A refined consumer behavior model for energy systems: Application to the pricing and energy-efficiency problems

Chao Zhang (1) , Samson Lasaulce (2) , Li Wang (1) , Lucas Saludjian (3) , H Vincent Poor (4)

1 Central South University [Changsha]
2 CRAN - Centre de Recherche en Automatique de Nancy
3 RTE - Réseau de Transport d'Electricité [Paris]
4 Princeton University

The sum-utility maximization problem is known to be important in the energy systems literature. The conventional assumption to address this problem is that the utility is concave. But for some key applications, such an assumption is not reasonable and does not reflect well the actual behavior of the consumer. To address this issue, the authors pose and address a more general optimization problem, namely by assuming the consumer's utility to be sigmoidal and in a given class of functions. The considered class of functions is very attractive for at least two reasons. First, the classical NP-hardness issue associated with sum-utility maximization is circumvented. Second, the considered class of functions encompasses well-known performance metrics used to analyze the problems of pricing and energy-efficiency. This allows one to design a new and optimal inclining block rates (IBR) pricing policy which also has the virtue of flattening the power consumption and reducing the peak power. We also show how to maximize the energy-efficiency by a low-complexity algorithm. When compared to existing policies, simulations fully support the benefit from using the proposed approach.

Mots clés: Smart grid; demand response; inclining block rates; energy efficiency; game theory; prospect theory

Domaines: Traitement du signal et de l'image [eess.SP]; Optimisation et contrôle [math.OC]

Chao Zhang, Samson Lasaulce, Li Wang, Lucas Saludjian, H Vincent Poor. A refined consumer behavior model for energy systems: Application to the pricing and energy-efficiency problems. Applied Energy, 2022, 308, pp.118239. ⟨10.1016/j.apenergy.2021.118239⟩. ⟨hal-03466112⟩