Research on user-side flexible load scheduling method based on greedy algorithm

In the context of increasing flexible load represented by smart household appliances, this study aims to establish a demand response model of residential flexible load to minimize electricity cost and reduce grid load variance. In this study, the flexible loads of residents are classified considering different load demand response modes, and demand response models are established for all kinds of loads. To make full use of residential electricity data, this paper established a user side flexible load multi -objective optimization scheduling model, the model for electricity cost and power grid load variance minimizing the objective function, and the safe operation of the meter and the adjustable resources as constraint, load and energy storage battery time-sharing electricity price for resident's flexible optimization scheduling. Finally, the greedy algorithm is use to calculate and analyze the model. The result show that the model is effective and feasible.(c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Automated summary

This study aims to establish a demand response model for residential flexible load to minimize electricity cost and reduce grid load variance in the context of increasing flexible load represented by smart household appliances. The study classifies the flexible loads of residents and establishes demand response models for different load demand response modes. To make full use of residential electricity data, a user-side flexible load multi-objective optimization scheduling model is developed, considering minimizing electricity cost and power grid load variance as the objective function. The results show that the model is effective and feasible.