Effects of Communication Network Performance on Dynamic Pricing in Smart Power Grid

In our fight against global warming and excessive carbon emission, smart power grid has emerged as a useful tool for its ability to integrate renewable energy sources with traditional energy sources in a single distribution system. Smart power grid depends on consumption scheduling and dynamic pricing to match power supply and demand, and to avoid significant fluctuation in power load. A supply demand mismatch or a large deviation in the power load may cause power outage and damage to equipments. In the literature, various dynamic pricing schemes have been proposed to manage and control power load. However, these existing works often assume perfect communication network performance, where pricing information and control messages can be transmitted to remote users without delay and without transmission error. In practice, communication channel is error prone and network delay is not negligible. In view of the situation, this paper begins by studying the effects of network delay and transmission error on achieving a desired power load through dynamic pricing. We find that these communication network impairments may impose a lower bound on price update interval, and an upper bound on price update step size. Based on the findings, we further propose a heuristics algorithm to determine the price update interval and price update step size, for a given requirement of maximum deviation in power load from a desired level. We have evaluated the proposed algorithm through random event simulations. Evaluation results confirm that, in the presence of network delay and transmission error, deviation from the desired power load can be limited for a range of number of users and price sensitivity of users.