DOI:10.35833/MPCE.2019.000572 |
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Consumer Psychology Based Optimal Portfolio Design for Demand Response Aggregators |
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Page view: 123
Net amount: 601 |
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Author:
Yunwei Shen1,2,Yang Li1,Qiwei Zhang2,Fangxing Li2,Zhe Wang3
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Author Affiliation:
1.School of Electrical Engineering, Southeast University, Nanjing 210096, China;2.Department of Electrical Engineering and Computer Science, The University of Tennessee, Knoxville, TN 37996, USA;3.State Grid Shanghai Municipal Electric Power Company, Shanghai 200122, China
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Foundation: |
This work was supported in part by the National Natural Science Foundation of China (No. 51777030), in part by CURENT, a U.S. NSF/DOE Engineering Research Center, through NSF under Award EEC-1081477, and the China Scholarship Council (No. 201706090150). |
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Abstract: |
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. |
Keywords: |
Demand response (DR) ; aggregator ; contract ; consumer psychology ; multi-objective problem ; Pareto optimization |
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Received:August 22, 2019
Online Time:2021/03/22 |
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