Document Type : Original Research Paper

Authors

1 Department of Electrical Engineering, Islamshahr Branch, Islamic Azad University, Tehran, Iran.

2 Dept. of Electrical Engineering Arak University of Technology, Arak, Iran.

Abstract

Background and Objectives: Suitable scheming as well as appropriate pricing of demand response (DR) programs are two important issues being encountered by system operators. Assigning proper values could have effects on creating more incentives and raising customers’ participation level as well as improving technical and economical characteristics of the power system. Here, time of use (TOU) as an important scheme of DR is linearly introduced based on the concepts of self and cross price elasticity indices of load demand.
Methods: In order to construct an effective TOU program, a combined optimization model over the operation cost and customers’ benefit is proposed based on the security-constrained unit commitment (SCUC) problem. Supplementary constraints are provided at each load point with 24-hour energy consumption requirement along with DR limitations.
Results: IEEE 24-bus test system has been employed to investigate the different features of the presented method. By varying DR potential in the system, TOU rates are determined and then their impacts on the customers' electricity bill, operation cost, and reserve cost as well as load profile of the system are analyzed. In addition, the effect of network congestion as a technical limitation is studied. The obtained results demonstrate the effectiveness and applicability of the proposed method.
Conclusion: The simulation results demonstrate that the TOU rates leads to financial profit for all customers, reduction of peak load as well as the operation cost while 24-hour energy consumptions of customers at load buses have been fulfilled. Furthermore, the operation cost decreases gradually by attaining more flat load profile. In addition, the effect of lines congestion on the proposed method has been investigated and it has been shown that lines congestion leads to profit reduction of customers at load points connected to the congested lines.


======================================================================================================
Copyrights
©2018 The author(s). This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, as long as the original authors and source are cited. No permission is required from the authors or the publishers.
======================================================================================================

Keywords

Main Subjects

[1] Department of Energy, U. S. Benefits of Demand Response in Electricity Markets and Recommendations for Achieving Them, February 2006.

[2] S. Kiliccote, D. Olsen, M. D. Sohn, M. A. Piette, “Characterization of demand response in the commercial, industrial, and residential sectors in the United States,” Wiley Interdisciplinary Reviews: Energy and Environment, 5(3), 2015.

[3] Staff report, “Assesment of demand response and advanced metring,” Federal Energy Regulatory Commission, September 2009.

[4] C. River, “Primer on demand side management,” Report for the World Bank, February 2005.

[5] H. A. Aalami, G. R. Yousefi, M. P. Moghaddam, “Modeling and prioritizing demand response programs in power markets,” Electric Power Systems Research, 80(4): 426-435, 2009.

[6] R. Aazami, K. Aflaki, M. R. Haghifam, “A demand response based solution for LMP management in power markets,” International Journal of Electrical Power & Energy Systems, 33(5): 1125-1132, 2011.

[7] A. Faruqui, S. George, “Quantifying customer response to dynamic pricing,” Electricity Journal, 18(4): 53-63, 2005.

[8] L. Goel, Q. Wu, P. Wang, “Nodal price volatility reduction and reliability enhancement of restructured power systems considering demand-price elasticity,” Electric Power Systems Research, 78(10): 1655-1663, 2008.

[9] F. Schweppe, M. Caramanis, B. Tabors, “Evaluation of spot price based electricity rates,” IEEE Transactions on Power Apparatus Systems, PAS-104(7): 1644–1655, 1985.

[10] F. C. Schweppe, M. C. Caramanis, R. D. Tabors, R. E. Bohn, “Spot Pricing of Electricity,” Norwell MA: Kluwer Academic Publishers, 1988.

[11] A. Moshari, A. Ebrahimi, “Reliability-based nodal evaluation and prioritization of demand response programs,” International Transactions on Electrical Energy Systems, 25(12): 3384-3407, 2014.

[12] M. Nikzad, B. Mozafari, “Reliability assessment of incentive- and priced-based demand response programs in restructured power systems,” International Journal of Electrical Power & Energy Systems, 56: 83-96, 2014.

[13] B. Kladnik, G. Artac, A. Gubina, “An assessment of the effects of demand response in electricity markets,” International Transactions on Electrical Energy Systems, 23(3): 380-391, 2013.

[14] E. Bompard, R. Napoli, B. Wan, “The effect of the programs for demand response incentives in competitive electricity markets,” European Transactions on Electrical Power, 19(1): 127-139, 2009.

[15] M. Nikzad, B. Mozafari, M. Bashirvand, S. Soleymani, A. M. Ranjbar,  “Designing time-of-use program based on stochastic security constrained unit commitment considering reliability index,” Energy, 41(1): 541-548, 2012.

[16] M. Shahidehpour, H. Yamin, Z. Y. Li, Market Operations in Electric Power Systems, New York: Wiley, 2002.

[17] N. Amjady, H. Nasiri-Rad, “Security constrained unit commitment by a new adaptive hybrid stochastic search technique,” Energy Conversion and Management, 52(2): 1097-1106, 2011.

[18] M. Shafie-khah, M. Parsa Moghaddam, M. K. Sheikh-El-Eslami, “Unified solution of a non-convex SCUC problem using combination of modified Branch-and-Bound method with quadratic programming,” Energy Conversion and Management, 52(12, p. 3425-3432, 2011.

[19] N. Amjady, A. A. Rashidi, H. Zareipour, “Stochastic security-constrained joint market clearing for energy and reserves auctions considering uncertainties of wind power producers     and      unreliable       equipment,”       International Transactions on Electrical Energy Systems, 23(4): 451-472, 2013.

[20] Mehrtash, M., et al., Fast stochastic security-constrained unit commitment using point estimation method. International Transactions on Electrical Energy Systems: 671-688.

[21] F. Kamyab, M. Amini, S. Sheykhha, M. Hasanpour, M. M. jalali, “Demand response program in smart grid using supply function bidding mechanism,” IEEE Transactions on Smart Grid, 7(3): 1277-1284, 2016.

[22] M. Alipour, K. Zare, M. Abapour, “MINLP probabilistic scheduling model for demand response programs integrated energy hubs,” IEEE Transactions on Industrial Informatics, 14(1): 79-88, 2018.

[23] E. Dehnavi, H. Abdi, “Optimal pricing in time of use demand response by integrating with dynamic economic dispatch problem,” Energy, 109: 1086-1094, 2016.

[24] H. Abdi, E. Dehnavi, F. Mohammadi, “Dynamic economic dispatch problem integrated with demand response (DEDDR) considering non-linear responsive load models,” IEEE Transactions on Smart Grid, 7(6): 2586-2595, 2016.

[25] R. E. Rosenthal, GAMS: A User’s Guide. Washington DC.

[26] C. Grigg, et al., “The ieee reliability test system-1996. A report prepared by the reliability test system task force of the application of probability methods subcommittee,” IEEE Transaction on Power Systems, 14(3): 1010-1020, 1999.

[27] J. Wang, N. E. Redondo, F.D. Galiana, “Demand-side reserve offers in joint energy/reserve electricity markets,” IEEE Transactions on power systems, 18(4): 1300-1306, 2003.


LETTERS TO EDITOR

Journal of Electrical and Computer Engineering Innovations (JECEI) welcomes letters to the editor for the post-publication discussions and corrections which allows debate post publication on its site, through the Letters to Editor. Letters pertaining to manuscript published in JECEI should be sent to the editorial office of JECEI within three months of either online publication or before printed publication, except for critiques of original research. Following points are to be considering before sending the letters (comments) to the editor.


[1] Letters that include statements of statistics, facts, research, or theories should include appropriate references, although more than three are discouraged.

[2] Letters that are personal attacks on an author rather than thoughtful criticism of the author’s ideas will not be considered for publication.

[3] Letters can be no more than 300 words in length.

[4] Letter writers should include a statement at the beginning of the letter stating that it is being submitted either for publication or not.

[5] Anonymous letters will not be considered.

[6] Letter writers must include their city and state of residence or work.

[7] Letters will be edited for clarity and length.

CAPTCHA Image