Faults in any components of PV system shall lead to performance degradation and if prolonged, it can leads to fire hazard. This paper presents an approach of early fault detection via acquired historical data sets of gridconnected PV (GCPV) systems. The approach is a developed algorithm comprises of failure detection on AC power by using Acceptance Ratio (AR) determination. Specifically, the implemented failure detection stage was based on the algorithm that detected differences between the actual and predicted AC power of PV system. Furthermore, the identified alarm of system failure was a decision stage which performed a process based on developed logic and decision trees. The results obtained by comparing two types of GCPV system (polycrystalline and monocrystalline silicon PV system), showed that the developed algorithm could perceive the early faults upon their occurrence. Finally, when applying AR to the PV systems, the faulty PV system demonstrated 93.38% of AR below 0.9, while the fault free PV system showed only 31.4% of AR below 0.9.

<p>This paper presents six months evaluation in determining Standard Reference Environment (SRE) for Photovoltaic (PV) Nominal Operating Cell Temperature (NOCT) testing of IEC61215 and IEC61646 that suits Malaysian climate. The SRE is established based on the median environmental conditions in Malaysia when solar PV is producing power. The site of the study is located at the Energy and Environment Field Lab, Universiti Teknologi MARA (UiTM) Shah Alam(3.066239ºN, 101.491685ºE). Three types of PV module technologies involved are monocrystalline, polycrystalline and copper indium diselenide (CIS) thin film. The experimental setup is a test bed that meets the IEC61215, IEC61646 and IEC61724 requirements. The measurements of        module temperature (MT) and open circuit voltage (V_OC) are taken simultaneously for the three PV module technologies together with other ambient parameters of solar irradiance(SI), ambient temperature(AT), relative humidity(RH), wind speed (Ws) and wind direction(Wd). The data set is taken for a six months period from February 2017 to July 2017. Based on the results obtained, a new proposed SRE of NOCT testing for IEC61215 and IEC61646 has been established to suit Malaysian climate. The SI and AT values for the SRE are 300W/m² and 31°C respectively.</p>

This paper presents the Acceptance Ratio (AR) analysis for three different grid-connected photovoltaic (GCPV) systems working under the Malaysia tropical climate. AR is a ratio between actual AC power, PAC_actual, and predicted AC power, PAC_predicted. According to Malaysian Standard MS2692:2020, the AR value must ≥ 0.9 to classify as accepted in testing and commissioning test. In contrast, a rate < 0.9 indicates a non-accepted GCPV system. Historical data of the AC power output, solar irradiance, and module temperature from January 1 to December 31, 2019, were used for the analysis. The analysis procedure was carried out using Matlab and Microsoft Excel software. The analysis covers the AC power analysis and the AR analysis based on the threshold of 0.9. The plotted monthly AC power graph shows that all systems have lower than 15 % differences between actual and predicted AC power. On the AR analysis, System 1 was found to show early fault indicator with a monthly cumulative percentage of AR < 0.9 ranges from 34 % to 71 %, meanwhile System 2 and System 3 have a lower cumulative percentage of AR < 0.9 ranges from 5 % to 19 %. This result suggested that only System 2 and 3 are fault-free GCPV systems and working in good condition. The outcome of this study has succeeded in providing preliminary AR analysis results for three GCPV systems located in Malaysia. This study would help to evaluate AR threshold reliability to indicate an early fault of a GCPV system.

No abstract

Data visualization is a technique of creating visual image big data. The visualization reveals hiddenprocess is known as visual analytics.that is congested and hardly reveal the data patterns.flexibility to users to control over the others. However, most of the filtering is has designed a structured process for formulating graph since it is a widely used technique for visualizing m flexible visual filtering presentations for parallel coordinate graph have finding support a wide range of visual analytics needs in parallel coordinated graph.