Residential demand response behavior analysis based on Monte Carlo simulation: The case of Yinchuan in China

Abstract

Demand response to time-varying pricing of electricity is critical to a smart grid's efficient management of electrical resources. This paper presents a new approach to quantify residential demand responsiveness to (time-of-use) TOU rates, which does not entail an econometric estimation of TOU demand equations. Based on one of the four smart grid pilots in China, our approach uses the survey data collected in 2011 from 236 residents in Yinchuan to implement a Monte Carlo simulation to obtain the minimum, expected and maximum demand responsiveness to four TOU rate designs. We find that residents do not respond to TOU pricing when the TOU rate design only causes a 10% increase in their existing electricity bills under non-TOU rates. However, their estimated peak demand responsiveness is 8.41% (21.26%) when the peak-time price increases by 20% (40%). Based on these findings, we conclude that suitably designed TOU rates are useful to the efficient operation of a smart grid.