This paper focuses on day-ahead (DA) retailing for fixed and Time-of-Use (TOU) price taker customers and DA real time pricing for active customers who participate in short-term markets. Customersâ response to the offered hourly prices are modeled using an hourly acceptance function which includes decreasing linear probability density functions based on the hourly minimum and maximum retail prices allowed by market regulators. Furthermore, the retailer offers to its active customers to participate in the DA demand response program and voluntary reduce their real time consumption for offered incentives. Numerical studies represent the effect of implementing demand response programs on the total benefit of retailing.
Y, S., & Yousefi, G. (2014). Retail Pricing and Day-Ahead Demand Response in Smart Distribution Networks. Computational Intelligence in Electrical Engineering, 4(4), 23-32.
MLA
shaghayesh Y; GholamReza Yousefi. "Retail Pricing and Day-Ahead Demand Response in Smart Distribution Networks". Computational Intelligence in Electrical Engineering, 4, 4, 2014, 23-32.
HARVARD
Y, S., Yousefi, G. (2014). 'Retail Pricing and Day-Ahead Demand Response in Smart Distribution Networks', Computational Intelligence in Electrical Engineering, 4(4), pp. 23-32.
VANCOUVER
Y, S., Yousefi, G. Retail Pricing and Day-Ahead Demand Response in Smart Distribution Networks. Computational Intelligence in Electrical Engineering, 2014; 4(4): 23-32.