Load Flow Allocation  to Improve the Fairness of MW-Mile Method

M. Bagas Syaatnuartoro; Sasongko Pramono Hadi; Sarjiya Sarjiya; Yusuf Susilo Wijoyo

doi:10.22146/ijitee.70431

Load Flow Allocation to Improve the Fairness of MW-Mile Method

https://doi.org/10.22146/ijitee.70431

M. Bagas Syaatnuartoro^(1*), Sasongko Pramono Hadi⁽²⁾, Sarjiya Sarjiya⁽³⁾, Yusuf Susilo Wijoyo⁽⁴⁾

(1) Universitas Gadjah Mada
(2) Universitas Gadjah Mada
(3) Universitas Gadjah Mada
(4) Universitas Gadjah Mada
(*) Corresponding Author

Abstract

In a deregulated power system, an appropriate wheeling cost is required to provide valuable economic information to market participants, such as generation and transmission companies. The load flow method is used in power wheeling to determine the condition of the existing system after the wheeling participant is added to the system. In the load flow method, it can be seen how much power is generated from a generator. However, the power flow method cannot determine wheeling generator allocation to the power flow in each transmission network. For this reason, power tracing will be used to determine the wheeling generator allocation. Power tracing is also a solution that could improve the fairness of determining wheeling costs. This paper discusses the power tracing method to determine load flow allocation for wheeling generators using the genetic algorithm (GA) method. GA is one of the optimization techniques, where in power tracing with GA, the load flow allocations (LFA) problem will be assumed as an optimization problem. Calculation with tracing and without tracing will be compared to demonstrate the benefits of the proposed technique. Experimental results showed that the MW-mile method with LFA yielded more expensive wheeling costs than the conventional method. The cost is more expensive due to the absence of cost reduction as in the conventional MW-mile method, and wheeling users pay wheeling costs based on the transmission usage. Although wheeling costs are high, the LFA method provides a fair price because wheeling users pay a fee based on the actual usage. In the future, another power tracing may be used to help determine wheeling costs.

Keywords

Power Wheeling;MW-Mile;Load Flow Allocation;Tracing;Genetic Algorithm.

Full Text:

PDF

References

L. Hirth, F. Ueckerdt, and O. Edenhofer, “Integration Costs Revisited - An Economic Framework for Wind and Solar Variability,” Renewable Energy, Vol. 74, pp. 925–939, Feb. 2015.

Y.R. Sood, N.P. Padhy, and H.O. Gupta, “Wheeling of Power under Deregulated Environment of Power System: A Bibliographical Survey,” IEEE Transactions on Power Systems, Vol. 17, No. 3, pp. 870–878, Aug. 2002.

H.M. Merrill and B.W. Erickson, “Wheeling Rates Based on Marginal-Cost Theory,” IEEE Power Engineering Review, Vol. 9, No. 11, pp. 39–40, Nov. 1989.

Y.S. Wijoyo, S.P. Hadi, and Sarjiya, “Review Perhitungan Biaya Wheeling (Wheeling Cost Calculation Review),” Jurnal Nasional Teknik Elektro dan Teknologi Informasi, Vol. 9, No. 1, pp. 116–122, Feb. 2020.

H.H. Happ, “Cost of Wheeling Methodologies,” IEEE Transactions on Power Systems, Vol. 9, No. 1, pp. 147–156, Feb. 1994.

H. Hamada and R. Yokoyama, “Wheeling Charge Reflecting the Transmission Conditions Based on the Embedded Cost Method,” Journal of International Council on Electrical Engineering, Vol. 1, No. 1, pp. 74–78, 2011.

A. Saxena, S.N. Pandey, and L. Srivastava, “Genetic Algorithm Based Wheeling Prices Allocation for Indian Power Utility by Using MVA-Mile and MW-Mile Approaches,” 2016 International Conference on Emerging Trends in Electrical Electronics & Sustainable Energy Systems (ICETEESES), 2016, pp. 60–63.

O. Pop, S. Kilyeni, P. Andea, C. Barbulescu, dan C. Craciun, “Power Flow Tracing Method for Electricity Transmission and Wheeling Pricing,” Journal of Sustainable Energy, Vol. 1, No. 4, pp. 63–70, Dec. 2010.

J. Bialek, “Tracing the Flow of Electricity,” IEE Proceedings - Generation, Transmission and Distribution, Vol. 143, No. 4, pp. 313–320, Jul. 1996.

C.T. Su and J.H. Liaw, “Power Wheeling Pricing Using Power Tracing and MVA-KM Method,” 2001 IEEE Porto Power Tech Proceedings, 2001, pp. 38–43.

X. Bai, G.P-. Wei, M. Gang, Y.G. Gui, et al., “A Spatial Load Forecasting Method Based on the Theory of Clustering Analysis,” Physics Procedia, Vol. 24, pp. 176–183, 2012.

M.H. Sulaiman, M.W. Mustafa, and O. Aliman, “Transmission Loss and Load Flow Allocations via Genetic Algorithm Technique,” TENCON 2009 - 2009 IEEE Region 10 Conference, 2009, pp. 1–5.

A.J. Wood, B.F. Wollenberg, and G.B. Sheblé, Power Generation, Operation, and Control. Hoboken, USA: John Wiley & Sons, 2013.

Yasir, Sarjiya, and T. Haryono, “Algoritma Genetika Sebagai Solusi Optimal Power Flow pada Sistem Kelistrikan 500 Kv Jawa Bali,” Vol. 15, No. 3, pp. 107–113, Aug. 2013.

G.A. Orfanos, G.T. Tziasiou, P.S. Georgilakis, and N D. Hatziargyriou, “Evaluation of Transmission Pricing Methodologies for Pool Based Electricity Markets,” 2011 IEEE Trondheim PowerTech, 2011, pp. 1–8.

A.A.A.E. Ela, M.A. Abido, and S.R. Spea, “Optimal Power Flow Using Differential Evolution Algorithm,” Electrical Engineering, Vol. 91, No. 2, pp. 69–78, Aug. 2009.

DOI: https://doi.org/10.22146/ijitee.70431