| Autor: |
Sungyoon Song, Sungwoo Kang, Sangho Lee, Chang Ki Kim |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
IEEE Access, Vol 11, Pp 134604-134613 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2169-3536 |
| DOI: |
10.1109/ACCESS.2023.3337373 |
| Popis: |
To achieve the goal of carbon neutrality, increasing the contribution of renewable energy sources (RESs) such as solar and wind to power grids is necessary. However, existing energy management systems are not well-equipped to handle the inherent volatility of RESs, and previous attempts to develop new management systems have mostly been limited to small scales such as microgrids and buildings. The Korea Electrotechnology Research Institute and Korea Institute of Energy Research jointly developed a renewables management system (RMS) for large-scale grids that comprises four parts: a 12-h-ahead solar irradiance forecast model; look-ahead horizon stability assessment; generation o f future RES penetration scenarios by a generative adversarial networks model; and confidence level-based adaptive droop control strategy for energy storage systems. In particular, the adaptive droop control obtains the joint probability distribution at each substation based on copula theory, and the droop gain changes with the confidence level. Simulations were performed to demonstrate the effectiveness of the proposed RMS at managing large-scale grids with high RES penetration. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
