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Simulated Annealing Based Coordinated Wind-Thermal Unit Commitment
Abstract
Efficient and optimum economic operation and planning of electric power generation system have occupied important position in electric power industry. The dependability of thermal power alone results in emission of polluting gases and depletion of conventional sources. This increased the interests in integrating renewable energy sources like wind, tidal, geothermal etc. into existing thermal power system. Due to the development in the field of power electronics and other allied technologies wind is preferred. For such coordinated systems, utilization of wind along with thermal results in alteration of reliability criteria owing to the intermittency and unpredictability of wind power generation. This paper deals with integrating wind energy with an existing thermal power system using Simulated Annealing (SA) Algorithm along with Constrained Dynamic Economic Dispatch (CDED) method. CDED is used to calculate wind power to be integrated to the existing system obtained by intermixing thermal and wind constraints. SA algorithm is used for optimizing. Simulation result shows the effect of wind power generation in reducing total fuel cost.
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References
Yue, C.D., Liu, C.M., and Liou Eric, M.L.(2001) “A transition toward a sustainable energy future: feasibility assessment and development strategies of wind power in Taiwan”, Energy Policy,, 29, pp. 951–963
A. G. Bakirtzis and P. S. Dokopoulos, (1988) “Short term generation scheding in a small autonomous system with unconventional energy sources,” IEEETrans. Power Syst., vol. 3, no. 3, pp. 1230–1236,
Chang, T.J., Wu, Y.T., Hsu, H.Y., Chu, C.R., and Liao, C.M.: ‘Assessment of wind characteristics and wind turbine characteristics in Taiwan’, Renew. Energy, 2003, 28, pp. 851–871
Chen, C.L., Lee, T.Y., and Jan, R.M. (2006) “Optimal wind-thermal coordination dispatch in isolated power systems with large integration of wind capacity”, Energy Convers. Manag., 47, (18–19), pp. 3456–347
Chun-Lung Chen, (2008)“Optimal Wind–Thermal Generating Unit Commitment” IEEE transactions on energy conversion, vol. 23, no. 1, march
Allen J Wood, Bruce F Wollenberg, “Power generation, operation, and control” second edition. Authorized by Wiley India P.Ltd.
Hongwei, Z., Xuanfu, L., and Yuzhao, F. (1999)“Optimal operation of large scale wind-diesel generation systems’, Renew. Energy, 16, pp. 851–854
Bakirtzis, A.G., and Petridis, (1996) “A genetic algorithm solution to the unit commitment problem”, IEEE Trans., PWRS-11, (1), pp. 83–92
Doherty, R., and O’Malley, (2005) “A new approach to quantify reserve demand in systems with significant installed wind capacity”, IEEE Trans., PWRS-20, (2), pp. 587–595
Rob A Rutenbar (1989) “Simulated annealing algorithms an overview” IEEE Confer., PWRS-89, (2), pp. 8755, Page No. 19-26
Mantawy, A.H., and Selim, (1998) “A simulated annealing algorithm for unit commitment”, IEEE Trans, PWRS-13, (1), pp. 197–204
Merlin, A., and Sandrin, (1983) “A new method for unit commitment at electricite De France”, IEEE Trans., PWRS-102, (5), pp. 1218–1225
G. K. Purushothama and Lawrence Jenkins (2006) “Simulated Annealing With Local Search—A Hybrid Algorithm for Unit Commitment” IEEE, ieee transactions on power systems, vol. 18, no. 1,
S. Kirkpatrick, C.D. Gelatt and M. P. Vecchi (1983) “Optimization by Simulated Annealing “ Science, vol. 220, No. 4598, pp. 671-680
John J Grainger and “William D Stevenson Power system analysis” Authorized by Wiley India P.Ltd Page No. 78-150.
DOI: http://dx.doi.org/10.36039/AA082016002.
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