Optimal Scheduling for Dynamic Loads Using Direct Method
Keywords:
accurately, economic dispatch, efficiently, quadratic objective function, ramp rate limitsAbstract
The main objective of the dynamic economic dispatch problem is to determine the optimal schedule of output powers of all generating units to meet the load demands and losses at minimum operating cost while satisfying ramp rate and power limits. In addition, the computing time should be as soon as possible because of the scheduling interval in an hour. This paper proposed an application of the direct method with cost functions of the generator units in the quadratic form to solve the problem. In which the proposed method is simplest, applicable and having shortest computing time. To validate the proposed method was done evaluating for 6-generator units in detail and the results compared to the other methods. While to test computing time was done a simulation to the large power system, 47 generator units of Jawa-Bali System. The results state that the proposed method can work efficiently and accurately. These are in line with expectations.
References
A. Bakirtzis, et. al., 1994. Genetic algorithm solution to the economic dispatch problem. IEE Proc. Generation, Transmission and distribution, 141, 4, 377-382.
A .J. Wood and B.F. Wollenberg, 1984. Power generation, operation and control. John Wiley and Sons., New York. Bhupender S, Shivani S, Ajay N., 2013. Particle Swarm Optimization and Genetic Algorithm based Optimal
Power Flow Solutions. International Journal of Application or Innovation in Engineering & Management. 2(7): 307-315.
D. C. Walters and G. B. Sheble, 1993. Genetic algorithm solution of economic dispatch with valve-point loading. IEEE Trans. Power Syst., 8, 1325-1332.
D. N. Jeyakumar, T. Jayabarathi and T. Raghunathan, 2006. Particle swarm optimization for various types of economic dispatch problems. Elec. Power Energy Syst, 28, 36-42.
G. B. Sheble and K. Brittig, 1995. Refined genetic algorithm-economic dispatch example. IEEE Trans. on Power Systems, 10 ,1, 117-124.
H. Zein, Y. Sabri, A. Mashar, 2012. Implementation of Electricity Competition Framework with Economic Dispatch Direct Method, Telkomnika.; 10(4): 667-674.
H. Zein, R. Raharjo, 2017. Generator Capability Curve Approaches for Optimal Power Flow, IRACST–Engineering Science and Technology: An International Journal (ESTIJ), ISSN: 2250-3498, 7, 4.
IEEE Committee Report, 1971. Present practices in the economic operation of power systems. IEEE Trans. Power Appa. Syst., PAS-90, 1768-1775.
J. B. Park, K. S. Lee, J. R. Shin and K. Y. Lee, 2005. A particle swarm optimization for economic dispatch with nonsmooth cost functions. IEEE Trans. Power Syst, 20, 34-42.
J. Nanda, A. Sachan, L. Pradhan M.L. Kothari, A. Koteswara Rao, 1997. Application of artificial neural network to economic load dispatch. IEEE Trans. Power Systems, 22.
J. Tippayachai, W. Ongsakul and I. Ngamroo, 2003. Parallel micro genetic algorithm for constrained economic dispatch. IEEE Trans. Power Syst., 17, 790-797.
J. Raharjo, A. Soeprijanto, H. Zein, 2016. Multi Dimension of Coarse to Fine Search Method Development for Solving Economic Dispatch, Indonesian Journal of Electrical Engineering and Computer Science. 3, 1, 1 ~ 9.
Lee KY, El-Sharkawi MA, 2013. Tutorial on Modern Heuristic Optimization Techniques with Applications to Power Systems. IEEE Power Engineering Society.
P. H. Chen and H. C. Chang, 1995. Large-scale economic dispatch approach by genetic algorithm. IEEE Trans. on Power Systems, 10, 4, 1918-1926.
Salama, M., M., 1999. Economic control for generations in the thermal power system. Energy Conversion and Management, 40, 669-681.
Shahinzadeh H, Nasr Azadani SM, Amirkabir Jannesari N., 2014. Applications of Particle Swarm Optimization Algorithm to Solving the Economic Load Dispatch of Units in Power Systems with Valve Point Effects. International Journal of Electrical and Computer Engineering (IJECE).; 4(6): 858-867.
Y. H. Song, F, R. Morgen, and D.T.Y. Cheng, 1995. Comparison studies of genetic algorithms in power system economic dispatch. Power System Technology, 19, 3, 28-33.
Z. L. Gaing, 2004. Constrained dynamic economic dispatch solution using particle swarm optimization. IEEE Power Engineering Society General Meeting, 153-158.
W. M. Mansour, et al., 2013. Dynamic Economic Load Dispatch of Thermal Power System Using Genetic Algorithm, IRACST – Engineering Science and Technology: An International Journal (ESTIJ), ISSN: 2250-3498, 3, 2.
