Intelligent Cloud-Based Monitoring and Control Digital Twin for Photovoltaic Power Plants

Today, climate change combined with the energy crisis is accelerating the worldwide adoption of renewable energies through incentive policies. However, due to their intermittent and unpredictable behavior, renewable energy sources need EMS (energy management systems) as well as storage infrastructure. In addition, their complexity requires the implementation of software and hardware means for data acquisition and optimization. The technologies used in these systems are constantly evolving but their current maturity level already makes it possible to design innovative approaches and tools for the operation of renewable energy systems. This work focuses on the use of Internet of Things (IoT) and Digital Twin (DT) technologies for standalone photovoltaic systems. Based on Energetic Macroscopic Representation (EMR) formalism and the Digital Twin (DT) paradigm, we propose a framework to improve energy management in real time. In this article, the digital twin is defined as the combination of the physical system and its digital model, communicating data bi-directionally. Additionally, the digital replica and IoT devices are coupled via MATLAB Simulink as a unified software environment. Experimental tests are carried out to validate the efficiency of the digital twin developed for an autonomous photovoltaic system demonstrator.

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“…However, they use a digital shadow instead of digital twin. We find the same confusion in the articles [ 29 , 30 , 31 , 32 , 33 ].…”

Section: Literature Reviewmentioning

confidence: 61%

Unified Environment for Real Time Control of Hybrid Energy System Using Digital Twin and IoT Approach

Chalal

Saadane

Rachid

2023

Sensors

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“…From the obtained EL images (see Figure 11), broken cells and cracks were detected for two of the test PV arrays (BP Solar and SolarWorld), justifying their low performance and the detection of change points within their time series. The FBP method, which demonstrated nonlinear PLR estimation and fault categor zation capabilities in PV systems [35,36], was then validated against the created Sanyo P performance time series with data anomalies. The results are shown in Figure 12, verifyin the FBP model's capability for capturing trend changes, even in the presence of global/lo cal outliers in the time series.…”

Section: Indoor Testing Results and Validationmentioning

confidence: 99%

“…FBP is thus a robust mod for reliability studies and the initial results showed that its performance is not affected b outliers. Though further validation is needed to confirm the model's accuracy in the pre The FBP method, which demonstrated nonlinear PLR estimation and fault categorization capabilities in PV systems [35,36], was then validated against the created Sanyo PV performance time series with data anomalies. The results are shown in Figure 12, verifying the FBP model's capability for capturing trend changes, even in the presence of global/local outliers in the time series.…”

Section: Indoor Testing Results and Validationmentioning

confidence: 99%

Estimating the Performance Loss Rate of Photovoltaic Systems Using Time Series Change Point Analysis

et al. 2023

Self Cite

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The accurate quantification of the performance loss rate of photovoltaic systems is critical for project economics. Following the current research activities in the photovoltaic performance and reliability field, this work presents a comparative assessment between common change point methods for performance loss rate estimation of fielded photovoltaic installations. An extensive testing campaign was thus performed to evaluate time series analysis approaches for performance loss rate evaluation of photovoltaic systems. Historical electrical data from eleven photovoltaic systems installed in Nicosia, Cyprus, and the locations’ meteorological measurements over a period of 8 years were used for this investigation. The application of change point detection algorithms on the constructed monthly photovoltaic performance ratio series revealed that the obtained trend might not always be linear. Specifically, thin film photovoltaic systems showed nonlinear behavior, while nonlinearities were also detected for some crystalline silicon photovoltaic systems. When applying several change point techniques, different numbers and locations of changes were detected, resulting in different performance loss rate values (varying by up to 0.85%/year even for the same number of change points). The results highlighted the importance of the application of nonlinear techniques and the need to extract a robust nonlinear model for detecting significant changes in time series data and estimating accurately the performance loss rate of photovoltaic installations.

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“…The operation and maintenance module (OM) [27] is designed for the plant operations to actually meet the expected target performances, preventing faults and minimizing operation downtimes. It sets the plant operational parameters, such as the PV array configuration, the inverter settings, and the actuation of any other automatic operation that can be performed on the plant.…”

Section: The General Structure Of a Pv Iot-scadamentioning

confidence: 99%

A Study on an IoT-Based SCADA System for Photovoltaic Utility Plants

Ferlito,

Ippolito,

Santagata

et al. 2024

Electronics

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Large-scale photovoltaic (PV) electricity production plants rely on reliable operation and maintenance (O&M) systems, often operated by means of supervisory control and data acquisition (SCADA) platforms aimed at limiting, as much as possible, the intrinsic volatility of this energy resource. The current trend is to develop SCADAs that achieve the finest possible control of the system components to efficiently and effectively cope with possible energy delivery problems. In this study, we investigated an innovative design of an IoT-based SCADA specifically tailored for large PV systems in which data transmission overheads are reduced by adopting lightweight protocols, and reliable data storage is achieved by means of hybrid solutions that allow the storage of historical data, enabling accurate performance analysis and predictive maintenance protocols. The proposed solution relies on an architecture where independent functional microservices handle specific tasks, ensuring scalability and fault tolerance. The technical approaches for IoT-SCADA connectivity are herein described in detail, comparing different possible technical choices. The proposed IoT-based SCADA is based on edge computing for latency reduction and to enhance real-time decision making, enabling scalability, and centralized management while leveraging cloud services. The resulting hybrid solutions that combine edge and cloud resources offer a balance between responsiveness and scalability. Finally, in the study, a blockchain solution was taken into account to certify energy data, ensuring traceability, security, and reliability in commercial transactions.

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Intelligent Cloud-Based Monitoring and Control Digital Twin for Photovoltaic Power Plants

Cited by 15 publications

References 17 publications

Unified Environment for Real Time Control of Hybrid Energy System Using Digital Twin and IoT Approach

Unified Environment for Real Time Control of Hybrid Energy System Using Digital Twin and IoT Approach

Estimating the Performance Loss Rate of Photovoltaic Systems Using Time Series Change Point Analysis

A Study on an IoT-Based SCADA System for Photovoltaic Utility Plants

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