Cost/comfort-oriented clustering-based extended time of use pricing

•This paper proposes a novel pricing method based on the clustering algorithm.•The proposed pricing in this paper does not require AMI that makes it more cost-effective.•The proposed method is based on analyzing the historical residential consumption data. Real-time pricing (RTP), as the most effective electricity pricing method, has recently attracted significant attention in tackling the challenges of the evolving power grid such as peak shaving and shifting, as well as the emergence of energy prosumers. However, the realization of RTP schemes require an advanced metering infrastructure (AMI). Therefore, time-of-use (ToU) pricing is still in use in residential sectors. This paper presents a novel clustering-based extended time of use pricing (ETOU) algorithm as an intermediate solution, which combines the advantages of both RTP and ToU pricing methods, without a need for AMI, while considering consumers’ desired comfort level. The proposed ETOU is designed based on analyzing the consumption patterns and the real cost of energy generation. The proposed rates are defined considering the dominant consumption and energy cost values extracted by clustering. The effectiveness of the proposed ETOU is verified through numerical analysis of a residential building with an electrical thermal system modeled as a controllable load and an electrical vehicle modeled as a delay-tolerant demand. Results show that the proposed tariffs, in comparison with RTP and ToU rates, noticeably increase the load factor and energy flexibility and decrease the maximum power ramp and electricity costs, while providing the desired comfort level. Additionally, implementation of the proposed ETOU does not require AMI despite the RTP method.