Projects per year
Project Details
Description
Future power and energy systems with increasing integration of emergent technologies, converter-interfaced distributed generation and energy storage units as well as responsive loads, require suitable testbed setups to evaluate their performance, reliability, and stability. In this practical project work, a Power Hardware-in-the-Loop (PHIL) platform is developed to design, test and verify the integration of new technologies into various types of energy systems, mainly power electronic (PE)-based power systems. The platforms offers a reasonable tradeoff between test fidelity and coverage and provides opportunities to test advanced control algorithms for improved performance/robustness/efficiency of PE-based energy systems.
Status | Finished |
---|---|
Effective start/end date | 01/08/2021 → 28/02/2022 |
Collaborative partners
- Universidade Federal do Rio Grande do Norte
UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):
Keywords
- Integrated Energy systems
- Inverter air conditioners
- brain emotional learning
- frequency control
- multi-area power system
- Virtual power plant
- coordinated control
- Power hardware-in-the-loop (PHiL)
- Real-time simulation and Testing
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Projects
- 1 Finished
-
HeatReFlex: Green and Flexible District Heating/Cooling
Anvari-Moghaddam, A., Guerrero, J. M., Nami, H. & Mohammadiivatloo, B.
01/05/2019 → 30/04/2022
Project: Research
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Adaptive Grid Impedance Shaping Approach Applied for Grid-Forming Power Converters
De Araujo Ribeiro, R. L., Oshnoei, A., Anvari-Moghaddam, A. & Blaabjerg, F., Aug 2022, In: IEEE Access. 10, p. 83096-83110 15 p., 9851656.Research output: Contribution to journal › Journal article › Research › peer-review
Open AccessFile6 Citations (Scopus)144 Downloads (Pure) -
Data-Driven Coordinated Control of AVR and PSS in Power Systems: A Deep Reinforcement Learning Method
Oshnoei, A., Sadeghian, O., Mohammadi-Ivatloo, B., Blaabjerg, F. & Anvari-Moghaddam, A., 2021, 2021 IEEE International Conference on Environment and Electrical Engineering : EEEIC 2021. IEEE Press, p. 1-6Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review
Open AccessFile6 Citations (Scopus)148 Downloads (Pure)