A Game-Theoretic approach for deep valley pricing strategy in the demand side

Abstract

The introduction of large-scale renewable energy will inevitably bring significant challenges to the security and stability of power systems. Toward this end, this paper proposes a demand-side deep valley pricing (DVP) model based on game theory. First, we conduct the fuzzy affiliation-based deep valley period division by Fuzzy C Means (FCM). Subsequently, we leverage the Bayesian discriminant method to calculate the posterior probability of results to verify the proposed division method. The model incorporates a game-theoretic framework, elucidating dynamics between electric users and the utility company within the proposed DVP pricing regimen. In addition, the utility function of participators is calculated through the fluctuation of user demand load, and the Nash equilibrium (NE) is obtained using the inverse induction method. Finally, the effectiveness of the proposed DVP pricing strategy is validated by the simulation results, which can reduce the peak-to-valley difference of the load curve and promote the characteristics of users’ electricity consumption behavior.