Implementing Discrete Model of Photovoltaic System on the Embedded Platform for Real-Time Simulation

Soetedjo, Aryuanto; Sulistiawati, Irrine Budi

doi:10.3390/en13174447

Cited by 2 publications

(2 citation statements)

References 47 publications

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“…The single-phase grid-connected PV dynamic vector model was established based on the stability characteristics of the PV plants [15]. A discrete-time model was established by considering the PV power generation system as a dynamic nonlinear multimodal system [16][17][18]. The two-level PV dynamic mathematical model was established considering the dynamic response characteristics of the distribution network with a high PV penetration rate [19].…”

Section: Introductionmentioning

confidence: 99%

Research on Dynamic Modeling and Parameter Identification of the Grid-Connected PV Power Generation System

et al. 2023

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With the increasing proportion of renewable energy in the new power system, the grid-connected capacity of photovoltaic (PV) units shows an obvious upward trend, but its dynamic behavior under different penetration rates significantly affects the transient stability of the power system, so it is crucial to establish a dynamic model that meets the actual working conditions and select a suitable parameter identification method. Therefore, in this paper, based on the electromechanical transient characteristics of the grid-connected PV power generation system, the corresponding dynamic discrete equivalent model is established, and the simulation platform of the grid-connected PV power generation system is built in MATLAB/Simulink to study the adaptability of the dynamic discrete equivalent model of the grid-connected PV power generation system from the single and multiple scenarios using the ordinary least squares (OLS) and bat algorithm (BA) while comparing the generalization ability of the parameters identified by the two methods to the model. The simulation results show that the generalization ability of the parameters identified by the OLS and BA for the model in the single scenario is better, indicating that the model has good adaptability; the generalization ability of a set of general parameters identified by the BA for the model in the multiple scenarios is better than that of the OLS, indicating that the parameters identified by the BA have better adaptability. In conclusion, the dynamic discrete equivalent model of the grid-connected PV power generation system proposed in this paper can accurately reflect the dynamic characteristics of the grid-connected PV power generation system, and the parameters identified by the BA are more generalized than the OLS.

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Section: Introductionmentioning

confidence: 99%

Research on Dynamic Modeling and Parameter Identification of the Grid-Connected PV Power Generation System

et al. 2023

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“…Instead of using the real WWTP, we develop realtime monitoring using a phytoremediation model which is implemented on an embedded system. Our previous work in [29] inspires the idea of using such a model for the real-time monitoring system. By implementing a phytoremediation model on embedded hardware, it could be connected to the IoT infrastructure for real-time monitoring.…”

Section: Introductionmentioning

confidence: 99%

IoT Based Real-Time Monitoring of Phytoremediation of Wastewater using the Mathematical Model Implemented on the Embedded Systems

Hendriarianti¹,

Soetedjo²

2021

IJIES

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This paper presents the Internet of things (IoT) technology for real-time monitoring of wastewater phytoremediation. Phytoremediation is a technique to remove pollutants from the wastewater using the plants. A conventional method to monitor the phytoremediation performance is by taking the samples of the contaminants from a site and measuring them at the laboratory. This method needs many works for data preparation and analysis. A recent development on the IoT technology may eliminate such tasks by a real-time monitoring system. In the proposed realtime monitoring system, several phytoremediation models are implemented on embedded hardware and connected to the Thingspeak IoT platform. The proposed system aims to provide a real-time monitoring system to better model the phytoremediation by examining the monitoring data time interval and fitting techniques. From the experiments, the proposed monitoring system achieves a data transfer reliability of 81.4% when the period of the data transmission is one minute, which is suitable for one-day interval real-time monitoring system. The proposed monitoring system can build a phytoremediation model using a polynomial fitting with a higher fit than the existing methods using an exponential fitting. Further, the proposed method promises a better solution in terms of the best model, the low cost, and the acceptable accuracy.

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Implementing Discrete Model of Photovoltaic System on the Embedded Platform for Real-Time Simulation

Cited by 2 publications

References 47 publications

Research on Dynamic Modeling and Parameter Identification of the Grid-Connected PV Power Generation System

Research on Dynamic Modeling and Parameter Identification of the Grid-Connected PV Power Generation System

IoT Based Real-Time Monitoring of Phytoremediation of Wastewater using the Mathematical Model Implemented on the Embedded Systems

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