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Real-time flexibility assessment for power systems with high wind energy penetration
Citation
Glazunova, A and Semshikov, E and Negnevitsky, M, Real-time flexibility assessment for power systems with high wind energy penetration, Mathematics, 9, (17) pp. 1-16. ISSN 2227-7390 (2021) [Refereed Article]
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Copyright Statement
Copyright 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/4.0/).
Abstract
To reduce the reliance on fossil fuel-based generation, many countries expand the use of renewable energy sources (RES) for electricity production. The stochastic and intermittent nature of such sources (i.e., wind and solar) poses challenges to the stable and reliable operation of the electric power system (EPS) and requires sufficient operational flexibility. With continuous and random changes in the EPS operational conditions, evaluating the system flexibility in a standardized manner may improve the robustness of planning and operating procedures. Therefore, the development of fast algorithms for determining system flexibility is a critical issue. In this paper, the flexibility of the EPS with high wind energy penetration is calculated in real time. In this context, the EPS flexibility is understood as the ability of the system to maintain a balance under irregular and short-term active power variations during a specified time by using the flexibility resources. The EPS flexibility calculation relies on a deterministic method developed to qualitatively and quantitatively assess the EPS readiness to changes in load. Accurate wind power forecasts and the observance of the electric circuit law when solving the optimization problem allow for determining the actual value of the EPS flexibility during a considered time.
Item Details
Item Type: | Refereed Article |
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Keywords: | electric power system, renewable energy sources, flexibility, wind power forecasting, state estimation |
Research Division: | Mathematical Sciences |
Research Group: | Applied mathematics |
Research Field: | Approximation theory and asymptotic methods |
Objective Division: | Expanding Knowledge |
Objective Group: | Expanding knowledge |
Objective Field: | Expanding knowledge in the mathematical sciences |
UTAS Author: | Semshikov, E (Mr Evgenii Semshikov) |
UTAS Author: | Negnevitsky, M (Professor Michael Negnevitsky) |
ID Code: | 151647 |
Year Published: | 2021 |
Web of Science® Times Cited: | 2 |
Deposited By: | Engineering |
Deposited On: | 2022-08-02 |
Last Modified: | 2022-09-05 |
Downloads: | 6 View Download Statistics |
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