Consumer Psychology Based Optimal Portfolio Design for Demand Response Aggregators
Demand response (DR) has received much attention for its ability to balance the changing power supply and demand with flexibility. DR aggregators play an important role in aggregating flexible loads that are too small to participate in electricity markets. In this work, a DR operation framework is p...
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doaj-4b28de4088d54ecb9fec5829deb62c022021-04-23T16:14:44ZengIEEEJournal of Modern Power Systems and Clean Energy2196-54202021-01-019243143910.35833/MPCE.2019.0005729153212Consumer Psychology Based Optimal Portfolio Design for Demand Response AggregatorsYunwei Shen0Yang Li1Qiwei Zhang2Fangxing Li3Zhe Wang4School of Electrical Engineering, Southeast University,Nanjing,China,210096School of Electrical Engineering, Southeast University,Nanjing,China,210096The University of Tennessee,Department of Electrical Engineering and Computer Science,Knoxville,TN,USA,37996The University of Tennessee,Department of Electrical Engineering and Computer Science,Knoxville,TN,USA,37996State Grid Shanghai Municipal Electric Power Company,Shanghai,China,200122Demand response (DR) has received much attention for its ability to balance the changing power supply and demand with flexibility. DR aggregators play an important role in aggregating flexible loads that are too small to participate in electricity markets. In this work, a DR operation framework is presented to enable local management of customers to participate in electricity market. A novel optimization model is proposed for the DR aggregator with multiple objectives. On one hand, it attempts to obtain the optimal design of different DR contracts as well as the portfolio management so that the DR aggregator can maximize its profit. On the other hand, the customers' welfare should be maximized to incentivize users to enroll in DR programs which ensure the effective and flexible load control. The consumer psychology is introduced to model the consumers' behavior during contract signing. Several simulation studies are performed to demonstrate the feasibility of the proposed model. The results illustrate that the proposed model can ensure the profit of the DR aggregator whereas the customers' welfare is considered.https://ieeexplore.ieee.org/document/9153212/Demand response (DR)aggregatorcontractconsumer psychologymulti-objective problemPareto optimization |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yunwei Shen Yang Li Qiwei Zhang Fangxing Li Zhe Wang |
spellingShingle |
Yunwei Shen Yang Li Qiwei Zhang Fangxing Li Zhe Wang Consumer Psychology Based Optimal Portfolio Design for Demand Response Aggregators Journal of Modern Power Systems and Clean Energy Demand response (DR) aggregator contract consumer psychology multi-objective problem Pareto optimization |
author_facet |
Yunwei Shen Yang Li Qiwei Zhang Fangxing Li Zhe Wang |
author_sort |
Yunwei Shen |
title |
Consumer Psychology Based Optimal Portfolio Design for Demand Response Aggregators |
title_short |
Consumer Psychology Based Optimal Portfolio Design for Demand Response Aggregators |
title_full |
Consumer Psychology Based Optimal Portfolio Design for Demand Response Aggregators |
title_fullStr |
Consumer Psychology Based Optimal Portfolio Design for Demand Response Aggregators |
title_full_unstemmed |
Consumer Psychology Based Optimal Portfolio Design for Demand Response Aggregators |
title_sort |
consumer psychology based optimal portfolio design for demand response aggregators |
publisher |
IEEE |
series |
Journal of Modern Power Systems and Clean Energy |
issn |
2196-5420 |
publishDate |
2021-01-01 |
description |
Demand response (DR) has received much attention for its ability to balance the changing power supply and demand with flexibility. DR aggregators play an important role in aggregating flexible loads that are too small to participate in electricity markets. In this work, a DR operation framework is presented to enable local management of customers to participate in electricity market. A novel optimization model is proposed for the DR aggregator with multiple objectives. On one hand, it attempts to obtain the optimal design of different DR contracts as well as the portfolio management so that the DR aggregator can maximize its profit. On the other hand, the customers' welfare should be maximized to incentivize users to enroll in DR programs which ensure the effective and flexible load control. The consumer psychology is introduced to model the consumers' behavior during contract signing. Several simulation studies are performed to demonstrate the feasibility of the proposed model. The results illustrate that the proposed model can ensure the profit of the DR aggregator whereas the customers' welfare is considered. |
topic |
Demand response (DR) aggregator contract consumer psychology multi-objective problem Pareto optimization |
url |
https://ieeexplore.ieee.org/document/9153212/ |
work_keys_str_mv |
AT yunweishen consumerpsychologybasedoptimalportfoliodesignfordemandresponseaggregators AT yangli consumerpsychologybasedoptimalportfoliodesignfordemandresponseaggregators AT qiweizhang consumerpsychologybasedoptimalportfoliodesignfordemandresponseaggregators AT fangxingli consumerpsychologybasedoptimalportfoliodesignfordemandresponseaggregators AT zhewang consumerpsychologybasedoptimalportfoliodesignfordemandresponseaggregators |
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1721512406304161792 |