Customized Pricing Strategy for Households Based on Occupancy-Aided Load Disaggregation

Abstract

Pricing strategies can be utilized to manage energy demand-supply imbalance and power distribution network congestion. With the application of smart meter technologies, the real-time consumption behavior of individual households can be studied to enhance the effectiveness of the formulated pricing strategy. Hence, in this paper, a customized pricing strategy based on non-intrusive load monitoring (NILM) techniques is proposed from the perspective of the energy retailer, aiming to incentivize households to change their load consumption patterns. First, the real-time occupancy state of each household is detected to identify the ability of the household to respond to the retail price. Second, the occupancy-aided factorial hidden Markov model (FHMM) is developed to facilitate the retailer to incorporate the real-time consumption behavior of households into pricing strategy formulation. Third, the real-time price elasticity of the consumption of each appliance within each household is mathematically modeled based on the real-time hidden state of each appliance. Numerical results indicate that the proposed pricing strategy is effective in managing the load consumption of households and assisting the retailer in increasing profitability.