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Modeling the Effects of Probabilistic Participation of Domestic and Industrial Customers’ in the Time-of-Use Pricing and Interruptible Load Programs

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Abstract (2. Language): 
Nowadays, demand response programs have gained importance due to their purpose of improving the operation of power systems. Demand response programs are divided into two main categories of incentive-based and price-based programs. The purpose of this paper is to model and analyze two practical and substantial demand response programs that correspond to the two types of customers in the distribution system. In this regard, the interruptible load program is intended for the industrial customers and the time-of-use (TOU) pricing program is intended for the domestic customers. The interruptible load program is a reward-based program specific to peak hours; while the time-of-use pricing program is based on three price tariffs throughout the day. An efficient model based on the information of customer price elasticity is used to analyze the customers’ response. Moreover, the level of customers’ participation is taken into account in each program using two parameters; and the effects of their probabilistic participation are evaluated in three different simulation cases. In order to analyze the proposed method, a case study is considered and the evaluation indices of the load curve are calculated and analyzed after executing the programs. The simulation results clearly indicate the efficiency of the proposed method.
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REFERENCES

References: 

[1] F. Staff, “Assessment of demand response and advanced metering,” Fed. Energy Regul. Comm. Docket AD-06-2-000, 2006.
[2] M. H. Albadi and E. El-Saadany, “A summary of demand response in electricity markets,” Electric power systems research, vol. 78, pp. 1989-1996, 2008.
[3] H. A. Aalami, M. P. Moghaddam, and G. R. Yousefi, “Evaluating the execution of the country’s TOU program and proposing an optimal program using the DR model,” The 24th International Power Conference, 2009.
[4] S. M. Mirzaei, S. Hadadipoor, “Investigating load response programs for Isfahan Power Distribution Company,” CIRED Regional Conference, Tehran, Iran, January 13th & 14th, 2013.
[5] M. J. Izad Khasti, R. Keipoor, and H. Izad Khasti, “The optimal programming of power load response based on the economic modeling of the demand function with flexible elasticity in Iran,” Journal of Iranian Energy Economics, 2015.
[6] H. A. Aalami, M. P. Moghaddam, and G. R. Yousefi, “Demand response modeling considering interruptible/curtailable loads and capacity market programs,” Appl. Energy, vol. 87, no. 1, pp. 243–250, 2010.
[7] H. A. Aalami, M. P. Moghaddam, and G. R. Yousefi, “Modeling and prioritizing demand response programs in power markets,” Electr. Power Syst. Res., vol. 80, no. 4, pp. 426–435, 2010.
[8] P. T. Baboli, M. Eghbal, M. P. Moghaddam, and H. Aalami, “Customer behavior based demand response model,” in Power and Energy Society General Meeting, 2012 IEEE, 2012, pp. 1–7.
[9] H. A. Aalami, M. P. Moghaddam, and G. R. Yousefi, “Evaluation of nonlinear models for time-based rates demand response programs,” Int. J. Electr. Power Energy Syst., vol. 65, pp. 282–290, 2015.

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