A Hybrid EP-SA-TS Method To Solve The Hydro – Thermal Unit Commitment Problem

Nimain Charan Nayak*
Professor, MNM Jain Engineering College, Chennai, India.
Periodicity:November - January'2014
DOI : https://doi.org/10.26634/jes.2.4.2801

Abstract

This paper presents a new approach to solve the Hydro – Thermal short-term unit commitment problem using hybrid algorithm based on Evolutionary Programming, Simulated Annealing and Tabu Search Method. The objective of this paper is to find the generation scheduling such that the total operating cost can be minimized, when subjected to a variety of constraints. This also means that it is desirable to find the optimal generating unit commitment in the power system for the next H hours. Evolutionary programming is a Global Optimization Technique for solving Unit Commitment Problem that operates on a system, which is designed to encode each unit's operating schedule with regard to its minimum up/down time. Simulated Annealing and Tabu Search methods improve the status by avoiding entrapment in local minima. A seven unit utility power system with twelve generating units in India demonstrates the effectiveness of the proposed approach; Extensive studies have also been performed for different IEEE test systems consisting of 10, 26 and 34 Units. Numerical results are shown comparing the cost solutions and computation time obtained by the proposed hybrid method and other conventional methods like Dynamic Programming, Legrangian Relaxation in reaching proper unit commitment.

Keywords

Evolutionary Programming, Simulated Annealing, Tabu Search, Unit Commitment

How to Cite this Article?

Nayak,N,C. (2014). A Hybrid EP-SA-TS Method to Solve the Hydro – Thermal Unit Commitment Problem. i-manager’s Journal on Embedded Systems, 2(4), 1-11. https://doi.org/10.26634/jes.2.4.2801

References

[1]. Snyder, WL. Powell, HD. Rayburn, C. (1987). “Dynamic Programming approach to Unit Commitment”. IEEE Trans. Power Systems, Vol.3, No.2, pp. 339-350.
[2]. Hsu. Su, Y.Y. Liang, C.C. Lin, C.J. Huang, C.T. (1991). “Dynamic Security Constrained Multi-Area Unit Commitment”. IEEE Trans. Power Systems, Vol.6, pp.1049- 1055.
[3]. Tao Li, Mohammad Shahidehpour (2005). “Price- Based Unit Commitment: A Lagrangian Relaxation Versus Mixed Integer Programming”. IEEE Trans. Power Systems, Vol. 20, No. 4, pp. 2015-2025.
[4]. Samer Takriti. John R.Birge. (2000). Using Integer Programming To Refine Lagrangian – Based Unit Commitment Solutions. IEEE Trans. Power Systems, Vol.15, No.1, pp.151-156.
[5]. Bakirtzis, A.G. Zoumas, C.E. (2000). “Lambda of Lagrangian relaxation solution to unit commitment problem”. IEEE Proc. Generation, Transmission and Distribution, Vol.147, No.2, pp.131-136.
[6]. Chuan-ping Chang. Chih-wen Liu. Chun-chang Liu.: (2000). “Unit Commitment by Lagrangian Relaxation and Genetic Algorithm”. IEEE Trans. Power Systems, Vol.15, No.2, pp.707-714.
[7]. Weerakorn Ongsakul, Nit Petcharaks (2004). “Unit Commitment by Enhanced Adaptive Lagrangian Relaxation”. IEEE Trans. Power Systems, Vol. 19, No. 1, pp. 620-628.
[8] Cohen A.I. Yoshimura, M. (1983). “A Branch and Bound Algorithm for Unit Commitment”. IEEE Trans. Power and Apparatus, Vol. 102, No.2, pp.444-451.
[9]. Ouyang, Z. Shahiderpour, S.M. (1990). “Short term Unit Commitment Expert System”. International Journal of Electrical Power System Research, Vol. 20, pp.1-13.
[10]. Su, C.C. Hsu, Y.Y. (1991). “Fuzzy Dynamic Programming: an application to Unit Commitment”. IEEE Trans. Power Systems, Vol.6, No.3, pp.1231-1237.
[11]. Anbazhagan S. and N. Kumarappan (2012). “A neural network approach to day-ahead deregulated electricity market prices Classification”, Electric Power Systems Research, Vol.86, No.3, pp.140-150.
[12]. Senjyu, T. Saber, A.Y. Miyagi, T. Shimabukuro, K. Urasaki, N. and Funabashi, T. (2005). “Fast Technique for Unit Commitment by Genetic Algorithm Based on Unit Clustering”. IEEE Proc. Generation, Transmission and Distribution, Vol. 152, No.5, pp. 705-713.
[13]. Ioannis G. Damousis, Anastasios G. Bakirtzis, Petros S. Dokopoulos (2004). “A Solution to the Unit Commitment Problem Using Integer-Coded Genetic Algorithm”. IEEE Trans. Power Systems, Vol. 19, No. 2, pp. 1165-1172.
[14]. Azadeh A. et al. (2012), “A New genetic algorithm approach for optimizing bidding strategy viewpoint of profit maximization of a generation company”, Expert Systems with Applications, Vol. 39, No.4, pp.1565–1574.
[15]. Padhy, N.P. (2000). Unit Commitment using Hybrid Models: “A Comparative Study for Dynamic Programming, Expert Systems, Fuzzy System and Genetic Algorithm”. International Journal of Electrical Power & Energy Systems, Vol.23, No.1, pp.827-836.
[16]. Zhuang, F. Galiana, F.D. (1990). “Unit Commitment by Simulated Annealing”. IEEE Trans. On Power Systems, Vol. 5, No.1, pp. 311-318.
[17]. Kirkpatrick, S. Gelatt, JR., C.D. Vecehi, M.P. (1983). “Optimisation by Simulated Annealing”. Science, Vol. 220, pp. 4598.
[18]. Shokri Z. Selim. Alsultan, K. (1991). “A Simulated Annealing Algorithm for the Clustering Problem”, Pattern Recognition, Vol. 24, No. 10, pp. 1003-1008.
[19]. Mantawy, A.H. Youssef L. Abdel-Magid. Shokri Z. Selim. (1998). “A Simulated Annealing Algorithm for Unit Commitment”. IEEE Trans. On Power Systems, Vol. 13, No. 1, pp. 197-204.
[20]. Mantawy, A.H. Youssef L. Abdel-Magid, Shokri Z. Selim. (1998). “A Unit Commitment By Tabu Search”. IEE Proc. Generation, Transmission and Distribution, Vol. 145, No. 1, pp.56-64.
[21]. Whei-Min Lin. Fu-Sheng Cheng. Ming-Tong Tsay. (2002). “An Improved Tabu Search for Economic Dispatch with Multiple Minima”. IEEE Trans. Power Systems, Vol.17, No.1, pp.108-112.
[22]. Yong-Gang Wu. Chun-Ying Ho. Ding-Yi Wang. (2000). “A Diploid Genetic Approach to Short-Term Scheduling of Hydro-Thermal System”. IEEE Trans. Power Systems, Vol.15, No.4, pp.1268-1274.
[23]. Ying-Yi Hong. Chih-Yuan Li.: (2002). “Genetic Algorithm Based Economic Dispatch for Cogeneration Units Considering Multiplant Multibuyer Wheeling”. IEEE Trans. Power Systems, Vol.17, No.1, pp.134-140.
[24]. Mantawy, A.H. Youssef L. Abdel-Magid, Shokri Z. Selim. (1999). “Integrating Genetic Algorithm, Tabu Search and Simulated Annealing For the Unit Commitment Problem”. IEEE Tans. Power Systems, Vol.14, No.3, pp.829-836.
[25]. Bai, X. Shahidehpour, M. (1996). “Hydro-Thermal Scheduling by Tabu Search and Decomposition Method”. IEEE Trans. Power Systems, Vol.11, No.2, pp.968-975.
[26]. Bai, X. Shahidehpour, M. (1997). “Extended Neighbourhood Search Algorithm for Constrained Unit Commitment”. International Journal of Electrical Power and Energy Systems, Vol.19, No.5, pp.349-356.
[27]. Juste, K.A. Kita, H. Tanaka, E. Hasegawa, J. (1999). An Evolutionary Programming Solution to the UC Problem. IEEE Trans. Power Systems, Vol.14, No.4, pp.1452-1459.
[28]. Yang, H.T. Yang P.C. Huang, C.L. (1996). “Evolutionary Programming Based Economic Dispatch for Units with Non-smooth Fuel Cost Functions”. IEEE Trans. Power Systems, Vol.11, No.1, pp.112-117.
[29]. Teuvo Kohonen, (1998). “An Introduction to Neural Computing”. Neural Networks Journal, Vol. 1, No.1, pp. 3- 16.
[30]. Wood A.J. Woollenberg, B.F. (1996). “Power Generation and control” 2nd Edn.. John Wiley and Sons, New York.
[31]. Fogel, D.B.: (1995). “Evolutionary Computation, Toward a New Philosophy of Machine Intelligence”. IEEE Press, New York.
[32]. Back, T.: (1996). “Evolutionary Algorithms in Theory and Practice”. Oxford University Press, New York.
[33]. Fogel, L.J. Owens, A.J. Walsh, M.J.: (1996). “Artificial Intelligence through Simulated Evolution”. John Wiley & Sons, New York.
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