An Effective Model for Demand Response Management Systems of Residential Electricity Consumers

TLDR

Conventional demand response approaches treat price signals, consumer benefit, and comfort loss as independent factors. The study proposes a holistic DR model that jointly optimizes dynamic price signals, consumer benefit, and comfort loss to maximize net consumer surplus and support mature DR programs. The model integrates dynamic price signals from the LSE, a consumer benefit function, and comfort loss into a scheduling framework linked to a home energy scheduler and smart meter. Dynamic benefit functions outperform alternatives, as demonstrated by an illustrative example.

Abstract

An effective demand response (DR) model framework for DR management systems in a residential premise is proposed. The proposed model consists of dynamic price signals from load serving entity (LSE), benefit function, and loss of consumer comfort. The conventional approaches generally consider these factors as independent in their formulation. Since these factors have functional relationship, the proposed model points to a holistic approach to capture the relationship. The scheduling model can be integrated with the home energy scheduler coupled to the smart meter, which facilitates the flow of dynamic price and energy consumption information to and from the household premise. The objective is to maximize net consumer surplus, which is formulated as a function of all aforementioned factors. A method for developing a practical and dynamic consumer benefit model for matured DR programs is proposed in this paper. For the purpose of showing the effectiveness of dynamic benefit function, a set of analytically formulated benefit functions is also considered. The suitability of the dynamic benefit function, as compared with other alternatives, is illustrated with an example. This paper also reports the dynamic price design from the view point of LSE, in order to cover the risks of wholesale price volatility.