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Calculation of Transmission Prices for Bilateral Contracts and Optimization of Pool Contracts Using Intelligent Techniques

Sushil Kumar Gupta*, Jwala Narasimha Rao**

* Professor, Department of Electrical Engineering, Deenbandhu Chhotu Ram University, Murthal (Sonepat) Haryana, India.

** Wipro Technology, Greater Noida, India.

Periodicity:July - September'2018
DOI : https://doi.org/10.26634/jee.12.1.14319

Abstract

The objective of ELD is to determine economic sharing of generating power from different generating stations to meet the demand while satisfying the constraints. Power scheduling is one of the most important problems in the optimization of operation price of the power system. In deregulated power system environment Economic load dispatch (ELD) has the objective of generation allocation to the power generators such that the total prices paid to Gencos is minimized and all operating constraints are satisfied. Various techniques are available to address ELD and other power system optimization problems. The soft computing techniques like particle swarm optimization (PSO), GA and lemda iteration are being used to improve the optimization results. This paper presents and compares the performance of the PSO, GA, and ABC with conventional ELD method for optimization of pool prices. A study on IEEE 26 Bus System has been made for calculating transmission Prices for Bilateral Contracts between GENCOs and DISCOs at different buses. Intelligent techniques have been applied to optimize pool prices and minimizing transmission losses. Transmission pricing are calculated using MWmile method. The results of these techniques are compared, which show better performance of ELD+PSO method over ELD+ABC and ELD+GA methods both.

Keywords

GA (Genetic Algorithm), PSO (Particle Swarm Optimization), ABC (Artificial Bee Colony), Pool Contracts, Transmission pricing, DISCO Participation Matrix (DPM), Independent System Operator (ISO)

How to Cite this Article?

Gupta S. K., and Gupta, D. (2018). Calculation of Transmission Prices for Bilateral Contracts and Optimization of Pool Contracts Using Intelligent Techniques. i-manager’s Journal on Electrical Engineering, 12(1), 33-40. https://doi.org/10.26634/jee.12.1.14319

References

[1]. Bhattacharya, A., & Chattopadhyay, P. K. (2010a). Biogeography-based optimization for different economic load dispatch problems. IEEE Transactions on Power Systems, 25(2), 1064-1077.

[2]. Bhattacharya, A., & Chattopadhyay, P. K. (2010b). Hybrid differential evolution with biogeography-based optimization for solution of economic load dispatch. IEEE Transactions on Power Systems, 25(4), 1955-1964.

[3]. David, A. K. (1998). Dispatch methodologies for open access transmission systems. IEEE Transactions on Power Systems, 13(1), 46-53.

[4]. Galiana, F. D., & Phelan, M. (2000). Allocation of transmission losses to bilateral contracts in a competitive environment. IEEE Transactions on Power Systems, 15(1), 143-150.

[5]. Gupta, S. K., & Chawala, P. (2015). Economic load dispatch in thermal power plant considering additional constraints using curve Fitting and ANN. Review of Energy Technologies and Policy Research, 2(1), 16-28.

[6]. Gupta, S. K., & Sharma, H. D. (2016). Optimization of pool contracts using intelligent techniques and calculation of transmission prices for bilateral contracts. IUP Journal of Electrical & Electronics Engineering, 9(3), 1-12.

[7]. Gupta, S., & Sharma, H. D. (2015). Transmission prices for bilateral contracts and optimization of pool contracts using GA and ABC. International Journal Series in Engineering Science (IJSES), 1(1), 39-48.

[8]. Happ, H. H. (1994). Cost of wheeling methodologies. IEEE Transactions on Power Systems, 9(1), 147-156.

[9]. Kennedy, J., & Eberhart, R. C. (1942). Particle swarm optimization. Proc. IEEE International Conference on Neural Networks (pp. 1942-1948). IEEE.

[10]. Lai, L. L. (Ed.). (2001). Power System Restructuring and Deregulation: Trading, Performance and Information Technology. John Wiley & Sons.

[11]. Maan, R. S., Mahela, O. P., and Gupta, M. (2013). Economic load dispatch optimization of six generator generating unit using particle swarm optimization. IOSRJEEE, 6 (2), 21-27.

[12]. Musirin, I., Ismail, N. H. F., Kalil, M. R., Idris, M. K., Rahman, T. K. A., & Adzman, M. R. (2009). Ant Colony Optimization (ACO) technique in economic power dispatch problems. In Trends in Communication Technologies and Engineering Science (pp. 191-203). Springer, Dordrecht.

[13]. Rau, N. S. (1989). Certain considerations in the pricing of transmission service. IEEE Transactions on Power Systems, 4(3), 1133-1139.

[14]. Saeh, I. S., & Khairuddin, A. (2009). Implementation of Artificial Intelligence Techniques for steady state security Assessment in Pool market. International Journal of Engineering, 3(1), 1-11.

[15]. Shi, Y., & Eberhart, R. (1998, May). A modified particle swarm optimizer. In Evolutionary Computation Proceedings, 1998. IEEE World Congresson Computational Intelligence., The 1998 IEEE International Conference on (pp. 69-73). IEEE.

[16]. Shi, Y., & Eberhart, R. C. (1999). Empirical study of particles warm optimization. In Evolutionary computation, 1999. CEC 99. Proceedings of the 1999 congress on (Vol. 3, pp. 1945-1950). IEEE.

[17]. Yuen, Y. S. C., & Lo, K. L. (2003). Simulations of bilateral energy markets using MATLAB. COMPEL- The International Journal for Computation and Mathematics in Electrical and Electronic Engineering, 22(2), 424-443.

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