Calculation Method for Electricity Price and Rebate Level in Demand Response Programs

Abstract

Demand response programs (DRs) can be implemented with less investment costs than those in power plants or facilities and enable us to control power demand. Therefore, they are highly expected as an efficient option for power supply–demand-balancing operations. On the other hand, DRs bring new difficulties on how to evaluate the cooperation of consumers and to decide electricity prices or rebate levels with reflecting its results. This paper presents a theoretical approach that calculates electricity prices and rebate levels in DRs based on the framework of social welfare maximization. In the authors’ proposal, the DR-originated changes in the utility functions of power suppliers and consumers are used to set a guide for DR requests. Moreover, optimal electricity prices and rebate levels are defined from the standpoint of minimal burden in DRs. Through numerical simulations and discussion on their results, the validity of the authors’ proposal is verified.

Impact of renewable energy integration on a novel method for pricing incentive payments of incentive‐based demand response program

“…Here, we use the normalized sigmoidal‐like satisfaction function given by $$\begin{equation} F({d_t}) = \frac{1}{{1 + {e^{-{X_t}({d_t} - {Y_t})}}}} \end{equation}$$where $${X_t}$$ and $${Y_t}$$ are the coefficients of the satisfaction function. These coefficients are obtained by measuring the actual data of electricity demand, thereby building the cumulative frequency distribution of the electricity consumption then approximate the distribution curve to the corresponding satisfaction function [19]. Here, we propose the use of the fuzzy logic method when there is a limitation in terms of actual data, so that we can construct sets of coefficients for the satisfaction function in a reasonable way.…”

“…Therefore, the balance of interests between the two parties when participating in the DR program should be ensured. On that basis, the social welfare maximization (SWM) framework that is often used for electricity market models, is introduced in references [18][19][20][21][22][23]. With the SWM framework, an optimal function is established consisting of sub-functions describing the benefits of the supplier and the consumer.…”