Incorporation of Survey-based Data into an Aggregation Algorithm for Residential Demand Response

被引：1

作者：

Algarni, Abdullah ^{[1
]}

Siegel, Howard Jay ^{[2
]}

Maciejewski, Anthony A. ^{[2
]}

Sulyanarayanan, Siddharth ^{[3
]}

机构：

[1] Umm Al Qura Univ, ECE Dept, Mecca 21955, Saudi Arabia

[2] Colorado State Univ, ECE Dept, Ft Collins, CO 80523 USA

[3] South Dakota State Univ, EECS Dept, Brookings, SD 57006 USA

来源：

2021 IEEE MADRID POWERTECH | 2021年

基金：

美国国家科学基金会;

关键词：

Aggregator; appliance rescheduling; comfort level; peak load; pricing; MANAGEMENT;

D O I：

10.1109/PowerTech46648.2021.9494766

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

Survey-based data of three home appliances are included in a residential demand response (DR) aggregation algorithm that performs resource re-allocation for peak demand reduction in a notional electric distribution system. In addition, new constraints are integrated into the resource allocation approach to alleviate the inconvenience of the participating customers due to rescheduling their home appliances. Our effort replaces some assumptions from prior work on the mathematical model of customer preferences with actual data from a survey to validate the prior work. The results confirm the feasibility of the DR aggregation approach in achieving profits for the aggregator while considering the comfort of the participating customers.

引用

页数：5

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