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An improved local search involving bee colony optimization using lambda iteration combined with a golden section search method to solve an economic dispatch problem

Wybrane pełne teksty z tego czasopisma
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Warianty tytułu
PL
Ulepszona metoda rozwiązywania problemu ekonomicznego rozsyłu energii wykorzystująca algorytmy rojowe i Iterację lambda
Języki publikacji
EN
Abstrakty
EN
This paper presents an improved local search method using bee colony optimization (ILS-BCO) to solve an economic dispatch (ED) problem with smooth cost function characteristic. The proposed ILS-BCO algorithm is an integration of lambda iteration and bee colony optimization (CLI-BCO) combined with golden section search and bee colony optimization (CGS-BCO). To show its effectiveness, the ILS-BCO was applied to test two systems consisting of either 6 or 15 power generating units. Results confirm that the proposed ILS-BCO approach is capable of obtaining rapid convergence and a high quality solution efficiently.
PL
W artykule zaproponowano metodę rozwoiązywania problemu ekonomicznego rozsyłu energii z uwzględnieniem kosztów. Wykorzystano metodę optymalizacji opartą na algorytmach rojowych. Metodę przetestowano na dwóch systemach złożonych z 6 lub 15 jednostek generatorów.
Rocznik
Strony
202--208
Opis fizyczny
Bibliogr. 36 poz., rys., tab.
Twórcy
  • Faculty of Engineering, Mahasarakham University, Mahasarakham 44150, Thailand
  • Faculty of Engineering, Rajamangala University of Technology Lanna, Lampang, Thailand
  • Faculty of Engineering, Mahasarakham University, Mahasarakham 44150, Thailand
  • Faculty of Engineering, Rajamangala University of Technology Lanna, Lampang, Thailand
Bibliografia
  • [1] A. J. Wood and B. F. Wollenberg, Power Generation Operation and Control. New York: Wiley, 1984.
  • [2] Leandro dos Santos Coelho and Viviana Cocco Mariani, “Combining of Chaotic Differential Evolution and Quadratic Programming for Economic Dispatch Optimization With ValvePoint Effect”, IEEE TRANSACTIONS ON POWER SYSTEMS, 21 (2006), No. 2, 989-996
  • [3] M. Ramamoorty, R. N. Dhar, and P. K. Mukherjee, “Reducedgradient method for economic dispatch,” in Electrical Engineers Proceedings of the Institution of Electrical Engineers, 120 (1973), Issue 11, 608-610
  • [4] R.J. Ringlee and D.D. Williams, ”Economic dispatch operation considering valve throttling losses II-distribution of system loads by the method of dynamic programming,” IEEE Trans. Power Appar. Syst. 81 (1963), Issue 3, 615-620
  • [5] Ahmed Farag, S. Al-Baiyat and T. C. Cheng, “Economic Load Dispatch Multi objective Optimization Procedures Using Linear Programming Techniques,” IEEE Transactions On Power Systems, 10 (1995), No. 2, 731-738
  • [6] Albert M. Sasson, “Nonlinear Programming Solutions for LoadFlow, Minimum-Loss, and Economic Dispatching Problems,” IEEE Transactions on Power Apparatus and Systems, 88 (1996), No. 4, 399_409
  • [7] V. Kumar, J. Singh, Y. Singh, and S. Sood, “Optimal Economic Load Dispatch Using Genetic Algorithms,” International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering, 9 (2015), No. 4, 463-470
  • [8] Samuel A. Oluwadare, Gabriel B. Iwasokun, Olatubosun Olabode, O. Olusi, and Akintoba E. Akinwonmi, “Genetic Algorithm-based Cost Optimization Model for Power Economic Dispatch Problem,” British Journal of Applied Science & Technology, 15 (2016), Issue 6, 1-10
  • [9] Ali Q. Al-Shetwi and Muwaffaq I. Alomoush, “A New Approach to the Solution of Economic Dispatch using Genetic Algorithm,” Journal of Engineering and Technology, 7 (2016), No. 1, 40-48
  • [10] K. Srikanth and V. HariVamsi, “Partical Swarm Optimization Technique for Dynamic Economic Dispatch,” International Journal of Research in Engineering and Technology, 5 (2016), Issue 5, 460-466
  • [11] Haifeng Zhang, “An Improved Particle Swarm Optimization Algorithm for Dynamic Economic Dispatch Problems,” International Journal of Innovative Research in Engineering & Management (IJIREM), 3 (2016), Issue 4, 264-266
  • [12] Hossein Lotfi, Ali Dadpour, and Mahdi Samadi, “Solving Economic Dispatch in Competitive Power Market Using Improved Particle Swarm Optimization Algorithm,” International Journal of Smart Electrical Engineering, 6 (2017), No.1, 35-41
  • [13] Dhaval K. Thesia, Pradeep Jangir, and Indrajit N. Trivedi, “Economic Emission Dispatch Problem Solution Using Ant Colony Optimization of Micro-grid in Island Mode,” International Journal of Advance Engineering and Research Development, 2 (2015), Issue 5, 89-95
  • [14] M. N. Nwohu and Osaremwinda Osarobo Paul, “Evaluation of Economic Load Dispatch Problem in Power Generating Stations by the Use of Ant Colony Search Algorithms,” International Journal of Research Studies in Electrical and Electronics Engineering (IJRSEEE), 3 (2017), Issue 1, 20-29
  • [15] Vijay Kumar Joshi, “Optimization of Economic Load Dispatch Problem by using Tabu Search Algorithm,” International Journal of Latest Trends in Engineering and Technology, 8 (2017), Issue 4-1, 182-187
  • [16] K. Chandrasekaran, S. P. Simon, and N. P. Padhy, “Cuckoo Search Algorithm for Emission Reliable Economic Multi- Objective Dispatch Problem,” IETE Journal of Research, 60 (2014), Issue 2, pp.128-138
  • [17] Thang Trung Nguyen, Dieu Ngoc Vo, and Bach Hoang Dinh, “Cuckoo search algorithm for combined heat and power economic dispatch,” Electrical Power and Energy Systems, ELSEVIER, 81 (2016), 204-214
  • [18] Mohsen Darabian, Seyed Masoud Moheni-Bonab, and Behnam Moohammadi-Ivatloo, “Improvement of Power System Stability by Optimal SVC Controller Design Using Shuffled Frog Leaping Algorithm,” IETE Journal of Research, 61 (2015), Issue 2, 160-169
  • [19] K. Selvakumar, K. Vijayakumar, D. Sattianadan, and C. S. Boopathi, “Shuffled Frog Leaping Algorithm (SFLA) for Short Term Optimal Scheduling of Thermal Units with Emission Limitation and Prohibited Operational Zone (POZ) Constraints,” Indian Journal of Science and Technology, 9 (2016), No. 42, 16
  • [20] M. Venkatesh and R. Raghutu, “Economic Load Dispatch using Simulated Annealing Algorithm,” International Research Journal of Engineering and Technology (IRJET), 2 (2015), Issue 3, 1961-1964
  • [21] Ziane Ismail, Benhamida Farid, and Graa Amel, “Simulated Annealing Optimization for Generation Scheduling with Cubic Fuel Cost Function,” WSEAS Transactions on Information Science and Applications, 14 (2017), 64-69
  • [22] Ehsanolah Assareh and Mojtaba Biglari, “A Novel Approach to Capture the Maximum Power Generation from Wind Turbines Using Hybrid MLP Neural Network and Bees Algorithm (HNNBA),” IETE Journal of Research, 62 (2015), Issue 3, 368-378
  • [23] Navpreet Singh Tung and Sandeep Chakravorty, “Solution to Economic Power Dispatch Planning Problem considering Generator Constraints using Artificial Bee Colony Algorithm,” International Journal of Hybrid Information Technology, 9 (2016), No. 5, 399-406
  • [24] Gitanjali Mehta, Raghvendra Pratap Singh, and Vinod Kumar Yada, “Optimization of Combined Economic Emission Dispatch Problem using Artificial Bee Colony Method,” International Journal on Cybernetics & Informatics (IJCI), 6 (2017), No. 1, 107-118
  • [25] G. Li, P. Niu, X. Xiao, “Development and investigation of efficient artificial bee colony algorithm for numerical function optimization”, Applied Soft Computing, 12 (2012), Issue 1 320–332
  • [26] A. Bahriye, D. Karaboga, “A modified Artificial Bee Colony algorithm for real-parameter optimization”, Information Sciences, 192 (2012), Issue 1, 120-142
  • [27] 27. WF. Gao, S. Liu, L. Huang, “A global best artificial bee colony algorithm for global optimization”, Journal of Computational and Applied Mathematics, 2362 (2012), Issue 11, 2741-2753
  • [28] T.K. Sharma, M. Pant, “Enhancing the food locations in an artificial bee colony algorithm,” in: IEEE Swarm Intelligence Symposium (SIS), Paris, France, 17 (2013), Issue 10, 1939– 1965
  • [29] D. Karaboga and B. Basturk. “On the performance of artificial bee colony (ABC) algorithm,” Applied soft computing, Science Direct, Elsevier, 8 (2006), Issue 1, 687-697
  • [30] J. Kiefer, “Sequential minimax search for a maximum”, in Proceedings of the American Mathematical Society, 4 (1953), 502–506
  • [31] R. Rahmani, M. F. Othman, R. Yusof, and M. Khalid, “Solving Economic Dispatch Problem using Particle Swarm Optimization by an Evolutionary Technique for Initializing Particles”, Journal of Theoretical and Applied Information Technology, 46 (2012), No. 2, 526-536
  • [32] Ankur Sharma and Hemant Mahala, “Economic Load Dispatch Problem by Particle Swarm Optimization”, International Journal of Engineering Science and Computing, 6 (2016), No. 3, 2237-2243
  • [33] Wanchai Khamsen and Chiraphon Takeang, “Hybrid of Lamda and Bee Colony Optimization for Solving Economic Dispatch”, PRZEGLAD ELEKTROTECHNICZNY, 9 (2016), 220-223
  • [34] A. Dihem, A. Salhi, D. Naimi and A. Bensalem, "Solving smooth and non-smooth economic dispatch using water cycle algorithm," 2017 5th International Conference on Electrical Engineering - Boumerdes (ICEE-B), Boumerdes, Algeria, (2017), 1-6
  • [35] 35. S. Sayah, A. Hamouda, “A hybrid differential evolution algorithm based on particle swarm optimization for non-convex economic dispatch problems”, Applied Soft Computing journa1 home, 13 (2013), Issue 4, 1608-1619
  • [36] B. Mandal, P.K. Roy, S. Mandal, “Economic load dispatch using krill herd algorithm”, International Journal of Electrical Power & Energy Systems, 57 (2014), 1-10
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-43b8c55c-d630-41a9-98f9-917399d0f7d7
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