SoC-Based Droop Coefficients Stability Region Analysis of the Battery for Stand-Alone Supply Systems With Constant Power Loads

Wang, Rui; Sun, Qiuye; Hu, Wei; Li, Yushuai; Ma, Dazhong; Wang, Peng

doi:10.1109/tpel.2021.3049241

Cited by 113 publications

(66 citation statements)

References 32 publications

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“…Droop control is a good option for stand-alone power systems with several batteries since it allows inverters to communicate without interfering with each other [62], [63]. Small-signal instability occurs when the droop coefficients of batteries fluctuate with their SOC and charge/discharge mode.…”

Section: Overview Of Control Aspect Of Microgridsmentioning

confidence: 99%

“…However, conventional impedance-based techniques can only examine the stability point of the droop coefficients, not the stability zone. The authors [63] provided a stability region analysis method based on droop coefficients. The authors discussed the charge/discharge SOCbased droop regulated battery, the P&Q controlled distributed generator, and the constant power load.…”

Section: Overview Of Control Aspect Of Microgridsmentioning

confidence: 99%

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A Comprehensive Review of Microgrid Control Mechanism and Impact Assessment for Hybrid Renewable Energy Integration

et al. 2021

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This paper describes a comprehensive review of microgrid control mechanism and impact assessment for hybrid grid. Building the model of sustained energy growth is one of the actions to achieve the Sustainable Development Objective (SDO) and change the global fossil fuel system. For co-operation in the development of one independent supplier of renewable energy, the microgrid is essential. Hybrid solar energy microgrid is also a solution for reducing fossil fuel consumption and providing an environmentally sustainable solution to rising rural electricity demand. The most common renewable energy options in the microgrid are solar photovoltaics, wind turbines and biomass. The environmentally sustainable and technologically innovative installation is convenient everywhere. Hybrid microgrid-based renewable energy, however, is confronted, given its intermittent and variable source efficiency, by challenges such as voltage instability, frequency instability, charge malfunction and power quality problems. The paper thus offers a critical overview of the micro grid growth, economic analysis and control strategy.

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Section: Overview Of Control Aspect Of Microgridsmentioning

confidence: 99%

Section: Overview Of Control Aspect Of Microgridsmentioning

confidence: 99%

A Comprehensive Review of Microgrid Control Mechanism and Impact Assessment for Hybrid Renewable Energy Integration

et al. 2021

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“…Through t-SNE [36] dimension reduction, the characteristics of ELM output data are visualized, as shown in Fig.16. In addition, the method presented in this paper can also be used in the analysis of medical EEG signal and voltage signal of power electronic equipment [37][38] . In the future, we will further try to explore and experiment on different signals in different fields.…”

Section: F Multiclassfication Capabilitymentioning

confidence: 99%

Rolling Bearing Sub-Health Recognition via Extreme Learning Machine Based on Deep Belief Network Optimized by Improved Fireworks

Luo

Zhou

et al. 2021

IEEE Access

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Rolling bearings, as the main components of the large industrial rotating equipment, usually work under complex conditions and are prone to break down. It can provide a certain theoretical basis for identifying the sub-health state of the industrial equipment by the analysis from the incipient weak signals. Thus, a subhealth recognition offline algorithm based on Refined Composite Multiscale Dispersion Entropy (RCMDE) and Deep Belief Network-Extreme Learning Machine (DBN-ELM) optimized by Improved Firework Algorithm (IFWA) is proposed. First of all, in light of the drawbacks that it is easy to fall into local optima and cross the boundary for exploding fireworks in Firework Algorithm (FWA), Cauchy mutation and adaptive dynamic explosion radius factor coefficient is introduced into IFWA. Secondly, Maximum Correlation Kurtosis Deconvolution (MCKD) optimized by the improved parameters is used to process the incipient vibration signals with nonlinearity, nonstationary, and IFWA is used to adaptively adjust to the period and the filter length in MCKD(IFWA-MCKD). Then, each sequence of signals is further extracted the feature-RCMDE to rich sample diversity. Finally, combining the powerful unsupervised learning capability from DBN and the generalization capability from ELM, DBN-ELM can be established. What's more, in order to avoid the interference of human on the parameters, IFWA is used to optimize the number of hidden nodes in DBN-ELM, and the IFWA-DBN-ELM is established. It shows that the algorithm has the higher sub-health recognition accuracy, better robustness and generalization, which has a better industrial application prospect.

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“…Mechanical and electrical faults result in changes in the winding resistance, inductance, and capacitance, and hence the winding impedance or transfer function will be changed within a particular frequency range. The FRA measurement is conducted offline without any power electronic interface and hence the issue of mirror frequency discussed in [8] is insignificant. The presented data include magnitude and phase spectrum.…”

Section: Introductionmentioning

confidence: 99%

Understanding the Influence of Power Transformer Faults on the Frequency Response Signature Using Simulation Analysis and Statistical Indicators

et al. 2021

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Frequency Response Analysis (FRA) is the most reliable technique currently used to evaluate the mechanical integrity of power transformers. While the measurement devices have been well developed over the past two decades, interpretation of the FRA signatures is still challenging regardless of the several papers published in this regard. This paper adds an attempt to understand the power transformer FRA signatures through experimental and simulation analyses. In this context, experimental FRA measurements are conducted on a 33/11 kV, 30 MVA transformer under various faults, including winding deformation, the short circuit turns, loss of clamping, and bushing fault. At the same time, the high-frequency transformer model that comprises series capacitance, self-inductance, series resistance, and mutual inductance is simulated using MATLAB / Simulink to compare simulation and experimental results. The correlation between physical circuit parameters and various faults facilitates a better understanding of each fault's effect on the FRA signature. To quantify the impact of such faults, correlation coefficient, the absolute sum of logarithmic error, standard deviation, and sum square error are calculated with respect to the healthy signature at three frequency regions. Results show that using statistical coefficients over three frequency ranges of the FRA signature facilitates better fault identification and quantification.

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SoC-Based Droop Coefficients Stability Region Analysis of the Battery for Stand-Alone Supply Systems With Constant Power Loads

Cited by 113 publications

References 32 publications

A Comprehensive Review of Microgrid Control Mechanism and Impact Assessment for Hybrid Renewable Energy Integration

A Comprehensive Review of Microgrid Control Mechanism and Impact Assessment for Hybrid Renewable Energy Integration

Rolling Bearing Sub-Health Recognition via Extreme Learning Machine Based on Deep Belief Network Optimized by Improved Fireworks

Understanding the Influence of Power Transformer Faults on the Frequency Response Signature Using Simulation Analysis and Statistical Indicators

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