch with valve-point effect. International Journal of Emerging Electric Power Systems 15.3:253–261

    Article  Google Scholar 

  29. Duman S, Yorukeren N, Altas IH (2015) A novel modified hybrid PSOGSA based on fuzzy logic for non-convex economic dispatch problem with valve-point effect. Int J Electr Power Energy Syst 64:121–135

    Article  Google Scholar 

  30. Niknam T (2010) A new fuzzy adaptive hybrid particle swarm optimization algorithm for non-linear, non-smooth and non-convex economic dispatch problem. Appl Energy 87(1):327–339

    Article  Google Scholar 

  31. Alsumait JS, Sykulski JK, Al-Othman AK (2010) A hybrid GA–PS–SQP method to solve power system valve-point economic dispatch problems. Appl Energy 87(5):1773–1781

    Article  Google Scholar 

  32. Chiroma H, Abdulkareem S, Herawan T (2015) Evolutionary neural network model for West Texas intermediate crude oil price prediction. Appl Energy 142:266–273

    Article  Google Scholar 

  33. Abu Arqub, O., Abo-Hammour, Z., Momani, S. and Shawagfeh, N. (2012). Solving singular two-point boundary value problems using continuous genetic algorithm. In Abstract and Applied Analysis (Vol. 2012). Hindawi Publishing Corporation

  34. Arqub OA (2016) The reproducing kernel algorithm for handling differential algebraic systems of ordinary differential equations. Mathematical Methods in the Applied Sciences 39(15):4549–4562

    Article  MathSciNet  MATH  Google Scholar 

  35. Arqub OA (2016) Approximate solutions of DASs with nonclassical boundary conditions using novel reproducing kernel algorithm. Fundamenta Informaticae 146(3):231–254

    Article  MathSciNet  MATH  Google Scholar 

  36. Arqub OA, Abo-Hammour Z (2014) Numerical solution of systems of second-order boundary value problems using continuous genetic algorithm. Inf Sci 279:396–415

    Article  MathSciNet  MATH  Google Scholar 

  37. Draa A, Bouaziz A (2014) An artificial bee colony algorithm for image contrast enhancement. Swarm and Evolutionary computation 16:69–84

    Article  Google Scholar 

  38. Raja MAZ, Shah FH, Tariq M and Ahmad I (2016). Design of artificial neural network models optimized with sequential quadratic programming to study the dynamics of nonlinear Troesch’s problem arising in plasma physics. Neur Comput Appl 1–27. doi: 10.1007/s00521-016-2530-2

  39. Ahmad, I., Ahmad, F., Raja, M.A.Z., Ilyas, H., Anwar, N. and Azad, Z. Intelligent computing to solve fifth-order boundary value problem arising in induction motor models. Neur Comput Appl 1–18. doi: 10.1007/s00521–016–2547-6

  40. Dahi ZAEM, Mezioud C, Draa A (2016) A quantum-inspired genetic algorithm for solving the antenna positioning problem. Swarm and Evolutionary Computation 31:24–63

    Article  Google Scholar 

  41. Raja MAZ, Shah FH, Alaidarous ES, Syam MI (2017) Design of bio-inspired heuristic technique integrated with interior-point algorithm to analyze the dynamics of heartbeat model. Appl Soft Comput 52:605–629

    Article  Google Scholar 

  42. Neri F, Cotta C (2012) Memetic algorithms and memetic computing optimization: a literature review. Swarm and Evolutionary Computation 2:1–14

    Article  Google Scholar 

  43. Ong YS, Lim MH, Chen X (2010) Memetic computation—past, present & future [research frontier]. IEEE Comput Intell Mag 5(2):24–31

    Article  Google Scholar 

  44. Kim J, Kim CS, Geem ZW (2014) A memetic approach for improving minimum cost of economic load dispatch problems. Math Probl Eng 2014

  45. Zaman MF, Elsayed SM, Ray T, Sarker RA (2016) Evolutionary algorithms for dynamic economic dispatch problems. IEEE Trans Power Syst 31(2):1486–1495

    Article  Google Scholar 

  46. Holland JH (1975) Adaptation in natural and artificial systems. University of Michigan press, Ann arbor, MI

    Google Scholar 

  47. Zhu Z, Zhang F, Li C, Wu T, Han K, Lv J, Li Y, Xiao X (2015) Genetic algorithm optimization applied to the fuel supply parameters of diesel engines working at plateau. Appl Energy 157:789–797

    Article  Google Scholar 

  48. Hong YY, Lai YM, Chang YR, Lee YD, Liu PW (2015) Optimizing capacities of distributed generation and energy storage in a small autonomous power system considering uncertainty in renewables. Energies 8(4):2473–2492

    Article  Google Scholar 

  49. Shahrokhabadi S, Khoshfahm V, Rafsanjani HN (2014) Hybrid of natural element method (NEM) with genetic algorithm (GA) to find critical slip surface. Alexandria Engineering Journal 53(2):373–383

    Article  Google Scholar 

  50. Shahrokhabadi S, Toufigh MM (2013) The solution of unconfined seepage problem using natural element method (NEM) coupled with genetic algorithm (GA). Appl Math Model 37(5):2775–2786

    Article  MathSciNet  MATH  Google Scholar 

  51. Ruiz GR, Bandera CF, Temes TGA, Gutierrez ASO (2016) Genetic algorithm for building envelope calibration. Appl Energy 168:691–705

    Article  Google Scholar 

  52. Nocedal J, Wright SJ (2006) Sequential quadratic programming. Num Opt 529–562

  53. Subathra MSP, Selvan S, Victoire T, Christinal AH, Amato U (2015) A hybrid with cross-entropy method and sequential quadratic programming to solve economic load dispatch problem. Systems Journal, IEEE 9(3):1031–1044

    Article  Google Scholar 

  54. Han X, Quan L, Xiong X (2015) A modified gravitational search algorithm based on sequential quadratic programming and chaotic map for ELD optimization. Knowl Inf Syst 42(3):689–708

    Article  Google Scholar 

  55. Nesterov Y, Nemirovskii A, Ye Y (1994) Interior-point polynomial algorithms in convex programming (Vol. 13). Society for industrial and applied mathematics, Philadelphia

    Book  MATH  Google Scholar 

  56. Duan C, Fang W, Jiang L, Liu J (2015) Adaptive barrier filter-line-search interior point method for optimal power flow with FACTS devices.Generation. Transmission & Distribution, IET 9(16):2792–2798

    Article  Google Scholar 

  57. Sindekar AS, Agrawal AR, Pande VN (2013) Comparison of some optimization techniques for efficiency optimization of induction motor. International Journal of Engineering Science and Technology 5(6):1303

    Google Scholar 

  58. Sivasubramani S, Ahmad M (2014) Hybrid harmony search algorithm and interior point method for economic dispatch with valve-point effect. International Journal of Emerging Electric Power Systems 15(3):253–261

    Article  Google Scholar 

  59. Victoire TAA, Jeyaku Mar AE (2004) Hybrid PSO–SQP for economic dispatch with valve point effect. Int J Elect Power Energy Syst 71(1):51–59

    Article  Google Scholar 

  60. Hemamalini S, Simon SP (2008) Emission constrained economic dispatch with valve-point effect using particle swarm optimization. IEEE Region 10 Conference Tencon

  61. Kim JO, Shin D-J, Park J-N, Singh C (2002) Atavistic genetic algorithm for economic dispatch with valve point effect. Elsevier Science BV Electric Power Systems Research 62:201–207

    Article  Google Scholar 

  62. Kurt A, Çenesiz Y, Tasbozan O (2015) On the solution of burgers’ equation with the new fractional derivative. Open Phys 13:355–360

    Article  Google Scholar 

  63. Çenesiz Y, Baleanu D, Kurt A, Tasbozan O (2016) New exact solutions of Burgers’ type equations with conformable derivative. Waves Random Complex Media 1–14

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Authors and Affiliations

  1. Department of Electrical Engineering, COMSATS Institute of Information Technology, Attock, Pakistan

    Muhammad Asif Zahoor Raja & Usman Ahmed

  2. Department of Computer and Information Science, Pakistan Institute of Engineering and Applied Sciences, Nilore, Pakistan

    Aneela Zameer

  3. Department of Economics, Federal Urdu University of Arts Science and Technology, Islamabad, Pakistan

    Adiqa Kausar Kiani

  4. Department of Electrical Engineering, International Islamic University, Islamabad, Pakistan

    Naveed Ishtiaq Chaudhary

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  1. Muhammad Asif Zahoor Raja
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  2. Usman Ahmed
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  4. Adiqa Kausar Kiani
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Correspondence to Naveed Ishtiaq Chaudhary.

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Raja, M.A.Z., Ahmed, U., Zameer, A. et al. Bio-inspired heuristics hybrid with sequential quadratic programming and interior-point methods for reliable treatment of economic load dispatch problem. Neural Comput & Applic 31 (Suppl 1), 447–475 (2019). https://doi.org/10.1007/s00521-017-3019-3

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