Real-Time Implementation of Electric Spring Using a Nine Switch Converter Topology for Combined Power Control in a Hybrid Microgrid System
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING(2023)
Institute of Technical Education & Research
Abstract
This work proposes an electric spring using a novel nine-switch converter topology (NSC) for power control of an isolated hybrid microgrid system. The hybrid microgrid system comprises a constant power source of a micro-hydro-based self-excited induction generator and a photovoltaic system equipped with battery energy storage. Generally, the ‘generation following load’ (GFL) strategy is used for an isolated system. This suggests the generation be varied according to the load demand. An electric spring works on a ‘load following generation’ (LFG) strategy. Hence, the load demand can be adjusted according to the generation. In this proposed work the loads are segregated into two types, namely sensitive load and non-sensitive load. A nine-switch converter is used in this work, which operates partly as a series and partly as a shunt compensator. The series side of NSC is connected to a non-sensitive load to form an electric spring. The Shunt side of the NSC acts as a power modulator to control the PV side power flow. The proposed isolated hybrid microgrid system is subjected to load and source variation. To study the performance analysis, MATLAB/Simulink is used to simulate the proposed system. The simulation performance is tested with OPAL-RT 5700 system. Typical results are given to prove our claims.
MoreTranslated text
Key words
Battery energy storage system,Electric spring,Generation following load,High integration ratio,Load following generation,Nine switch converter,Photovoltaic,Self-excited induction generator
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined