Signal Processing for Solar Array Monitoring, Fault Detection, and Optimization

Banavar, Mahesh K.; Braun, Henry; Buddha, S. T.; Krishnan, Venkatachalam; Spanias, Andreas; Takada, Shinichi; Takehara, Toru; Tepedelenlioğlu, Cihan; Yeider, Ted

doi:10.2200/s00425ed1v01y201206pel004

Cited by 19 publications

(5 citation statements)

References 46 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Imaging methods are currently expensive and time consuming, whereas electrical characterization is cheaper and more flexible [24]. The latter methods also can be further split into several branches: signal processing and statistical methods (e.g., [8,25,26]), i − v curve characteristics analysis (e.g., [27,28]), power losses analysis or efficiency analysis (e.g., [17,29,30]), current and/or voltage measurements (e.g., [31,32]), and artificial intelligent methods (e.g., [9,33,34]). The diagnosis algorithm implemented in this work is based on the IF-THEN rules presented by the authors in [35] and follows the diagnosis branch based on current-voltage measurements.…”

Section: Automated Fault Management System Approachmentioning

confidence: 99%

Automated Fault Management System in a Photovoltaic Array: A Reconfiguration-Based Approach

Murillo-Soto

Meza

2021

Energies

View full text Add to dashboard Cite

This work proposes an automated reconfiguration system to manage two types of faults in any position inside the solar arrays. The faults studied are the short-circuit to ground and the open wires in the string. These faults were selected because they severely affect power production. By identifying the affected panels and isolating the faulty one, it is possible to recover part of the power loss. Among other types of faults that the system can detect and locate are: diode short-circuit, internal open-circuit, and the degradation of the internal parasitic serial resistance. The reconfiguration system can detect, locate the above faults, and switch the distributed commutators to recover most of the power loss. Moreover, the system can return automatically to the previous state when the fault has been repaired. A SIMULINK model has been built to prove this automatic system, and a simulated numerical experiment has been executed to test the system response to the faults mentioned. The results show that the recovery of power is more than 90%, and the diagnosis accuracy and sensitivity are both 100% for this numerical experiment.

show abstract

Section: Automated Fault Management System Approachmentioning

confidence: 99%

Automated Fault Management System in a Photovoltaic Array: A Reconfiguration-Based Approach

Murillo-Soto

Meza

2021

Energies

View full text Add to dashboard Cite

show abstract

“…Every type of PV module has a variable specification caused by processing characteristics. Even the response to the variation of the solar irradiation may be different, since it depends on the manufacturer characteristics and material like the reflection of the protection glass, heat dissipation of the panel, rated voltage and current [28]. For these reasons, it is recommended to use the same type of the PV panel in the solar array.…”

Section: Mismatching Effectsmentioning

confidence: 99%

Detection and control of power loss due to soiling and faults in photovoltaic solar farms via wireless sensor network

Abid

Obed

Al-Naima

2018

IJET

View full text Add to dashboard Cite

Solar photovoltaic (PV) farm output power is highly related to the panel conditions. Soiling causes faults in the PV panels leading to a dras-tic reduction in the system efficiency. In vast solar PV farms, the detection of faults in an individual PV panel is a difficult task since it is usually done manually. In this research, a new design is proposed to detect the production of individual PV panel automatically and periodically to evaluate the condition of each panel in the farm no matter how it is connected in the array. The proposed design allows the user to measure the open circuit voltage (VOC), the short circuit current (ISC) and the delivered power for each PV panel in the farm. It is also capable of controlling each panel to work at the maximum power point using a built in Maximum Power Point Tracking (MPPT) sub-circuit on each solar panel. The presented system depicts a complete wireless sensor network, which does not need any extra wiring and is character-ized by being of low cost, reliable and efficient.

show abstract

“…PV inverter uptime [5], (b) improvement of output power with consistent energy flows to the utility grid and (c) minimization of mismatch losses. Studies reported in [6], [7], [8], and [9] highlight the importance of reconfiguration to tackle mismatch losses.…”

Section: Introductionmentioning

confidence: 99%

“…Conventionally, PV arrays rely on fixed connections or topologies to provide power to the grid. However under continuous, real-time variations of shading patterns, alternate topologies such as series-parallel (SP), bridge-link (BL), honeycomb (HC), or total-cross-tied (TCT) can lead to improved power production [5], [10]. Consequently, there has been several research efforts to address reconfiguration in PV arrays.…”

Section: Introductionmentioning

confidence: 99%

Optimizing Solar Power Using Array Topology Reconfiguration With Regularized Deep Neural Networks

et al. 2023

Self Cite

View full text Add to dashboard Cite

Reconfiguring photovoltaic (PV) array connections among different topologies such as seriesparallel, bridge-link, honeycomb, or total-cross-tied is a popular strategy to mitigate impediments in power production caused by partial shading. Conventional approaches rely on either by-passing or replacing shaded modules with auxiliary panels through complex control mechanisms, optimization strategies, or simulator driven approaches to obtain the best topology. However, these solutions are not scalable and incur significant installation costs and computational overhead, motivating the need to develop 'smart' methods for topology reconfiguration. To this end, we propose a regularized neural network based algorithm that leverages panel-level sensor data to reconfigure the array to the topology that maximizes power output under arbitrary shading conditions. Based on our simulations that include wiring losses in different configurations, we observe power improvement of up to 11% through reconfiguration. The proposed algorithm can be easily integrated in any cyber-physical PV system with reconfiguration capabilities and is scalable.

show abstract

Signal Processing for Solar Array Monitoring, Fault Detection, and Optimization

Cited by 19 publications

References 46 publications

Automated Fault Management System in a Photovoltaic Array: A Reconfiguration-Based Approach

Automated Fault Management System in a Photovoltaic Array: A Reconfiguration-Based Approach

Detection and control of power loss due to soiling and faults in photovoltaic solar farms via wireless sensor network

Optimizing Solar Power Using Array Topology Reconfiguration With Regularized Deep Neural Networks

Contact Info

Product

Resources

About