Description:FIELD OF THE INVENTION

Our Invention is related to a development Method for Evaluating the Reliability-Oriented Performance of PV Inverters

BACKGROUND OF THE INVENTION

However, the ability to harvest solar energy from both the rare and front surfaces of the panels can increase the load on the inverters, which affects the reliability performance. Nevertheless, inverter is reported as the critical component in the PV system. The performance of a PV inverter based on geographical locations and environmental factors. The lifetime of a PV inverter with different orientation and tilt angles of panels. In addition, the degradation rate of these panels is taken into account. The influence of mission profile on the lifetime of a PV inverter. The reliability oriented accelerated testing of dc link capacitor of PV inverter. A method for improving the reliability of PV inverters by implementing a variable voltage distribution network under uncertain conditions. As the PV inverter reliability is the major concern in this invention is the reliability oriented performance evaluation of PV inverter with bifacial panels is proposed. A test case of 3-kW PV system is considered with yearly mission profile data at Hyderabad, India. This evaluation is carried out under various albedos. The albedo significantly impacts the lifetime of PV inverter and hence these factors should be taken into account when designing a PV inverter for bifacial panels.

These methods contains professionally and precisely energy demand in the world increases the need for electricity based on this different energy sources need to be taken for consideration.

OBJECTIVES OF THE INVENTION

The objective of the invention is to develop PV inverter for bifacial solar inverter with different albedos based on the energy requirements in the day to day energy demand.
The crisis in energy demand the adoption of a technology in the power generation. The business of energy companies and giving quality and uninterruptable supply to the consumers.
By using the technology of bifacial solar panel with different albedos will increase the power generation but the major problem is inverter. Here the inverter is invented by considering different parameters into consideration based on the power increase with bifacial solar panels
The main aim of this inverter design is to reduce the cost of electricity and provide uninterruptable supply during high demand days also.
Inverter stability must be considered at all times to exist the availability, access, and utilization of the power which highlights the importance to reduce the possibility of power shortages.
Real time implementation of this project is not only makes a impact on power sector, as well industries and reduces the cost of energy per unit.

SUMMARY OF THE INVENTION

The reliability of PV inverter is obtained by calculating the reliability of IGBT at System Level (Ls). Initially Component Level (Lc) reliability for IGBT (For Single IGBT) is evaluated and System Level (Ls) reliability is obtained by combining all IGBTs Component Level (Lc) reliability using series reliability block diagram. The reliability oriented performance analysis of PV inverter involves several steps. The flow chart is presented in Fig. 2.
Mission Profile Logging
Yearly Solar Irradiance (Is) and Ambient Temperature (Ta) are logged as Mission Profile (MP) at Hyderabad, India between August 2018 to September 2019 [14].
Junction Temperature Estimation
Junction Temperature (Jt) for the yearly MP is estimated using foster electro thermal model [15].
RF Counting
Rainflow Counting is implemented to analyse the variation of Jt [16].
MCS and Reliability Evaluation
The lifetime (Lf) is calculated using the Bayerer’s lifetime equation [17] show in Eq. 1
L_f= 1/(∑▒〖(〖No.of cycles (n〗_i))/(A(〖∆T〗_j )^(β_1 ).e^(β_2/((T_j+ 273) )).〖t_on〗^(β_3 ).I^(β_4 ).V^(β_5 ).D^(β_6 ) ) 〗)
Monte Carlo Simulation (MCS) generates 10000 samples with 5% variation. Lf at each sample is calculated using Eq. 1 and fitted in Weibull distribution. Reliability Evaluation at component level and system level are calculated using the Eq. 2 and Eq. 3 respectively [18].
R_i (t)= e^(〖-(t/∝)〗^γ )
Where
R_i (t)= Reliability of individual component
∝ =Scale Parameter
γ=Shaper Parameter

R_total (t)= ∏_(i=1)^n▒〖R_i (t)〗
Test Case
In this invention a test case of 3-kW PV system is considered as shown in Fig. 3. An yearly MP from August 2018 to September 2019 is considered at Hyderabad, India. The system specifications are tabulated in Table 1.
Table 1 System Specifications
Item Specifications
PV Panel BP(365)
IGBT IGW30N60H3
Grid Voltage 230 Volts
Grid Frequency 50 Hz

In this invention performance of monofacial and bifacial panels are considered for comparison. The bifacial panels are modelled under the various albedos [19] keeping the module height from ground at 1meter as shown in Fig. 5.

BRIEF DESCRIPTION OF THE DIAGRAM

Fig.1 Bifacial Technology.
Fig. 2 Flow Chart for PV Inverter Reliability Evaluation
Fig. 3. Test Case
Fig. 4 Monthly MP for One Year
Fig. 5 Bifacial Gain at Various Albedos
Fig. 6 Jt for Monofaical Panel
Fig. 7 RF for Monofacial Panel
Fig. 8 CL Reliability for Monofacial Panel
Fig. 9 SL Reliability for Monofacial Panel
Fig. 10 Jt for Bifaical Panel
Fig. 11 RF for Bifacial Panel
Fig. 12 MCS for Monofacial Panel
Fig. 13 CL Reliability for Bifacial Panel
Fig. 14 SL Reliability for Bifacial Panel
Fig. 15 Comparison Analysis

INVENTION DISCLOUSERS
In this invention reliability oriented performance evaluation of PV inverter with bifacial panels is proposed. A test case of 3-kW PV system is considered with yearly mission profile data at Hyderabad, India. The following cases are evaluated.
PV Inverter With Monofacial Panels
PV Inverter With Bifacial Panels
PV Inverter With Monofacial Panels
In this case conventional monofacial panel is considered for the assessment. Yearly MP is taken between August 2018 to September 2019 as shown in Fig. 4.
Junction Temperature Estimation
The yearly MP is translated to Jt using foster electro thermal model as shown in Fig. 6. The Jt follows the irregular profile, hence counting algorithm is needed to analyse.
RF Counting
To extract the thermal profile from the Jt, rainflow counting algorithm is implemented. The thermal profiles such as number for cycles, cycle average, cycle range are extracted as shown in Fig. 7.
MCS and Reliability Evaluation
Monte Carlo Simulation (MCS) generates 10000 samples with 5% variation. Lf at each sample is calculated using Eq. 1 and fitted in Weibull distribution as shown in Fig. 8. Reliability Evaluation at component level and system level are calculated using the Eq. 2 and Eq. 3 as shown in Fig. 9 and Fig. 10 respectively.
In this case B10 lifetime for PV inverter at CL is recorded as 33 years and for SL is recorded as 24 years.
PV Inverter With Bifacial Panels
In this case conventional bifacial panel is considered for the assessment under various albedos as shown in Fig. 5. Yearly MP is taken between August 2018 to September 2019 as shown in Fig. 4.
Junction Temperature Estimation
The yearly MP is translated to Jt for various albedos using foster electro thermal model as shown in Fig. 10. The Jt follows the irregular profile, hence counting algorithm is needed to analyse.
RF Counting
To extract the thermal profile from the Jt for various albedos, rainflow counting algorithm is implemented. The thermal profiles such as number for cycles, cycle average, cycle range are extracted as shown in Fig. 11.
MCS and Reliability Evaluation
Monte Carlo Simulation (MCS) generates 10000 samples with 5% variation for various albedos. Lf at each sample is calculated using Eq. 1 and fitted in Weibull distribution as shown in Fig. 12. Reliability Evaluation at component level and system level are calculated using the Eq. 2 and Eq. 3 as shown in Fig. 13 and Fig. 14 respectively.
In this case B10 lifetime for PV inverter at CL is recorded as follows under various Albedos
Soil Meadows (Albedo 15 %) = 22 Years
Dirt, Gravel, Concrete (Albedo 30 %) = 16 Years
Sand (Albedo 50 %) = 8 Years
Snow (Albedo 70 %) = 5.8 Years
White Membrane (Albedo 85 %) = 6 Years

Similarly B10 lifetime for PV inverter at SL is recorded as follows under various Albedos
Soil Meadows (Albedo 15 %) = 16 Years
Dirt, Gravel, Concrete (Albedo 30 %) = 12 Years
Sand (Albedo 50 %) = 11 Years
Snow (Albedo 70 %) = 8 Years
White Membrane (Albedo 85 %) = 5
Comparison Analysis
In this invention PV inverter reliability performance is evaluated for Monofacial and Bifacial (Considering Albedos) panels at SL and CL as shown in Fig. 15. Albedo significantly impact the reliability performance of PV inverter, as the albedo increases the reliability of PV inverter decreases. Hence impact of albedo needs to be consider during the design of Bifacial system.

WE CLAIMS

Claim 1: A method for assessing the reliability-oriented performance of photovoltaic (PV) inverters in bifacial panel PV systems, comprising:
a. Capturing solar energy from both front and rear sides of bifacial panels;
b. Determining the impact of energy harvesting from the front and rear surfaces of the panels on the load of the PV inverters;
c. Evaluating the reliability performance of the PV inverters.
Claim 2: The method of claim 1, wherein said method is applied to a PV system with a power capacity of 3-kW.
Claim 3: The method of claim 1, further comprising the step of utilizing yearly mission profile data specific to a geographical location, wherein said geographical location is Hyderabad, India.
Claim 4: The method of claim 1, further comprising the step of conducting reliability-oriented performance evaluation under multiple albedo conditions, wherein each albedo condition corresponds to a distinct level of surface reflectivity.
Claim 5: A method for designing PV inverters tailored for bifacial panel PV systems, comprising:
a. Incorporating albedo impact analysis into the PV inverter design process;
b. Determining design parameters and specifications based on the results of reliability-oriented performance evaluation.
Claim 6: The method of claim 5, wherein the albedo impact analysis considers the effect of albedo on the operational lifetime of PV inverters.

References:
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, Claims:Claim 1: A method for assessing the reliability-oriented performance of photovoltaic (PV) inverters in bifacial panel PV systems, comprising:
a. Capturing solar energy from both front and rear sides of bifacial panels;
b. Determining the impact of energy harvesting from the front and rear surfaces of the panels on the load of the PV inverters;
c. Evaluating the reliability performance of the PV inverters.
Claim 2: The method of claim 1, wherein said method is applied to a PV system with a power capacity of 3-kW.
Claim 3: The method of claim 1, further comprising the step of utilizing yearly mission profile data specific to a geographical location, wherein said geographical location is Hyderabad, India.
Claim 4: The method of claim 1, further comprising the step of conducting reliability-oriented performance evaluation under multiple albedo conditions, wherein each albedo condition corresponds to a distinct level of surface reflectivity.
Claim 5: A method for designing PV inverters tailored for bifacial panel PV systems, comprising:
a. Incorporating albedo impact analysis into the PV inverter design process;
b. Determining design parameters and specifications based on the results of reliability-oriented performance evaluation.
Claim 6: The method of claim 5, wherein the albedo impact analysis considers the effect of albedo on the operational lifetime of PV inverters.