This paper proposes an application of Differential Evolution Technique(DE) for solving short- term scheduling problem.Generally Short-term hydrothermal scheduling involves the hour by hour scheduling of all generation on a system to achieve minimum production cost.A set of starting conditions is given and the optimal hourly schedule that minimizes the desired objective,while meeting hydraulic and steam constraints is sought and solved using Differential Evolution. . The results are examined to validated the effectiveness of the algorithm in comparision with other Meta heuristic algorithms like GA, GS, IFEP, SA and PSO.

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Application Of Differential Evolution Technique For Short Term Hydrothermal Scheduling And Its Comparision With Other Meta Heuristic Search Algorithms

S.Padmini*, C. Christober Asir Rajan**
* Research Scholar, SRM University, Chennai, India.
** Associate Professor, Pondichery Engineering College, India.
Periodicity:January - March'2013
DOI : https://doi.org/10.26634/jee.6.3.2179

Abstract

This paper proposes an application of Differential Evolution Technique(DE) for solving short- term scheduling problem.Generally Short-term hydrothermal scheduling involves the hour by hour scheduling of all generation on a system to achieve minimum production cost.A set of starting conditions is given and the optimal hourly schedule that minimizes the desired objective,while meeting hydraulic and steam constraints is sought and solved using Differential Evolution. . The results are examined to validated the effectiveness of the algorithm in comparision with other Meta heuristic algorithms like GA, GS, IFEP, SA and PSO.

Keywords

Hydrothermal Scheduling, Differential Evolution, Discharge rate

How to Cite this Article?

Padmini, S., and Rajan, C. C. A. (2013). Application of Differential Evolution Technique for Short Term Hydrothermal Scheduling and its Comparision with Other Meta Heuristic Search Algorithms. i-manager’s Journal on Electrical Engineering, 6(3), 37-41. https://doi.org/10.26634/jee.6.3.2179

References

[1]. Wood, A.J. and Wollenberg, (1984). B.F.: Power Generation, Operation and Control, John Wiley and Sons, New York, 1984.
[2]. Ferrero, R.W.; Rivera, J.F.; Shahidehpour, S.M., (1998). “A dynamicprogramming two-stage algorithm for long-termhydrothermal scheduling of multireservoir systems”, IEEE Transactions on Power Systems, Volume 13, Issue 4, Nov 1998 Page(s):1534 –1540.
[3]. Esteban Gil,Hugh Rudnick, (2003). ”Short-term hydrothermal generation scheduling model using a genetic algorithm”,IEEE Transactions on Power Systems, 2003, Vol 18, No.4,1256-1264.
[4]. Brannud H, Bubenko JA, Sjelvgren D. (1986). Optimal short term operation planning of a large hydrothermal power system based on non linear network flow concept. IEEE Trans PWRS 1986;1(4):75-82.
[5]. Wong KP, Wong YW. (1994). Short-term hydro thermal scheduling Part 1: Simulated annealing approach. IEE Proc Generat Transmission Distribut 1994;141(5):497-501.
[6]. Yang PC, Yang HT, Huang CL. (1996). Scheduling short term hydro thermal generation using evolutionary programming techniques. IEE Proc Generat Transmission Distribut 1996;143(4):371-6.
[7]. Dhillon JS, Parti SC, Kothari DP. (2002). Fuzzy decision-making in stochastic multi objective short term hydro thermal scheduling. IEE Proc Generet Transmission Distribut 2002;149(2):191-200.
[8]. Padmini.S, Rajan C.C.A, Murthy.P, ”Application of Improved PSO technique for short term hydrothermal generation scheduling of power system” Lecture Notes in Computer Science7076 LNCS (PART I) PP-176-182.
[9]. Storn R, Price K. (2007). Differntial Evolution:=.Changa Chung-Fu, Wong Ji-Jeng, Chiou Ji-Pyng , Su Ching-Tzong. Robust searching hybrid differential evolution method for optimal reactive power planning in large scale distribution systems. Electric Power Syst Res 2007;77:430-7.
[10]. Coelho Leandro dos Santos, Mariani Viviana Cocco. (2007). Improved differential evolution algorithms for handling economic dispatch optimization with generator constraints. Energy Convers Manage 2007;48:1631-9.
[11]. Sinha, N. Loi-Lei Lai, (2006). “Meta Heuristic Search Algorithms for Short-Term Hydrothermal Scheduling”, International Conference on Machine Learning and Cybernetics, Location:. Dalian, 2006.
[12]. Lai JC, Leung,F.H, Sai Ho-Li. (2010). Economic load dispatch using differential evolution with double wavelet mutation operations. Evolutionary computation (CEC), 2010 IEEE.
[13]. J. J. Liang, A. K. Qin, P. N. Suganthan and S. Baskar, (2006). "Comprehensive Learning Particle Swarm Optimizer for Global Optimization of Multimodal Functions", IEEE T. on Evolutionary Computation, Vol. 10, No. 3, pp. 281-295, June 2006.
[14]. S.Huang, (1999). “Application of genetic based fuzzy systems to hydroelectric generation scheduling ", IEEE T. on Energy Conversion, pp. 724-730, 1999.
[15]. R.Naresh, J.Sharma, (1999). “Two-phase neural network bsed solution technique for short term hydrothermal scheduling, Generation, Transmission and Distribution”, IEE Proceedings. pp 657-663.(1999)
[16]. Yinghai Li; Xiaohua Dong; Cuimei Lv; Faxing Du; (2011). “A modified shuffled frog leaping algorithm and its application to short-term hydrothermalscheduling”, Vol.4, 2011 , Page(s): 1909 - 1913
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