Optimization of peak-valley pricing policy based on a residential electricity demand model

In order to deal with the rapid growth in residential electricity consumption, residential peak-valley pricing (PVP) policies have been implemented in 12 provinces in China. However, being inappropriate, the residential PVP policies have delivered no significant results. The challenge to China's PVP policy research lies in obtaining high-resolution electricity consumption data and modeling residents' behavior. By simulating household electricity load profiles, an electricity price policy response model and a residential PVP policy optimization model, are constructed and applied in this paper to simulate the effect of the current residential PVP policy and optimize the policy. The results show that the peak-shaving capability (represented by the reduction in peak load) of the PVP policy in 11 provinces is less than 3%, while the PVP policy in Gansu Province has increased household electricity bills by about 5.7%. In addition, the optimized PVP can reduce household electricity bills by 3% and reduce peak electricity consumption by about 9%. The 12 provinces should adopt the 3-phase division method and optimize the electricity price in the peak and valley (i.e. off-peak) periods respectively. This paper promotes the research on China's residential PVP policy and provides an effective reference for the design of the PVP policy.

Automated summary

This study constructs electricity price policy response model and residential peak-valley pricing (PVP) policy optimization model by simulating household electricity load profiles, and proposes methods to optimize PVP policy. The results show that the original PVP policy has limited effect in some provinces, while the optimized policy can reduce household electricity bills and peak electricity consumption.