Tariff Packaged Pricing Strategy for Electricity Retailers Considering Consumer Irrationality

To address the challenge that traditional single-pricing methods used by power retailers struggle to achieve dynamic and precise pricing as well as behavior guidance for new-type power users, a power retail packaged pricing method considering users' irrationality under a multi-level market framework is proposed. First, a principal-agent game framework is constructed based on the operational mode of power retailers to establish the foundational model for packaged pricing. Second, a decreasing quadratic convex function is constructed to simulate users' loss-aversion behavior, and a demand response model for users exhibiting irrational behavior is established by combining it with the user's power procurement cost model. Subsequently, in view of the uncertainties associated with users' power consumption fluctuations and electricity prices, the conditional value at risk (CVaR) theory is introduced to establish a comprehensive risk-return decision-making model for power retailers. Finally, an optimization model for packaged electricity prices is established, and the GUROBI solver along with an improved particle swarm optimization algorithm are employed to solve it. MATLAB simulations indicate that the introduction of the multi-level market effectively reduces users' costs, and the proposed pricing method increases power retailers’ profits, smooths the users' load curves, and alleviates regulation pressure on the generation side.