A user response reliability evaluation method based on incentive demand response

Abstract

The invention discloses a user response reliability evaluation method under an exciting demand response, which is carried out according to the following steps: 1. Acquiring the historical power consumption data of a resident user and the power consumption load curve given by a power network; 2. Establish the user's response behavior model, and calculate the parameters of the user's response behavior model by using the least square method; 3. Establish the reliability index of single user response, and standardize the reliability index of single user response by principal component analysis; Combined with the response behavior model and response reliability index of users, the load curve of next response is predicted, and the reliability of user response is calculated. The invention establishes a user response behavior model under the incentive policy by studying the influence of different incentives on the user response, and solves the response behavior model parameters according to the historical data, thereby evaluating the response result of the user, thereby providing a basis and a reference for the demand response policy of the power grid.

Description

technical field [0001] The invention relates to the field of response reliability evaluation, in particular to user response load forecasting and response reliability evaluation methods. Background technique [0002] With the development of the economy, the electricity consumption of users continues to grow, and the increase in electricity demand promotes the reform of the power system; electricity demand response enables users to actively change their original electricity consumption habits through electricity price signals or incentive policies, so as to improve The load curve serves the purpose of shaving peaks and filling valleys. At present, Jiangsu Power Grid has carried out demand response work in the demonstration area, sending response signals to users through load integrators, and obtaining users' electricity consumption data by installing smart meters. [0003] For the user's response behavior, some scholars at home and abroad have studied it. The main methods ar...

AI Technical Summary

Problems solved by technology

The price elasticity matrix and based on the principle of consumer psychology are to study the user's response behavior model under the time-of-use electricity price, and change the user's electricity consumption mode by changing the electricity price, but the time-of-use electricity price is not suitable for domestic demand response policies, based on statistical principles Need to get enough historical response load data

In addition, after implementing the demand response policy, it is necessary to evaluate the response results. At present, there are few researches on response reliability and related response reliability indicators at home and abroad. Therefore, it is necessary to study user response behavior and response reliability.

Images