Nikzad, M., Samimi, A.. (1397). Responsive Load Model Integration with SCUC to Design Time-of-Use Program. فناوری آموزش, 6(2), 223-234. doi: 10.22061/jecei.2019.5166.197
M. Nikzad; A. Samimi. "Responsive Load Model Integration with SCUC to Design Time-of-Use Program". فناوری آموزش, 6, 2, 1397, 223-234. doi: 10.22061/jecei.2019.5166.197
Nikzad, M., Samimi, A.. (1397). 'Responsive Load Model Integration with SCUC to Design Time-of-Use Program', فناوری آموزش, 6(2), pp. 223-234. doi: 10.22061/jecei.2019.5166.197
Nikzad, M., Samimi, A.. Responsive Load Model Integration with SCUC to Design Time-of-Use Program. فناوری آموزش, 1397; 6(2): 223-234. doi: 10.22061/jecei.2019.5166.197
1Department of Electrical Engineering, Islamshahr Branch, Islamic Azad University, Tehran, Iran.
2Dept. of Electrical Engineering Arak University of Technology, Arak, Iran.
تاریخ دریافت: 12 اردیبهشت 1396،
تاریخ بازنگری: 16 آذر 1396،
تاریخ پذیرش: 26 مرداد 1397
چکیده
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.
