A novel stochastic maximum power point tracking control for off-grid standalone photovoltaic systems with unpredictable load demand

This study discusses the new stochastic maximum power point tracking (MPPT) control approach towards the photovoltaic cells (PCs). PC generator is isolated from the grid, resulting in a direct current (DC) microgrid that can provide changing loads. In the course of the nonlinear systems through the time-varying delays, we proposed a Networked Control Systems (NCSs) beneath an event-triggered approach basically in the fuzzy system. In this scenario, we look at how random, variable loads impact the PC generator's stability and efficiency. The basic premise of this article is to load changes and the value matching to a Markov chain. PC generators are complicated nonlinear systems that pose a modeling problem. Transforming this nonlinear PC generator model into the Takagi-Sugeno (T-S) fuzzy model is another option. Takagi-Sugeno (T-S) fuzzy model is presented in a unified framework, for which 1) the fuzzy observer-based on this premise variables can be used for approximately in the infinite states to the present system, 2) the fuzzy observer-based controller can be created using this same premises be the observer, and 3) to reduce the impact of transmission burden, an event-triggered method can be investigated. Simulating in the PC generator model for the realtime climate data obtained in China demonstrates the importance of our method. In addition, by using a new Lyapunov-Krasovskii functional (LKF) for combining to the allowed weighting matrices incorporating mode-dependent integral terms, the developed model can be stochastically stable and achieves the required performances. Based on the T-P transformation, a new depiction of the nonlinear system is derived in two separate steps in which an adequate controller input is guaranteed in the first step and an adequate vertex polytope is ensured in the second step.To present the potential of our proposed method, we simulate it for PC generators.

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“…Pre-and post multiply to (24) by {Xm, Xm, Xm, Xm, I} and its transpose, which yields to (34). The proof can be finished consequently.…”

Section: Design Analysismentioning

confidence: 90%

“…This feature is taken into account in the model that follows. A PC cell's output voltage-current characteristic is expressed as follows [34]:…”

Section: Mathematical Modeling Of Photocell Array With Load Using The...mentioning

confidence: 99%

Observer-Based Control for a New Stochastic Maximum Power Point Tracking for Photovoltaic Systems With Networked Control System

Aslam

Tiwari

Pandey

et al. 2023

IEEE Trans. Fuzzy Syst.

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“…′ ∈ R 3 , while the control input u(t) ∈ [0, 1] regulates the MOSFET duty cycle modulation. The PV generator dynamics can be expressed as follows [19,20]:…”

Section: Photovoltaic Panel Modelmentioning

confidence: 99%

Wireless Diagnosis and Control of DC–DC Converter for Off-Grid Photovoltaic Systems

El Abbadi,

Aatabe,

Bouzid

2024

Sustainability

Self Cite

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Integrating a photovoltaic (PV) microgrid system with wireless network control heralds a new era for renewable energy systems. This fusion capitalizes on the strengths of photovoltaic technology, leveraging solar energy for electricity generation while incorporating advanced networked control capabilities. Although employing network communication to facilitate information exchange among system elements offers benefits, it also introduces novel challenges which can hinder fault diagnosis, such as packet loss and communication delay. This paper focuses on a cloud-based fault detection approach for an effective boost converter within a photovoltaic system. Faults are diagnosed using a detection algorithm based on the Lyapunov function, ensuring power optimization. The effectiveness of our approach is demonstrated through simulations of a PV generator model utilizing real-time weather data collected in Brazil, illustrating its robustness through the acquired results.

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“…New energy vehicles have become a more widely used new type of vehicle. At the same time, electric vehicles have become the main target for promoting new energy vehicles due to their mature technology and better maintenance efficiency (Aatabe et al, 2021). One of the core technologies for electric vehicles is the high-efficiency Permanent Magnet Motors…”

Section: Introductionmentioning

confidence: 99%

Optimal efficiency point membership incorporating fuzzy logic and automatic control of various charging stages for electric vehicles

Wang,

2024

Front. Mech. Eng.

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Introduction: The rapid development of electric vehicle technology in the field of renewable energy has brought significant challenges to wireless charging systems. The efficiency of these systems is crucial for improving availability and sustainability. The main focus of the research is to develop an intelligent charging strategy that utilizes fuzzy logic to optimize the efficiency of wireless charging systems for electric vehicles.Method: Introduce a model that combines fuzzy logic algorithm with automatic control system to improve the wireless charging process of electric vehicles. The model adopts dynamic tracking and adaptive control methods by analyzing the characteristics of static wireless charging systems. Utilizing primary phase shift control and secondary controllable rectifier regulation, combined with optimized fuzzy control algorithm.Result and discussion: The experimental results show that when the secondary coil is stable, the model maintains a stable duty cycle of about 75.6% and a stable current of 5A. It was observed that when the mutual inductance values were set to 10, 15, and 20 uH, the efficiency of the primary coil before applying control decreased with increasing resistance.Conclusion: The proposed system has shown great potential for application in real-world electric vehicle charging systems, demonstrating good applicability and feasibility in controlling the charging process and tracking the optimal efficiency point. The integration of fuzzy logic enhances the system’s ability to adapt to different operating conditions, which may lead to wider implementation and improved operational efficiency.

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A novel stochastic maximum power point tracking control for off-grid standalone photovoltaic systems with unpredictable load demand

Cited by 11 publications

References 50 publications

Observer-Based Control for a New Stochastic Maximum Power Point Tracking for Photovoltaic Systems With Networked Control System

Observer-Based Control for a New Stochastic Maximum Power Point Tracking for Photovoltaic Systems With Networked Control System

Wireless Diagnosis and Control of DC–DC Converter for Off-Grid Photovoltaic Systems

Optimal efficiency point membership incorporating fuzzy logic and automatic control of various charging stages for electric vehicles

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