A Pricing Method for Distribution System Aggregators Considering Differentiated Load Types and Price Uncertainty
Liang, Bomiao, Yang, Jiajia, Hou, Beiping, and He, Zhiyuan (2021) A Pricing Method for Distribution System Aggregators Considering Differentiated Load Types and Price Uncertainty. IEEE Transactions on Power Systems, 36 (3). pp. 1973-1983.
|
PDF (Author Accepted Version)
- Accepted Version
Download (717kB) | Preview |
Abstract
The utilization of demand response flexibility has become a significant method to cope with the intermittence of renewable energy sources in distributed systems. This paper proposed a new pricing method for demand response resources managed by a distribution system aggregator, which is deduced from analyzing the operating revenue within the timescale from hours to years. In the proposed model, the hourly decision-making of an aggregator is formulated as a newsvendor model and uncertainties in the long-term decisions are modelled by a backward valuation process. It maximizes the benefit of an aggregator by considering the price and quantity uncertainties of distributed load/generation in day-ahead and real-time wholesale electricity markets. Meanwhile, the coexistence of controllable and uncontrollable loads is also considered, where the former refers to electricity consumption from end-users who are equipped with smart devices for energy management, and the latter load demand of passive end-users who have no willingness or capability to participate in the demand response schemes. Finally, numerical studies are carried out to demonstrate the feasibility and effectiveness of the developed model and methods, and the impacts of active end-user percentage on the aggregator operation under the proposed pricing method are also compared and illustrated.
Item ID: | 78127 |
---|---|
Item Type: | Article (Research - C1) |
ISSN: | 1558-0679 |
Copyright Information: | © 20XX IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Date Deposited: | 15 Jun 2023 06:52 |
FoR Codes: | 49 MATHEMATICAL SCIENCES > 4901 Applied mathematics > 490108 Operations research @ 30% 49 MATHEMATICAL SCIENCES > 4903 Numerical and computational mathematics > 490304 Optimisation @ 30% 49 MATHEMATICAL SCIENCES > 4905 Statistics > 490506 Probability theory @ 40% |
SEO Codes: | 17 ENERGY > 1701 Energy efficiency > 170103 Residential energy efficiency @ 40% 17 ENERGY > 1701 Energy efficiency > 170101 Commercial energy efficiency @ 30% 17 ENERGY > 1701 Energy efficiency > 170102 Industrial energy efficiency @ 30% |
Downloads: |
Total: 95 Last 12 Months: 21 |
More Statistics |