Abstract
Generally, wind energy resources have characteristics of randomness and uncontrollability, which leads to uncertainty, intermittency and volatility of its outputs Therefore, great challenges in coordinating it with a large hydrothermal system. In this article, solves multi-objective short-term hydrothermal scheduling (MOSTHTS) problem integrated wind power generation using an effective and specific parameter less algorithm of Non-dominated Sorting Teaching Learning Based Optimization (NSTLBO) algorithm. The problem has been modelled in the form of multi-objective functions which includes fuel cost of thermal and wind generators, transmission loss and environmental emissions such as NOx, SOx and COx with various constraints of hydrothermal and wind systems. The interaction of the present NSTLBO algorithm is to decrease the operating cost of thermal and wind generators, transmission losses and different kinds of emissions. By applying this algorithm a set of non-dominated solutions are created. A fuzzy decision making approach has been involved on these solution in order to identify the best comprise solution among the group of solutions. The practicability of the proposed approach has been demonstrated on a sample test system which consists of four hydro, four thermal and two wind units. The experimental finding of this method has been compared with that of well established techniques in order to validate the performance of the test results.
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References
Zahavi J, Eisenberg L (1975) Economic-enviromental power dispatch. IEEE Trans Syst, Man, Cybern 5:485–489
Nanda J, Kothari DP, Lingamurthy KS (1988) Economic-emission load dispatch through goal programming techniques. IEEE Trans Energy Convers 3(1):26–32
Dhillon JS, Kothari DP (2000) The surrogate worth trade-off approach for multiobjective thermal power dispatch problem. Electr Power Syst Res 56(2):103–110
Sasikala J, Ramaswamy M (2012) PSO based economic emission dispatch for fixed head hydrothermal systems. Electr Eng 94(4):233–239
Talaq JH, El-Hawary F, El-Hawary ME (1994) A summary of environmental/economic dispatch algorithms. IEEE Trans Power Syst 9(3):1508–1516
Wood AJ, Wollenberg BF (2012)Â Power generation, operation, and control. Wiley
Rashid AHA, Nor KM (1991) An efficient method for optimal scheduling of fixed head hydro and thermal plants. IEEE Trans Power Syst 6(2):632–636
Jin-Shyr Y, Nanming C (1989) Short term hydrothermal coordination using multi-pass dynamic programming. IEEE Trans Power Syst 4(3):1050–1056
Salam MS, Nor KM, Hamdam AR (1998) Hydrothermal scheduling based Lagrangian relaxation approach to hydrothermal coordination. IEEE Trans Power Syst 13(1):226–235
Li CA, Svoboda AJ, Tseng CL, Johnson RB, Hsu E (1997) Hydro unit commitment in hydro-thermal optimization. IEEE Trans Power Syst 12(2):764–769
Agarwal SK (1973) Optimal stochastic scheduling of hydrothermal systems. In: Proceedings of the institution of electrical engineers, vol 120, no 6, pp 674–678. IET Digital Library
Nanda J, Bijwe PR, Kothari DP (1986) Application of progressive optimality algorithm to optimal hydrothermal scheduling considering deterministic and stochastic data. Int J Electr Power Energy Syst 8(1):61–64
Dhillon JS, Parti SC, Kothari DP (2002) Fuzzy decision-making in stochastic multiobjective short-term hydrothermal scheduling. IEE Proc-Gener, Transm Distrib 149(2):191–200
Dhillon JS, Parti SC, Kothari DP (2001) Fuzzy decision making in multiobjective long-term scheduling of hydrothermal system. Int J Electr Power Energy Syst 23(1):19–29
Benhamida F, Belhachem R (2013) Dynamic constrained economic/emission dispatch scheduling using neural network. Adv Electr Electron Eng 11(1):1–9
Dieu VN, Ongsakul W (2005) Hopfield Lagrange for short-term hydrothermal scheduling. In: Power Tech, 2005 IEEE Russia, pp 1–7. IEEE
Dhillon JS, Dhillon JS, Kothari DP (2011) Real coded genetic algorithm for stochastic hydrothermal generation scheduling. J Syst Sci Syst Eng 20(1):87–109
Narang N, Dhillon JS, Kothari DP (2012) Multiobjective fixed head hydrothermal scheduling using integrated predator-prey optimization and Powell search method. Energy 47(1):237–252
Umayal SP, Kamaraj N (2005) Stochastic multi objective short term hydrothermal scheduling using particle swarm optimization. In: INDICON, 2005 Annual IEEE, pp 497–501. IEEE
Zhou J, Liao X, Ouyang S, Zhang R, Zhang Y (2014) Multi-objective artificial bee colony algorithm for short-term scheduling of hydrothermal system. Int J Electr Power Energy Syst 55:542–553
Zhang H, Zhou J, Zhang Y, Fang N, Zhang R (2013) Short term hydrothermal scheduling using multi-objective differential evolution with three chaotic sequences. Int J Electr Power Energy Syst 47:85–99
Basu M (2011) Economic environmental dispatch of fixed head hydrothermal power systems using nondominated sorting genetic algorithm-II. Appl Soft Comput 11(3):3046–3055
Deb K, Pratap A, Agarwal S, Meyarivan TAMT (2002) A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans Evol Comput 6(2):182–197
Zitzler E, Laumanns M, Thiele L (2001) SPEA2: improving the strength Pareto evolutionary algorithm. TIK-report, p 103
Cagnina L, Esquivel SC, Coello Coello C (2005) A particle swarm optimizer for multi-objective optimization. J Comput Sci & Technol 5
Xue F, Sanderson AC, Graves RJ (2003) Pareto-based multi-objective differential evolution. In: The 2003 congress on evolutionary computation, 2003. CEC’03, vol 2, pp 862–869. IEEE
Nadakuditi G, Sharma V, Naresh R (2016) Non-dominated sorting disruption-based gravitational search algorithm with mutation scheme for multi-objective short-term hydrothermal scheduling. Electr Power Compon Syst 44(9):990–1004
Dubey HM, Pandit M, Panigrahi BK (2016) Hydro-thermal-wind scheduling employing novel ant lion optimization technique with composite ranking index. Renew Energy 99:18–34
Wu XY, Cheng CT, Shen JJ, Luo B, Liao SL, Li G (2015) A multi-objective short term hydropower scheduling model for peak shaving. Int J Electr Power Energy Syst 68:278–293
Norouzi MR, Ahmadi A, Sharaf AM, Nezhad AE (2014) Short-term environmental/economic hydrothermal scheduling. Electr Power Syst Res 116:117–127
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The authors gratefully acknowledge the authorities of Annamalai University for the facilities offered to carry out this work.
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Pasupulati, B., Kumar, R.A., Asokan, K. (2020). A Novel Approach of Non-dominated Sorting TLBO for Multi Objective Short-Term Generation Scheduling of Hydrothermal-Wind Integrated System. In: Hitendra Sarma, T., Sankar, V., Shaik, R. (eds) Emerging Trends in Electrical, Communications, and Information Technologies. Lecture Notes in Electrical Engineering, vol 569. Springer, Singapore. https://doi.org/10.1007/978-981-13-8942-9_34
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