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

TL;DR

This paper introduces a refined consumer behavior model with sigmoidal utility functions for energy systems, enabling better optimization of pricing and energy efficiency while avoiding NP-hardness issues.

Contribution

It proposes a novel utility model that captures consumer behavior more accurately and develops efficient algorithms for pricing and energy efficiency optimization.

Findings

The sigmoidal utility model simplifies the optimization problem.

The new pricing policy flattens power consumption and reduces peak load.

Simulations demonstrate improved performance over existing policies.

Abstract

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.