The DOI matches its Crossref record; 64 of the 64 references it cites were found in a registry or an index.
Fundamentals and business model for resource aggregator of demand response in electricity markets
Abstract
Abstract Demand response (DR) is an effective means to help maintain the balance between power supply and demand, promote energy conservation and emission reduction. Nevertheless, the involvement of different flexible resources, including distributed generation (DG), energy storage system (EES) and especially controllable load of customers in DR programs becomes the critical element for the implementation of DR. The resource aggregators (RA), an emerging market participant, serves as the professional integrator of these widely-distributed adjustable resources and offers them convenient access to related market trading information. The participation of RAs plays a significant role in enhancing system flexibility, fully exploiting the potential of flexible resources and bridging the gap between suppliers and buyers of DR. This paper focuses on the fundamentals and business mechanism of RAs in the electricity market. First, a comprehensive review of recent literature and projects is presented, with particular attention on RAs’ roles in electricity markets as well as their difference from other market entities. Then, the business model for RA is analyzed systematically, involving resource aggregation, basic information prediction, market bidding strategy development, and settlement process. Besides, information about existing RAs around the world is collected and compared to understand the development status and existing challenges.
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Cited by
Strielkowski, W., Vlasov, A., Selivanov, K., Muraviev, K., & Shakhnov, V. (2023) · Energies · doi:10.3390/en16104025 · Cited by 237
Artificial Intelligence Enabled Demand Response: Prospects and Challenges in Smart Grid Environment
Khan, M. A., Saleh, A. M., Waseem, M., & Sajjad, I. A. (2023) · IEEE Access · doi:10.1109/access.2022.3231444 · Cited by 179
Exploiting demand-side flexibility: State-of-the-art, open issues and social perspective
D’Ettorre, F., Banaei, M., Ebrahimy, R., Pourmousavi, S. A., Blomgren, E. M. V., Kowalski, J., Bohdanowicz, Z., Łopaciuk-Gonczaryk, B., Biele, C., & Madsen, H. (2022) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2022.112605 · Cited by 160
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Evaluating Multitimescale Response Capability of EV Aggregator Considering Users’ Willingness
Xu, X., Li, K., Wang, F., Mi, Z., Jia, Y., Wei, W., & Jing, Y. (2021) · IEEE Transactions on Industry Applications · doi:10.1109/tia.2021.3081402 · Cited by 65
Self-citation
Metadata
- Authors
- Lu, X., Li, K., Xu, H., Wang, F., Zhou, Z., & Zhang, Y.
- Venue
- Energy
- Publisher
- Elsevier BV
- Published
- 2020-08
- Volume
- 204
- Pages
- 117885
- ISSN
- 0360-5442 (ISSN-L)
- OpenAlex
- W3026041860
- Cited by
- 293
- References
- 64
- FWCI
- 15.70
- Type
- journal article
- Language
- en
- Open access
- closed
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- Lu, X., Li, K., Xu, H., Wang, F., Zhou, Z., & Zhang, Y. (2020). Fundamentals and business model for resource aggregator of demand response in electricity markets. Energy. https://doi.org/10.1016/j.energy.2020.117885
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