Fuzzy Decision-Making Model for Solar Photovoltaic Panel Evaluation
Abstract
:1. Introduction
- Monocrystalline silicon—are made of melted silica sand with the addition of boron; cells produced on their basis are characterized by the highest efficiency, but also the highest price;
- Polycrystalline silicon—they are made of ground silicon, which is melted and cast in the form of a block composed of non-homogenous crystals with a diameter of several millimeters to several centimeters; the distances between the crystals weaken the efficiency of the cell compared to monocrystalline cells;
- Cadmium telluride—they are created in the process of applying a thin layer of cadmium telluride to glass or other substrate; the entire photovoltaic module is usually made of one cell;
- Copper indium gallium selenide—they can absorb more solar radiation than other cells, which is why they work well in poorer insolation;
- Amorphous silicon—they are created in the process of applying a thin layer of allotropic silicon to glass or another substrate; due to the small amount of semiconductor used and low energy consumption in the production process, their production is quick and cheap, but their efficiency is worse than other types of cells.
2. Review of the Literature
3. Materials and Methods
3.1. Preliminaries
3.2. Uncertain Criteria and a Fuzzy Model for Assessing PV Panels
4. Results
5. Discussion
6. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Aim of the Study | Subject of the Study | Location | MCDM Methods | No of Criteria/Sub-criteria | Ref. |
---|---|---|---|---|---|
Evaluation of five renewable power generation sources and choose the most favorable technology | Renewable energy sources | Saudi Arabia | AHP | 4/14 | [28] |
Identification of the best renewable resource for electricity generation | Renewable resources for electricity generation | Malaysia | AHP | 4/12 | [29] |
Selection of the best alternative renewable energy sources for electricity production | Residential building | Oran, Algeria | Delphi, fuzzy AHP, fuzzy PROMETHEE | 7/15 | [27] |
Establishing a decision model for improving the performance of solar PV farms | Solar PV plants sites | China | DEMATEL, DANP | 10 | [34] |
Development of the wind farm and solar PV farm | Wind farm and solar PV farm | South Central England | GIS, AHP | 3/5 | [33] |
Defining and classifying particular criteria considered for solar PV farm siting | Solar PV power plant | Zastavna district, Ukraine | AHP | 13 | [32] |
Evaluation of the region’s priority for the installation of solar PV projects | Solar PV plants sites | Iran | SWARA, WASPAS | 4/14 | [36] |
Determination of the best location for a solar thermoelectric power plant | Location of solar thermoelectric power plants | Region of Murcia, Spain | Fuzzy AHP, Fuzzy TOPSIS | 4/10 | [35] |
Proposing a decision support system to avoid flooding when choosing a location for a solar power plant | Sites for a solar power plant | Thailand | Fuzzy AHP, TOPSIS | 5/19 | [30] |
Identification of optimal locations for solar PV farms | Areas for the construction of solar PV farms | Fars province, Iran | Fuzzy AHP, fuzzy DS | 11 | [31] |
Choosing a solar PV panel supplier from a variety of options that best suits the needs of manufacturing companies | Solar PV energy systems in manufacturing companies | Mexico | Fuzzy TOPSIS | 4/37 | [37] |
Selection of the PV technology | Five PV technologies | - | LFPP, AHP | 4/13 | [17] |
Selection of the best solar PV panel for the photovoltaic system design | Solar PV panels up to 200W | - | AHP | 5/26 | [38] |
Finding the most rational solar PV panel from a given set of alternatives | Public available solar PV panels | - | COMET, TOPSIS | 6 | [39] |
Selection of the best technology for solar PV panels | First, second, and third generations of solar PV panels | Iran | MULTIMOOSRAL, BWM | 5/20 | [18] |
Proposing a decision support system for the assessment of solar PV panels used in photovoltaic installations | Solar PV panels | - | COMET, SPOTIS | 6 | [40] |
Criterion | Reference |
---|---|
Maximum power (Pmax) [Wp]/PTC power rating [W]/STC power per unit of area [W/m2]/peak power [W]/peak power per m2 [W/m2] | [18,38,39,40] |
Panel efficiency [%]/peak efficiency [%]/module efficiency [%] | [18,38,39,40] |
Open-circuit voltage (VOC) (STC) [V] | [18,38,39,40] |
Short-circuit current (ISC) (STC) [A] | [18,38,39,40] |
Panel cost [USD]/cost per watt [USD]/price [USD]/cost [USD]/cost per m2 [USD/m2] | [18,38,39,40] |
Weight [kg]/weight per m2 [kg/m2] | [18,38,40] |
L × W × H [cm3]/length × width × depth [mm]/area [m2] | [18,38,39] |
Product warranty [years]/service support | [18,38] |
Manufacturer | Astronergy | JA Solar | Jinko Solar | Kensol | Meyer Burger | Phono Solar | REC | Risen | Selfa | Trina Solar |
---|---|---|---|---|---|---|---|---|---|---|
Country of Manufacture | China | China | China | Poland/China | Germany | China | Norway/Singapore | Poland/China | Poland | China |
Model | CHSM54M-HC (182) | JAM60S20 390/MR | JKM430N-54HL4 | KS395M-SH | White | PS420M4-22/WH | REC380AA | RSM40-8-410M | SV108M.3-410 | TSM-DE09.08 405W |
Power—NOCT (PNOCT) [W] | 306.4 | 295 | 323 | 297 | 302 | 310 | 289 | 310.7 | 309.6 | 306 |
Power—STC (Pmax) [W] | 410 | 390 | 430 | 395 | 400 | 420 | 380 | 410 | 410 | 405 |
Positive power tolerance (PT) [W] | 5 | 5 | 12.9 | 5 | 5 | 5 | 5 | 12.3 | 5 | 5 |
Temperature coefficient of Pmax (TCP) [%/°C] | −0.350% | −0.350% | −0.300% | −0.340% | −0.259% | −0.380% | −0.260% | −0.340% | −0.360% | −0.340% |
Open-circuit voltage—NOCT (VOCNOCT) [V] | 35.34 | 39.63 | 36.56 | 47.1 | 42.3 | 41.8 | 41.7 | 38.97 | 35.2 | 38.9 |
Open-circuit voltage—STC (VOCSTC) [V] | 37.4 | 41.94 | 38.49 | 49.4 | 44.6 | 45.69 | 44.3 | 41.9 | 37.45 | 41.4 |
Temperature coefficient of VOCSTC (TCV) [%/°C] | −0.270% | −0.272% | −0.250% | −0.270% | −0.234% | −0.300% | −0.240% | 0.250% | −0.300% | −0.250% |
Short-circuit current—NOCT (ISCNOCT) [A] | 11.26 | 9.4 | 11.49 | 8.11 | 8.7 | 9.25 | 8.57 | 10.22 | 11.16 | 9.95 |
Short-circuit current—STC (ISCSTC) [A] | 13.88 | 11.58 | 14.23 | 10.07 | 10.9 | 11.45 | 10.61 | 12.47 | 13.88 | 12.34 |
Temperature coefficient of ISCSTC (TCI) [%/°C] | 0.045% | 0.044% | 0.046% | 0.040% | 0.033% | 0.050% | 0.040% | 0.040% | 0.060% | 0.040% |
Module efficiency (ME) [%] | 21.00% | 20.90% | 22.02% | 21.10% | 21.70% | 20.98% | 21.70% | 21.30% | 21.00% | 21.10% |
Guaranteed power performance after 1 year (PP1) [%] | 98.0% | 98.0% | 99.0% | 98.0% | 98.0% | 98.0% | 98.0% | 98.0% | 97.0% | 98.0% |
Guaranteed power performance after 25 years (PP25) [%] | 84.8% | 83.0% | 89.4% | 84.8% | 92.0% | 84.8% | 92.0% | 84.8% | 83.0% | 84.8% |
Product warranty (PrW) [years] | 12 | 12 | 12 | 25 | 25 | 15 | 20 | 12 | 20 | 15 |
Performance warranty (PfW) [years] | 25 | 25 | 30 | 25 | 25 | 25 | 25 | 25 | 30 | 25 |
Dimensions—length (DL) [mm] | 1722 | 1776 | 1722 | 1646 | 1767 | 1925 | 1721 | 1754 | 1724 | 1754 |
Dimensions—width (DW) [mm] | 1134 | 1052 | 1134 | 1140 | 1041 | 1040 | 1016 | 1096 | 1134 | 1096 |
Dimensions—height (DH) [mm] | 30 | 35 | 30 | 30 | 35 | 35 | 30 | 30 | 30 | 30 |
Weight (We) [kg] | 21.6 | 20.7 | 22 | 19 | 19.7 | 23 | 19.5 | 21.5 | 22.1 | 21 |
Price per W (PW) [PLN/W] | 1.52 | 1.57 | 1.59 | 1.76 | 3.77 | 1.6 | 2.93 | 1.76 | 1.99 | 1.6 |
No. | Name | Unit of Measure | Preference Direction | Membership Function Type |
---|---|---|---|---|
C1 | Power | [W] | max | TFN |
C2 | Module efficiency | [%] | max | TrFN |
C3 | Open-circuit voltage | [V] | max | TrFN |
C4 | Short-circuit current | [A] | max | TrFN |
C5 | Price per watt | [PLN/W] | min | RN |
C6 | Weight | [kg] | min | RN |
C7 | Area | [m2] | min | RN |
C8 | Warranty | [years] | max | IN |
A1—Astronergy CHSM54M-HC (182) | A2—JA Solar JAM60S20 390/MR | A3—Jinko Solar JKM430N-54HL4 | A4—Kensol KS395M-SH | A5—Meyer Burger White | A6—Phono Solar PS420M4-22/WH | A7—REC 380AA | A8—Risen RSM40-8-410M | A9—Selfa SV108M.3-410 | A10—Trina Solar TSM-DE09.08 405W | |
---|---|---|---|---|---|---|---|---|---|---|
C1 | (306.40, 323.90, 410.00, 415.00) | (295.00, 308.10, 390.00, 395.00) | (323.00, 352.60, 430.00, 442.90) | (297.00, 314.42, 395.00, 400.00) | (302.00, 337.84, 400.00, 405.00) | (310.00, 324.24, 420.00, 425.00) | (289.00, 320.72, 380.00, 385.00) | (310.70, 326.36, 410.00, 422.30) | (309.60, 321.44, 410.00, 415.00) | (306.00, 322.38, 405.00, 410.00) |
C2 | (17.81, 20.58, 21.00) | (17.35, 20.48, 20.90) | (19.69, 21.80, 22.02) | (17.89, 20.68, 21.10) | (19.96, 21.27, 21.70) | (17.79, 20.56, 20.98) | (19.96, 21.27, 21.70) | (18.06, 20.87, 21.30) | (17.43, 20.37, 21.00) | (17.89, 20.68, 21.10) |
C3 | (31.34, 35.34, 37.40) | (35.10, 39.63, 41.94) | (32.72, 36.56, 38.49) | (41.40, 47.10, 49.40) | (38.34, 42.30, 44.60) | (37.47, 41.80, 45.69) | (37.92, 41.70, 44.30) | (35.62, 38.97, 41.90) | (30.71, 35.20, 37.45) | (35.19, 38.90, 41.40) |
C4 | (11.26, 13.88, 14.25) | (9.40, 11.58, 11.89) | (11.49, 14.23, 14.62) | (8.11, 10.07, 10.31) | (8.70, 10.90, 11.12) | (9.25, 11.45, 11.79) | (8.57, 10.61, 10.86) | (10.22, 12.47, 12.77) | (11.16, 13.88, 14.38) | (9.95, 12.34, 12.64) |
C5 | 1.52 | 1.57 | 1.59 | 1.76 | 3.77 | 1.60 | 2.93 | 1.76 | 1.99 | 1.60 |
C6 | 21.6 | 20.7 | 22.0 | 19.0 | 19.7 | 23.0 | 19.5 | 21.5 | 22.1 | 21.0 |
C7 | 1.95 | 1.87 | 1.95 | 1.88 | 1.84 | 2.00 | 1.75 | 1.92 | 1.96 | 1.92 |
C8 | (12, 25) | (12, 25) | (12, 30) | (25, 25) | (25, 25) | (15, 25) | (20, 25) | (12, 25) | (20, 30) | (15, 25) |
No. | Name | Weight | Preference Function | Preference Threshold |
---|---|---|---|---|
C1 | Power | VH | V-shaped | 99.098 |
C2 | Module efficiency | H | V-shaped | 0.026 |
C3 | Open-circuit voltage | M | V-shaped | 8.505 |
C4 | Short-circuit current | M | V-shaped | 3.491 |
C5 | Price per watt | VH | V-shaped | 1.434 |
C6 | Weight | VL | V-shaped | 2.468 |
C7 | Area | L | V-shaped | 0.138 |
C8 | Warranty | MH | V-shaped | 12.126 |
A1 | A2 | A3 | A4 | A5 | A6 | A7 | A8 | A9 | A10 | |
---|---|---|---|---|---|---|---|---|---|---|
(0.0727, 0.1233, 0.4023, 0.6264) | (0.0800, 0.0977, 0.3256, 0.6215) | (0.0658, 0.1460, 0.5665, 0.6907) | (0.0878, 0.1648, 0.4192, 0.6357) | (0.0376, 0.0681, 0.3838, 0.6322) | (0.0544, 0.0852, 0.3976, 0.6465) | (0.0667, 0.0910, 0.3504, 0.6128) | (0.0527, 0.0835, 0.3814, 0.6482) | (0.0433, 0.0949, 0.4052, 0.6325) | (0.0646, 0.0939, 0.3652, 0.6473) | |
0.3110 | 0.2906 | 0.3680 | 0.3311 | 0.2860 | 0.3016 | 0.2873 | 0.2980 | 0.2985 | 0.3004 | |
Rank | 3 | 8 | 1 | 2 | 10 | 4 | 9 | 7 | 6 | 5 |
(0.0302, 0.0791, 0.4316, 0.6734) | (0.0090, 0.0547, 0.4465, 0.6866) | (0.0297, 0.0607, 0.3236, 0.5694) | (0.0311, 0.0835, 0.3092, 0.5291) | (0.1982, 0.2459, 0.4145, 0.6322) | (0.0436, 0.0777, 0.4164, 0.6687) | (0.1620, 0.2125, 0.4828, 0.6639) | (0.0310, 0.0487, 0.3868, 0.6745) | (0.0742, 0.1351, 0.4147, 0.6411) | (0.0166, 0.0505, 0.3710, 0.6549) | |
0.3083 | 0.3036 | 0.2520 | 0.2435 | 0.3789 | 0.3070 | 0.3836 | 0.2923 | 0.3210 | 0.2802 | |
Rank | 7 | 5 | 2 | 1 | 9 | 6 | 10 | 4 | 8 | 3 |
(−0.6007, −0.3084, 0.3232, 0.5963) | (−0.6066, −0.3488, 0.2709, 0.6124) | (−0.5037, −0.1776, 0.5059, 0.6611) | (−0.4413, −0.1444, 0.3357, 0.6046) | (−0.5946, −0.3464, 0.1379, 0.4340) | (−0.6142, −0.3312, 0.3198, 0.6029) | (−0.5972, −0.3918, 0.1379, 0.4508) | (−0.6219, −0.3033, 0.3327, 0.6172) | (−0.5978, −0.3198, 0.2700, 0.5583) | (−0.5903, −0.2771, 0.3147, 0.6307) | |
0.0021 | −0.0158 | 0.1177 | 0.0878 | −0.0908 | −0.0057 | −0.0971 | 0.0053 | −0.0220 | 0.0196 | |
Rank | 5 | 7 | 1 | 2 | 9 | 6 | 10 | 4 | 8 | 3 |
A1 | A2 | A3 | A4 | A5 | A6 | A7 | A8 | A9 | A10 | |
---|---|---|---|---|---|---|---|---|---|---|
C1 | 410.00 | 390.00 | 430.00 | 395.00 | 400.00 | 420.00 | 380.00 | 410.00 | 410.00 | 405.00 |
C2 | 21.00 | 20.90 | 22.02 | 21.10 | 21.70 | 20.98 | 21.70 | 21.30 | 21.00 | 21.10 |
C3 | 37.40 | 41.94 | 38.49 | 49.40 | 44.60 | 45.69 | 44.30 | 41.90 | 37.45 | 41.40 |
C4 | 13.88 | 11.58 | 14.23 | 10.07 | 10.90 | 11.45 | 10.61 | 12.47 | 13.88 | 12.34 |
C5 | 1.52 | 1.57 | 1.59 | 1.76 | 3.77 | 1.60 | 2.93 | 1.76 | 1.99 | 1.60 |
C6 | 21.6 | 20.7 | 22.0 | 19.0 | 19.7 | 23.0 | 19.5 | 21.5 | 22.1 | 21.0 |
C7 | 1.95 | 1.87 | 1.95 | 1.88 | 1.84 | 2.00 | 1.75 | 1.92 | 1.96 | 1.92 |
C8 | 18.5 | 18.5 | 21 | 25 | 25 | 20 | 22.5 | 18.5 | 25 | 20 |
A1 | A2 | A3 | A4 | A5 | A6 | A7 | A8 | A9 | A10 | |
---|---|---|---|---|---|---|---|---|---|---|
0.2026 | 0.1235 | 0.4862 | 0.2933 | 0.3285 | 0.2582 | 0.2833 | 0.2149 | 0.2706 | 0.1838 | |
Rank | 8 | 10 | 1 | 3 | 2 | 6 | 4 | 7 | 5 | 9 |
0.2629 | 0.3528 | 0.1249 | 0.2421 | 0.3355 | 0.2266 | 0.4282 | 0.2166 | 0.2311 | 0.2242 | |
Rank | 7 | 9 | 1 | 6 | 8 | 4 | 10 | 2 | 5 | 3 |
0.2629 | 0.3528 | 0.1249 | 0.2421 | 0.3355 | 0.2266 | 0.4282 | 0.2166 | 0.2311 | 0.2242 | |
Rank | 8 | 10 | 1 | 2 | 6 | 4 | 9 | 5 | 3 | 7 |
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Ziemba, P.; Szaja, M. Fuzzy Decision-Making Model for Solar Photovoltaic Panel Evaluation. Energies 2023, 16, 5161. https://doi.org/10.3390/en16135161
Ziemba P, Szaja M. Fuzzy Decision-Making Model for Solar Photovoltaic Panel Evaluation. Energies. 2023; 16(13):5161. https://doi.org/10.3390/en16135161
Chicago/Turabian StyleZiemba, Paweł, and Marta Szaja. 2023. "Fuzzy Decision-Making Model for Solar Photovoltaic Panel Evaluation" Energies 16, no. 13: 5161. https://doi.org/10.3390/en16135161
APA StyleZiemba, P., & Szaja, M. (2023). Fuzzy Decision-Making Model for Solar Photovoltaic Panel Evaluation. Energies, 16(13), 5161. https://doi.org/10.3390/en16135161