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A Novel Framework for Optimizing Ramping Capability of Hybrid Energy Storage Systems
- Source :
- IEEE Transactions on Smart Grid. 12:1651-1662
- Publication Year :
- 2021
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2021.
-
Abstract
- Hybrid Energy Storage System has been widely applied in aerospace, electric vehicle, and microgrid applications. The advantages are that they include complimentary technologies with both high power and energy capabilities. HESS have the potential to be useful to the bulk power systems, for example to increase the value of energy produced by variable generation resource through enabling participation in ancillary service markets. Actualizing the benefits of HESSs requires optimizing the combined ramping capability of aggregated HESS resources. To provide quality ancillary service, source of HESSs locating at multiple sites of variable generation resource must be optimally sized and cohesively controlled. Optimizing aggregated resources can be formulated as an optimization problem. Successfully solving this problem not only requires using effective solution methods but also depends on accurately and rapidly setting the necessary parameters in the problem formula. This article proposes a novel framework with double-layer structure to solve the optimization problem of aggregating ramping capability. Program developed on the upper layer focuses on solving the optimization of aggregating ramping capability among multiple HESSs and is compatible with most existing optimization algorithms. Program on lower layer of the framework targets at optimizing the local control of a single HESS based on a thorough analytics of HESS operation strategy presented in this article. Result of local optimization is also provided to upper layer program for updating the parameters in formula of optimization problem. Real time hardware-in-the-loop test is conducted to verify the performance of the optimization framework developed. The work presented is expected to provide guidance for implementing this framework in practical operation.
- Subjects :
- business.product_category
Optimization problem
General Computer Science
business.industry
Computer science
020209 energy
Distributed computing
020208 electrical & electronic engineering
02 engineering and technology
Variable (computer science)
Electric power system
Resource (project management)
Electric vehicle
Computer data storage
0202 electrical engineering, electronic engineering, information engineering
Microgrid
business
Aerospace
Subjects
Details
- ISSN :
- 19493061 and 19493053
- Volume :
- 12
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Smart Grid
- Accession number :
- edsair.doi...........3be97ab6f643d83d9d89969dcf7f77d0
- Full Text :
- https://doi.org/10.1109/tsg.2020.3023712