Review of long-term fault detection approaches in solar thermal systems

Keizer, A.C. de; Vajen, Klaus; Jordan, Ulrike

doi:10.1016/j.solener.2011.03.025

Cited by 10 publications

(4 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Theorem 1: Consider the linear discrete time-varying system with missing measurements described by (1). For a given…”

Section: Resultsmentioning

confidence: 99%

“…Therefore, the past few years have witnessed constant research interests on various fault detection and diagnosis and fault-tolerant control problems, and there has been an abundant of research results available in the literature, see e.g. [1], [2], [5], [6], [8], [10], [11], [12]. Fault estimation has long been one of the fundamental problems in the fault detection systems.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

H<inf>∞</inf> fault estimation for uncertain linear discrete time-varying systems with missing measurements

Zhang

Shen

Shu

2014

Proceeding of the 11th World Congress on Intelligent Control and Automation

View full text Add to dashboard Cite

This paper is concerned with the H∞ fault estimation problem for a class of uncertain linear discrete time-varying systems with missing measurements over a finite time-horizon. In order to characterise the random nature resulting from the missing measurements, the conventional H∞ performance index is first modified in the stochastic sense. Then, by introducing an auxiliary system, the parameter uncertainties are eliminated formally and the modified H∞ performance index is described by a certain indefinite quadratic form. Subsequently, the desired fault estimator is designed by equivalently solving a minimum problem of the indefinite quadratic form. Finally, an illustrative numerical example is given to show the effectiveness of the proposed fault estimation scheme.Index Terms-H∞ fault estimation; indefinite quadratic form; missing measurements; robust fault estimation; uncertain systems.

show abstract

“…Theorem 1: Consider the linear discrete time-varying system with missing measurements described by (1). For a given…”

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

H<inf>∞</inf> fault estimation for uncertain linear discrete time-varying systems with missing measurements

Zhang

Shen

Shu

2014

Proceeding of the 11th World Congress on Intelligent Control and Automation

View full text Add to dashboard Cite

show abstract

“…After sensing a particular parameter, the diagnosing sensor is taken into consideration for continuing the simulation process. Furthermore, the fault diagnosis system must be equipped with telemonitoring panels for the successful implementation of a graphic user interface [19]. Another paper analyzed the characteristics of the terminals used in faulty PV strings and arrays.…”

Section: Online/remote Supervision Of Pv Panelmentioning

confidence: 99%

An Effective Evaluation on Fault Detection in Solar Panels

et al. 2021

View full text Add to dashboard Cite

The world’s energy consumption is outpacing supply due to population growth and technological advancements. For future energy demands, it is critical to progress toward a dependable, cost-effective, and sustainable renewable energy source. Solar energy, along with all other alternative energy sources, is a potential renewable resource to manage these enduring challenges in the energy crisis. Solar power generation is expanding globally as a result of growing energy demands and depleting fossil fuel reserves, which are presently the primary sources of power generation. In the realm of solar power generation, photovoltaic (PV) panels are used to convert solar radiation into energy. They are subjected to the constantly changing state of the environment, resulting in a wide range of defects. These defects should be discovered and remedied as soon as possible so that PV panels efficiency, endurance, and durability are not compromised. This paper focuses on five aspects, namely, (i) the various possible faults that occur in PV panels, (ii) the online/remote supervision of PV panels, (iii) the role of machine learning techniques in the fault diagnosis of PV panels, (iv) the various sensors used for different fault detections in PV panels, and (v) the benefits of fault identification in PV panels. Based on the investigated studies, recommendations for future research directions are suggested.

show abstract

“…So, the weather data is grouped into four categories: clear sky, hazy day, hazy and cloudy, and cloudy day where the diffusive radiation shares are ≤ 25%, between 25-50%, between 50-75%, and ≥ 75% respectively [12]. Nevertheless, by analysing many existing facilities, it is shown that many of them have a dimensioning defect or are operated incorrectly [13]. This cannot just cause economic loss but also less satisfactory results in the overall gain [14].…”

Section: Introductionmentioning

confidence: 99%

Linear Model of DHW System Using Response Surface Method Approach

2022

Teh. vjesn.

View full text Add to dashboard Cite

Using alternative and clean energy resources is considered the most effective method to deal with the environment and energy crises nowadays. In this study a comparative analysis of FPC data for DHW are theoretically and experimentally evaluated to optimise the design parameters. A forced circulation solar heating system using flat-plate collector, is modelled using T*SOL as a new approach, for hot water requirements of a laboratory unit at Szent Istvan University, in Gödöllő, Hungary. The modelling shows 69% solar fraction and 510 kWh annual solar gain. Furthermore, the comparison study was based on these two factors, and the two results matched with 93.12% accuracy. After the modelling, practically, the exergy analysis was conducted to determine and highlight the losses of the system. Since Hungary is considered a cold climate country, it was found that the thermal and optical losses from the collector and the piping system were tremendous. Then all the necessary design parameters were studied to achieve the optimal working points using non-linear correlation response surface method (RSM, which has never been used as an analysis tool in the solar field) at two perspectives (solar fraction and annual yield) for seven factors using R script. The factors were collector surface area, inclination angle, glycol-water ratio, tank capacity, boiler capacity, desired hot water temperature, and volume flow-rate. We identified the most influential single factors using ParetoPlot and each two-factorsꞌ interaction using contour plots. The most influential factors on the solar yield are solar collector surface area, tank capacity, desired hot water temperature and volume flow rate by magnitude effects of +129.7, +125.3, +50.9 and +17.2 kWh per annum, respectively.

show abstract

Review of long-term fault detection approaches in solar thermal systems

Cited by 10 publications

References 5 publications

H<inf>∞</inf> fault estimation for uncertain linear discrete time-varying systems with missing measurements

H<inf>∞</inf> fault estimation for uncertain linear discrete time-varying systems with missing measurements

An Effective Evaluation on Fault Detection in Solar Panels

Linear Model of DHW System Using Response Surface Method Approach

Contact Info

Product

Resources

About

Review of long-term fault detection approaches in solar thermal systems

Cited by 10 publications

References 5 publications

H<inf>&#x221E;</inf> fault estimation for uncertain linear discrete time-varying systems with missing measurements

H<inf>&#x221E;</inf> fault estimation for uncertain linear discrete time-varying systems with missing measurements

An Effective Evaluation on Fault Detection in Solar Panels

Linear Model of DHW System Using Response Surface Method Approach

Contact Info

Product

Resources

About

H<inf>∞</inf> fault estimation for uncertain linear discrete time-varying systems with missing measurements

H<inf>∞</inf> fault estimation for uncertain linear discrete time-varying systems with missing measurements