Application of TOPSIS Approach to Multi-Criteria Selection of Wind Turbines for On-Shore Sites
Abstract
:1. Introduction
2. Literature Review
3. Contributions of the Proposed Work
- A TOPSIS-based approach is proposed for the turbine selection problem. To the best of our knowledge, this study is the first attempt to solve the turbine selection problem using the TOPSIS method.
- A multi-criteria decision approach is employed using important and relevant criteria. These criteria include hub height, wind speed, percentage of zero power, percentage of rated power, and annual energy production. The importance of these criteria is endorsed by several previous studies [18,21,29,36,37]. Furthermore, the approach is robust and scalable, and can be easily extended to accommodate more selection criteria.
- As opposed to many previous studies, the proposed method was tested on real data collected from two potential sites in Saudi Arabia, namely, Turaif and Wejh. However, the approach is generic and is broadly applicable to any real site around the globe.
- To demonstrate the impact and diversity of the TOPSIS approach in different scenarios, a comparative analysis on the performance of the proposed TOPSIS approach is provided with regard to the two diverse potential sites. Both sites have different topographic and climatic conditions.
- Comparison of the TOPSIS approach is done with three other MCDM techniques that were employed for turbine selection problem in previous studies [18,19,20,21,22,23]. These techniques include the weighted sum method, fuzzy logic, and goal programming. The comparison aims at analyzing the trends of a turbine type for the two sites when TOPSIS is used and when all four techniques are used in an aggregated manner.
4. Methodology
5. Application of the TOPSIS Method for Turbine Selection
- Calculate the normalized decision matrix. The calculation of the normalized value is done as
- Calculate the weighted normalized decision matrix. The calculation of weighted normalized value is done as
- Determine the ideal solutions (both positive and negative):
- Calculate the separation measures, using the n-dimensional Euclidean distance. The separation of each solution from the positive ideal solution is given asSimilarly, the separation from the negative ideal solution is given as
- Calculate the relative closeness to the ideal solution. The relative closeness of the solution with respect to is defined asNote that since and , then
- Rank the preference order. The solution with the highest value of is the best solution.
6. Results and Discussion
6.1. TOPSIS Analysis for Identification of Best Tradeoff
6.2. TOPSIS Analysis for Identification of Best Turbine
6.3. Comparison between Turaif and Wejh
7. Comparison with Other Multi-Criteria Decision-Making Techniques
7.1. Brief Discussion of Other MCDM Techniques
7.2. Comparative Results
8. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Abbreviations
normalized value of criteria | |
weighted normalized value of criteria | |
weight of criterion j | |
ideal positive solution | |
ideal negative solution | |
separation from positive ideal solution | |
separation from negative ideal solution | |
relative closeness of solution w.r.t. | |
Weighted sum of turbine t | |
Membership function for turbine t | |
Membership function for hub height | |
Membership function for wind speed | |
Membership function for percentage of zero output | |
Membership function for percentage of rated output | |
Membership function for annual energy production | |
Dev(t) | Collective deviation for all criteria for turbine t |
Ideal value of criterion x | |
Actual achieved value of criterion x | |
Multi-criteria decision-making | |
Technique for Order of Preference by Similarity to Ideal Solution | |
Genetic Algorithms | |
Particle Swarm Optimization | |
Analytical Hierarchy Process | |
Weighted aggregated sum product assessment | |
Hub height (in meters) | |
Wind speed (in m/s) | |
Percentage of zero output | |
Percentage of rated output | |
Annual energy production (in kWh/yr) | |
Maximum Hub height (in meters) | |
Maximum Wind speed (in m/s) | |
Maximum Percentage of zero output | |
Maximum Percentage of rated output | |
Maximum Annual energy production (in kWh/yr) | |
Fuzzy logic | |
Weighted sum method | |
Goal programming | |
Acciona | Acciona AW70/1500 Class I |
Alstom | Alstom ECO 100/2000 Class I |
DeWind | DeWind D92 |
Dongfang | Dongfang DF110-2500 |
Doosan | Doosan WinDS 3000 |
EnerconE2 | Enercon E-82E2/2000 |
EnerconE4 | Enercon E-82E4/3000 |
Gamesa | Gamesa G97-2.0MW |
Hanjin | Hanjin HJWT2000-93 |
Leiwtwind | Leitwind LTW70-2000 |
Nordex | Nordex N131/3000 |
Sinovel | Sinovel SL3000/115 |
Vestas112 | Vestas V112-3.0MW |
Vestas110 | Vestas V110-2.0MW |
Windtec | Windtec FC3000-130 |
Appendix A
HH | Turaif | Wejh | ||||||||
---|---|---|---|---|---|---|---|---|---|---|
(m) | WS | ZP | RP | AEP | WS | ZP | RP | AEP | ||
50 | 6.08 | 13.56 | 0.16 | 2,511,427 | 0.427 | 4.99 | 22.90 | 0.01 | 1,631,379 | 0.344 |
60 | 6.24 | 12.87 | 0.21 | 2,696,078 | 0.429 * | 5.11 | 21.80 | 0.02 | 1,761,383 | 0.343 |
70 | 6.37 | 12.33 | 0.26 | 2,859,608 | 0.428 | 5.23 | 20.94 | 0.03 | 1,877,239 | 0.350 |
80 | 6.49 | 11.88 | 0.31 | 3,006,741 | 0.423 | 5.33 | 20.23 | 0.04 | 1,982,126 | 0.369 |
90 | 6.6 | 11.51 | 0.36 | 3,140,724 | 0.409 | 5.41 | 19.60 | 0.05 | 2,078,069 | 0.400 |
100 | 6.7 | 11.17 | 0.41 | 3,263,976 | 0.386 | 5.49 | 19.06 | 0.06 | 2,166,765 | 0.440 |
110 | 6.79 | 10.87 | 0.46 | 3,378,100 | 0.352 | 5.57 | 18.56 | 0.08 | 2,249,234 | 0.539 |
120 | 6.87 | 10.61 | 0.51 | 3,484,564 | 0.314 | 5.64 | 18.15 | 0.09 | 2,326,365 | 0.572 |
130 | 6.95 | 10.38 | 0.56 | 3,584,210 | 0.282 | 5.70 | 17.77 | 0.11 | 2,398,928 | 0.631 |
140 | 7.02 | 10.17 | 0.62 | 3,678,128 | 0.265 | 5.76 | 17.41 | 0.13 | 2,467,511 | 0.656 * |
HH | Turaif | Wejh | ||||||||
---|---|---|---|---|---|---|---|---|---|---|
(m) | WS | ZP | RP | AEP | WS | ZP | RP | AEP | ||
50 | 6.08 | 2.66 | 0.06 | 5,311,341 | 0.409 | 4.99 | 0.12 | 0.00 | 3,485,619 | 0.319 |
60 | 6.24 | 2.53 | 0.08 | 5,704,562 | 0.411 | 5.11 | 0.12 | 0.00 | 3,762,654 | 0.295 |
70 | 6.37 | 2.42 | 0.10 | 6,052,657 | 0.418 | 5.23 | 0.12 | 0.01 | 4,009,747 | 0.368 |
80 | 6.49 | 2.34 | 0.13 | 6,365,770 | 0.456 | 5.33 | 0.11 | 0.01 | 4,233,309 | 0.350 |
90 | 6.60 | 2.26 | 0.15 | 6,650,370 | 0.483 | 5.41 | 0.11 | 0.01 | 4,437,715 | 0.330 |
100 | 6.70 | 2.19 | 0.17 | 6,911,742 | 0.512 | 5.49 | 0.11 | 0.02 | 4,626,457 | 0.496 |
110 | 6.79 | 2.14 | 0.19 | 7,153,358 | 0.537 | 5.57 | 0.11 | 0.02 | 4,801,919 | 0.480 |
120 | 6.87 | 2.08 | 0.21 | 7,378,063 | 0.555 | 5.64 | 0.10 | 0.03 | 4,966,023 | 0.635 |
130 | 6.95 | 2.04 | 0.24 | 7,588,310 | 0.580 | 5.70 | 0.10 | 0.03 | 5,120,199 | 0.613 |
140 | 7.02 | 2.00 | 0.27 | 7,785,749 | 0.591 * | 5.76 | 0.10 | 0.04 | 5,265,803 | 0.681* |
HH | Turaif | Wejh | ||||||||
---|---|---|---|---|---|---|---|---|---|---|
(m) | WS | ZP | RP | AEP | WS | ZP | RP | AEP | ||
50 | 6.08 | 23.90 | 0.33 | 3,554,286 | 0.436 | 4.99 | 38.21 | 0.04 | 2,163,993 | 0.360 |
60 | 6.24 | 22.70 | 0.42 | 3,868,633 | 0.442 | 5.11 | 36.60 | 0.07 | 2,375,710 | 0.362 |
70 | 6.37 | 21.76 | 0.51 | 4,145,965 | 0.454 | 5.23 | 35.30 | 0.09 | 2,564,732 | 0.361 |
80 | 6.49 | 20.97 | 0.60 | 4,394,194 | 0.474 | 5.33 | 34.19 | 0.12 | 2,735,843 | 0.382 |
90 | 6.60 | 20.31 | 0.69 | 4,618,874 | 0.499 | 5.41 | 33.19 | 0.15 | 2,892,282 | 0.416 |
100 | 6.70 | 19.72 | 0.78 | 4,824,184 | 0.524 | 5.49 | 32.35 | 0.19 | 3,036,566 | 0.479 |
110 | 6.79 | 19.21 | 0.87 | 5,012,960 | 0.545 | 5.57 | 31.59 | 0.23 | 3,170,538 | 0.542 |
120 | 6.87 | 18.77 | 0.97 | 5,187,854 | 0.561 | 5.64 | 30.93 | 0.27 | 3,295,595 | 0.591 |
130 | 6.95 | 18.37 | 1.06 | 5,350,521 | 0.564 * | 5.70 | 30.31 | 0.32 | 3,412,988 | 0.632 |
140 | 7.02 | 17.99 | 1.15 | 5,502,655 | 0.564 * | 5.76 | 29.77 | 0.36 | 3,523,561 | 0.640 * |
HH | Turaif | Wejh | ||||||||
---|---|---|---|---|---|---|---|---|---|---|
(m) | WS | ZP | RP | AEP | WS | ZP | RP | AEP | ||
50 | 6.08 | 9.39 | 3.34 | 6,519,861 | 0.442 | 4.99 | 16.13 | 1.59 | 4,346,507 | 0.438 |
60 | 6.24 | 8.93 | 4.23 | 6,965,871 | 0.446 | 5.11 | 15.34 | 2.09 | 4,664,726 | 0.446 |
70 | 6.37 | 8.55 | 5.23 | 7,355,533 | 0.459 | 5.23 | 14.73 | 2.59 | 4,945,179 | 0.460 |
80 | 6.49 | 8.22 | 6.24 | 7,700,508 | 0.481 | 5.33 | 14.21 | 3.10 | 5,195,996 | 0.485 |
90 | 6.60 | 7.96 | 7.24 | 8,009,363 | 0.508 | 5.41 | 13.76 | 3.58 | 5,423,059 | 0.511 |
100 | 6.70 | 7.71 | 8.21 | 8,288,809 | 0.534 | 5.49 | 13.37 | 4.05 | 5,630,576 | 0.537 |
110 | 6.79 | 7.51 | 9.14 | 8,543,449 | 0.551 | 5.57 | 13.03 | 4.52 | 5,821,956 | 0.555 |
120 | 6.87 | 7.32 | 10.06 | 8,777,304 | 0.559 | 5.64 | 12.71 | 4.98 | 5,999,156 | 0.564 |
130 | 6.95 | 7.16 | 10.94 | 8,993,076 | 0.560 * | 5.70 | 12.45 | 5.43 | 6,164,460 | 0.566 * |
140 | 7.02 | 7.00 | 11.82 | 9,193,307 | 0.558 | 5.76 | 12.19 | 5.84 | 6,319,248 | 0.562 |
HH | Turaif | Wejh | ||||||||
---|---|---|---|---|---|---|---|---|---|---|
(m) | WS | ZP | RP | AEP | WS | ZP | RP | AEP | ||
50 | 6.08 | 9.40 | 0.47 | 4,369,087 | 0.441 | 4.99 | 16.13 | 0.08 | 2,865,384 | 0.368 |
60 | 6.24 | 8.93 | 0.59 | 4,729,954 | 0.447 | 5.11 | 15.34 | 0.12 | 3,103,645 | 0.365 |
70 | 6.37 | 8.56 | 0.71 | 5,057,001 | 0.458 | 5.23 | 14.74 | 0.16 | 3,319,926 | 0.367 |
80 | 6.49 | 8.23 | 0.84 | 5,356,886 | 0.480 | 5.33 | 14.21 | 0.21 | 3,518,405 | 0.387 |
90 | 6.60 | 7.96 | 0.96 | 5,634,306 | 0.504 | 5.41 | 13.76 | 0.27 | 3,702,388 | 0.431 |
100 | 6.70 | 7.72 | 1.08 | 5,892,609 | 0.528 | 5.49 | 13.38 | 0.33 | 3,874,142 | 0.486 |
110 | 6.79 | 7.51 | 1.19 | 6,134,469 | 0.542 | 5.57 | 13.04 | 0.38 | 4,035,330 | 0.528 |
120 | 6.87 | 7.32 | 1.32 | 6,361,797 | 0.556 | 5.64 | 12.71 | 0.45 | 4,187,367 | 0.582 |
130 | 6.95 | 7.16 | 1.44 | 6,576,412 | 0.559 * | 5.70 | 12.46 | 0.53 | 4,331,374 | 0.621 |
140 | 7.02 | 7.00 | 1.56 | 6,779,562 | 0.559 * | 5.76 | 12.20 | 0.60 | 4,468,187 | 0.632 * |
HH | Turaif | Wejh | ||||||||
---|---|---|---|---|---|---|---|---|---|---|
(m) | WS | ZP | RP | AEP | WS | ZP | RP | AEP | ||
50 | 6.08 | 1.67 | 0.55 | 3,908,583 | 0.446 | 4.99 | 2.99 | 0.10 | 2,563,184 | 0.370 |
60 | 6.24 | 1.59 | 0.69 | 4,201,630 | 0.452 | 5.11 | 2.83 | 0.15 | 2,765,474 | 0.368 |
70 | 6.37 | 1.53 | 0.83 | 4,460,943 | 0.463 | 5.23 | 2.71 | 0.20 | 2,945,786 | 0.370 |
80 | 6.49 | 1.47 | 0.96 | 4,693,399 | 0.477 | 5.33 | 2.61 | 0.27 | 3,108,770 | 0.397 |
90 | 6.60 | 1.43 | 1.10 | 4,904,445 | 0.499 | 5.41 | 2.53 | 0.33 | 3,257,746 | 0.429 |
100 | 6.70 | 1.39 | 1.22 | 5,097,631 | 0.514 | 5.49 | 2.45 | 0.40 | 3,395,056 | 0.479 |
110 | 6.79 | 1.35 | 1.37 | 5,275,713 | 0.537 | 5.57 | 2.37 | 0.48 | 3,522,579 | 0.538 |
120 | 6.87 | 1.31 | 1.50 | 5,440,956 | 0.545 | 5.64 | 2.31 | 0.57 | 3,641,713 | 0.592 |
130 | 6.95 | 1.28 | 1.64 | 5,595,181 | 0.550 | 5.70 | 2.26 | 0.65 | 3,753,511 | 0.617 |
140 | 7.02 | 1.26 | 1.80 | 5,739,430 | 0.554 * | 5.76 | 2.22 | 0.74 | 3,858,955 | 0.630 * |
HH | Turaif | Wejh | ||||||||
---|---|---|---|---|---|---|---|---|---|---|
(m) | WS | ZP | RP | AEP | WS | ZP | RP | AEP | ||
50 | 6.08 | 6.03 | 0.03 | 3,874,862 | 0.394 | 4.99 | 10.52 | 0.00 | 2,530,963 | 0.283 |
60 | 6.24 | 5.73 | 0.05 | 4,169,620 | 0.407 | 5.11 | 10.02 | 0.00 | 2,732,520 | 0.262 |
70 | 6.37 | 5.50 | 0.06 | 4,432,370 | 0.408 | 5.23 | 9.59 | 0.00 | 2,913,226 | 0.241 |
80 | 6.49 | 5.31 | 0.08 | 4,670,072 | 0.447 | 5.33 | 9.23 | 0.00 | 3,077,518 | 0.221 |
90 | 6.60 | 5.13 | 0.10 | 4,887,685 | 0.501 | 5.41 | 8.95 | 0.00 | 3,228,599 | 0.202 |
100 | 6.70 | 4.98 | 0.11 | 5,088,723 | 0.518 | 5.49 | 8.68 | 0.01 | 3,368,719 | 0.499 |
110 | 6.79 | 4.84 | 0.13 | 5,275,628 | 0.569 | 5.57 | 8.45 | 0.01 | 3,499,526 | 0.489 |
120 | 6.87 | 4.72 | 0.15 | 5,450,443 | 0.602 | 5.64 | 8.23 | 0.01 | 3,622,458 | 0.479 |
130 | 6.95 | 4.61 | 0.16 | 5,614,841 | 0.597 | 5.70 | 8.05 | 0.01 | 3,738,398 | 0.469 |
140 | 7.02 | 4.51 | 0.18 | 5,769,935 | 0.606 * | 5.76 | 7.88 | 0.02 | 3,848,353 | 0.717 * |
HH | Turaif | Wejh | ||||||||
---|---|---|---|---|---|---|---|---|---|---|
(m) | WS | ZP | RP | AEP | WS | ZP | RP | AEP | ||
50 | 6.08 | 5.58 | 0.14 | 4,971,160 | 0.431 | 4.99 | 10.03 | 0.01 | 3,287,488 | 0.351 |
60 | 6.24 | 5.30 | 0.17 | 5,311,123 | 0.428 | 5.11 | 9.54 | 0.02 | 3,532,671 | 0.349 |
70 | 6.37 | 5.07 | 0.21 | 5,606,868 | 0.435 | 5.23 | 9.12 | 0.03 | 3,748,451 | 0.356 |
80 | 6.49 | 4.88 | 0.26 | 5,868,372 | 0.462 | 5.33 | 8.80 | 0.04 | 3,941,565 | 0.374 |
90 | 6.60 | 4.72 | 0.30 | 6,102,752 | 0.485 | 5.41 | 8.50 | 0.05 | 4,116,268 | 0.403 |
100 | 6.70 | 4.57 | 0.34 | 6,314,648 | 0.511 | 5.49 | 8.25 | 0.07 | 4,275,954 | 0.499 |
110 | 6.79 | 4.45 | 0.38 | 6,508,118 | 0.533 | 5.57 | 8.04 | 0.08 | 4,423,102 | 0.537 |
120 | 6.87 | 4.34 | 0.43 | 6,685,633 | 0.558 | 5.64 | 7.84 | 0.10 | 4,559,555 | 0.613 |
130 | 6.95 | 4.25 | 0.47 | 6,849,496 | 0.563 | 5.70 | 7.65 | 0.11 | 4,686,655 | 0.625 |
140 | 7.02 | 4.17 | 0.52 | 7,001,725 | 0.569 * | 5.76 | 7.51 | 0.13 | 4,805,785 | 0.649 * |
HH | Turaif | Wejh | ||||||||
---|---|---|---|---|---|---|---|---|---|---|
(m) | WS | ZP | RP | AEP | WS | ZP | RP | AEP | ||
50 | 6.08 | 9.42 | 0.47 | 4,552,426 | 0.448 | 4.99 | 16.17 | 0.08 | 2,982,459 | 0.368 |
60 | 6.24 | 8.95 | 0.59 | 4,876,812 | 0.453 | 5.11 | 15.39 | 0.12 | 3,213,212 | 0.364 |
70 | 6.37 | 8.58 | 0.72 | 5,161,005 | 0.467 | 5.23 | 14.78 | 0.16 | 3,417,237 | 0.365 |
80 | 6.49 | 8.25 | 0.84 | 5,413,711 | 0.484 | 5.33 | 14.25 | 0.21 | 3,600,277 | 0.384 |
90 | 6.60 | 7.98 | 0.96 | 5,641,045 | 0.505 | 5.41 | 13.8 | 0.27 | 3,766,569 | 0.426 |
100 | 6.70 | 7.74 | 1.09 | 5,847,676 | 0.530 | 5.49 | 13.41 | 0.33 | 3,919,029 | 0.480 |
110 | 6.79 | 7.53 | 1.20 | 6,037,218 | 0.542 | 5.57 | 13.07 | 0.39 | 4,059,755 | 0.532 |
120 | 6.87 | 7.34 | 1.33 | 6,211,605 | 0.553 | 5.64 | 12.75 | 0.46 | 4,190,603 | 0.584 |
130 | 6.95 | 7.18 | 1.45 | 6,373,608 | 0.555 * | 5.70 | 12.49 | 0.53 | 4,312,877 | 0.615 |
140 | 7.02 | 7.03 | 1.56 | 6,524,469 | 0.552 | 5.76 | 12.23 | 0.61 | 4,427,608 | 0.632 * |
HH | Turaif | Wejh | ||||||||
---|---|---|---|---|---|---|---|---|---|---|
(m) | WS | ZP | RP | AEP | WS | ZP | RP | AEP | ||
50 | 6.08 | 6.01 | 0.33 | 2,590,458 | 0.439 | 4.99 | 10.49 | 0.04 | 1,695,636 | 0.363 |
60 | 6.24 | 5.72 | 0.42 | 2,791,523 | 0.445 | 5.11 | 9.99 | 0.07 | 1,831,760 | 0.365 |
70 | 6.37 | 5.49 | 0.51 | 2,972,116 | 0.456 | 5.23 | 9.57 | 0.09 | 1,954,550 | 0.365 |
80 | 6.49 | 5.29 | 0.59 | 3,136,781 | 0.469 | 5.33 | 9.20 | 0.12 | 2,066,902 | 0.387 |
90 | 6.60 | 5.11 | 0.69 | 3,288,471 | 0.500 | 5.41 | 8.91 | 0.15 | 2,170,740 | 0.423 |
100 | 6.70 | 4.96 | 0.78 | 3,429,386 | 0.525 | 5.49 | 8.65 | 0.18 | 2,267,467 | 0.467 |
110 | 6.79 | 4.82 | 0.87 | 3,561,223 | 0.545 | 5.57 | 8.42 | 0.22 | 2,358,216 | 0.532 |
120 | 6.87 | 4.71 | 0.96 | 3,685,270 | 0.557 | 5.64 | 8.20 | 0.27 | 2,443,829 | 0.601 |
130 | 6.95 | 4.59 | 1.06 | 3,802,472 | 0.564 * | 5.70 | 8.02 | 0.31 | 2,524,915 | 0.628 |
140 | 7.02 | 4.50 | 1.14 | 3,913,676 | 0.561 | 5.76 | 7.86 | 0.35 | 2,602,009 | 0.637 * |
HH | Turaif | Wejh | ||||||||
---|---|---|---|---|---|---|---|---|---|---|
(m) | WS | ZP | RP | AEP | WS | ZP | RP | AEP | ||
50 | 6.08 | 8.62 | 0.92 | 8,504,922 | 0.456 | 4.99 | 15.32 | 0.31 | 5,760,853 | 0.394 |
60 | 6.24 | 8.19 | 1.12 | 9,031,649 | 0.460 | 5.11 | 14.61 | 0.43 | 6,160,035 | 0.391 |
70 | 6.37 | 7.84 | 1.33 | 9,485,898 | 0.468 | 5.23 | 14 | 0.57 | 6,509,001 | 0.400 |
80 | 6.49 | 7.54 | 1.52 | 9,884,089 | 0.477 | 5.33 | 13.51 | 0.73 | 6,818,982 | 0.425 |
90 | 6.60 | 7.30 | 1.73 | 10,238,104 | 0.493 | 5.41 | 13.09 | 0.88 | 7,097,942 | 0.459 |
100 | 6.70 | 7.08 | 1.93 | 10,556,804 | 0.508 | 5.49 | 12.7 | 1.04 | 7,351,799 | 0.503 |
110 | 6.79 | 6.90 | 2.14 | 10,845,975 | 0.522 | 5.57 | 12.37 | 1.2 | 7,584,389 | 0.544 |
120 | 6.87 | 6.73 | 2.37 | 11,109,818 | 0.535 | 5.64 | 12.08 | 1.38 | 7,799,305 | 0.580 |
130 | 6.95 | 6.57 | 2.59 | 11,352,896 | 0.540 | 5.70 | 11.82 | 1.55 | 7,998,834 | 0.598 |
140 | 7.02 | 6.45 | 2.84 | 11,578,293 | 0.544 * | 5.76 | 11.58 | 1.74 | 8,185,010 | 0.606 * |
HH | Turaif | Wejh | ||||||||
---|---|---|---|---|---|---|---|---|---|---|
(m) | WS | ZP | RP | AEP | WS | ZP | RP | AEP | ||
50 | 6.08 | 9.39 | 0.96 | 6,632,186 | 0.439 | 4.99 | 16.12 | 0.27 | 4,418,179 | 0.391 |
60 | 6.24 | 8.92 | 1.18 | 7,095,683 | 0.441 | 5.11 | 15.33 | 0.38 | 4,746,076 | 0.390 |
70 | 6.37 | 8.55 | 1.40 | 7,503,843 | 0.446 | 5.23 | 14.73 | 0.50 | 5,037,027 | 0.398 |
80 | 6.49 | 8.22 | 1.62 | 7,868,771 | 0.457 | 5.33 | 14.20 | 0.64 | 5,298,941 | 0.423 |
90 | 6.60 | 7.95 | 1.87 | 8,199,107 | 0.478 | 5.41 | 13.75 | 0.77 | 5,537,503 | 0.456 |
100 | 6.70 | 7.71 | 2.11 | 8,500,607 | 0.501 | 5.49 | 13.36 | 0.91 | 5,756,929 | 0.500 |
110 | 6.79 | 7.51 | 2.37 | 8,777,953 | 0.524 | 5.57 | 13.02 | 1.06 | 5,959,892 | 0.546 |
120 | 6.87 | 7.32 | 2.64 | 9,034,599 | 0.543 | 5.64 | 12.70 | 1.22 | 6,149,030 | 0.582 |
130 | 6.95 | 7.15 | 2.93 | 9,273,298 | 0.555 | 5.70 | 12.45 | 1.38 | 6,325,976 | 0.602 |
140 | 7.02 | 7.00 | 3.23 | 9,496,276 | 0.561 * | 5.76 | 12.19 | 1.54 | 6,492,396 | 0.609 * |
HH | Turaif | Wejh | ||||||||
---|---|---|---|---|---|---|---|---|---|---|
(m) | WS | ZP | RP | AEP | WS | ZP | RP | AEP | ||
50 | 6.08 | 9.40 | 1.03 | 6,004,721 | 0.440 | 4.99 | 16.13 | 0.3 | 4,029,225 | 0.394 |
60 | 6.24 | 8.93 | 1.26 | 6,376,031 | 0.440 | 5.11 | 15.34 | 0.42 | 4,306,757 | 0.393 |
70 | 6.37 | 8.56 | 1.49 | 6,694,271 | 0.443 | 5.23 | 14.74 | 0.57 | 4,548,616 | 0.405 |
80 | 6.49 | 8.23 | 1.75 | 6,971,803 | 0.456 | 5.33 | 14.22 | 0.71 | 4,763,187 | 0.426 |
90 | 6.60 | 7.96 | 2.00 | 7,217,285 | 0.472 | 5.41 | 13.77 | 0.85 | 4,955,901 | 0.458 |
100 | 6.70 | 7.72 | 2.27 | 7,436,972 | 0.496 | 5.49 | 13.38 | 1.01 | 5,130,901 | 0.503 |
110 | 6.79 | 7.52 | 2.55 | 7,635,472 | 0.519 | 5.57 | 13.04 | 1.17 | 5,291,203 | 0.546 |
120 | 6.87 | 7.32 | 2.85 | 7,816,086 | 0.539 | 5.64 | 12.71 | 1.35 | 5,438,905 | 0.583 |
130 | 6.95 | 7.16 | 3.18 | 7,981,536 | 0.554 | 5.70 | 12.46 | 1.51 | 5,575,759 | 0.598 |
140 | 7.02 | 7.01 | 3.51 | 8,133,928 | 0.560 * | 5.76 | 12.2 | 1.69 | 5,703,519 | 0.606 * |
HH | Turaif | Wejh | ||||||||
---|---|---|---|---|---|---|---|---|---|---|
(m) | WS | ZP | RP | AEP | WS | ZP | RP | AEP | ||
50 | 6.08 | 13.40 | 0.33 | 6,424,320 | 0.439 | 4.99 | 22.64 | 0.05 | 4,200,601 | 0.370 |
60 | 6.24 | 12.72 | 0.43 | 6,901,962 | 0.448 | 5.11 | 21.56 | 0.07 | 4,533,556 | 0.363 |
70 | 6.37 | 12.19 | 0.51 | 7,323,283 | 0.455 | 5.23 | 20.73 | 0.09 | 4,829,414 | 0.359 |
80 | 6.49 | 11.76 | 0.60 | 7,700,227 | 0.472 | 5.33 | 20.01 | 0.12 | 5,096,189 | 0.375 |
90 | 6.60 | 11.38 | 0.70 | 8,041,682 | 0.501 | 5.41 | 19.39 | 0.16 | 5,339,421 | 0.425 |
100 | 6.70 | 11.04 | 0.79 | 8,353,468 | 0.525 | 5.49 | 18.84 | 0.19 | 5,563,363 | 0.467 |
110 | 6.79 | 10.74 | 0.88 | 8,640,153 | 0.544 | 5.57 | 18.36 | 0.23 | 5,770,720 | 0.529 |
120 | 6.87 | 10.49 | 0.97 | 8,905,399 | 0.555 | 5.64 | 17.95 | 0.27 | 5,964,065 | 0.579 |
130 | 6.95 | 10.25 | 1.07 | 9,152,209 | 0.562 * | 5.70 | 17.57 | 0.32 | 6,145,047 | 0.621 |
140 | 7.02 | 10.05 | 1.16 | 9,382,609 | 0.561 | 5.76 | 17.22 | 0.36 | 6,315,349 | 0.630 * |
HH | Turaif | Wejh | ||||||||
---|---|---|---|---|---|---|---|---|---|---|
(m) | WS | ZP | RP | AEP | WS | ZP | RP | AEP | ||
50 | 6.08 | 11.36 | 2.05 | 8,508,531 | 0.431 | 4.99 | 19.35 | 0.88 | 5,709,133 | 0.419 |
60 | 6.24 | 10.77 | 2.56 | 9,054,678 | 0.430 | 5.11 | 18.41 | 1.18 | 6,108,825 | 0.422 |
70 | 6.37 | 10.32 | 3.14 | 9,525,854 | 0.437 | 5.23 | 17.68 | 1.49 | 6,458,727 | 0.432 |
80 | 6.49 | 9.94 | 3.75 | 9,939,049 | 0.453 | 5.33 | 17.05 | 1.82 | 6,770,263 | 0.454 |
90 | 6.60 | 9.62 | 4.36 | 10,306,589 | 0.476 | 5.41 | 16.51 | 2.16 | 7,051,016 | 0.487 |
100 | 6.70 | 9.34 | 5.06 | 10,636,346 | 0.510 | 5.49 | 16.04 | 2.50 | 7,306,586 | 0.523 |
110 | 6.79 | 9.10 | 5.75 | 10,935,505 | 0.540 | 5.57 | 15.61 | 2.84 | 7,541,109 | 0.554 |
120 | 6.87 | 8.88 | 6.43 | 11,208,357 | 0.559 | 5.64 | 15.26 | 3.19 | 7,757,882 | 0.574 |
130 | 6.95 | 8.69 | 7.11 | 11,458,985 | 0.568 | 5.70 | 14.95 | 3.52 | 7,959,208 | 0.581 * |
140 | 7.02 | 8.51 | 7.77 | 11,690,264 | 0.569 * | 5.76 | 14.66 | 3.84 | 8,147,224 | 0.581 * |
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Ref. | Year | Method | Decision Approach | Number of Criteria |
---|---|---|---|---|
[5] | 2013 | Nil | Nil | 5 |
[6] | 2015 | GA | Multi-criteria | 5 |
[7] | 2010 | Others | Single-criteria | 1 |
[8] | 2013 | PSO | Single-criteria | 1 |
[9] | 2009 | Probabilistic model | Single-criteria | 1 |
[10] | 2014 | Weibull distribution | Single-criteria | 1 |
[12] | 2016 | Self-proposed | Single-criteria | 1 |
[13] | 2013 | GA | Single-criteria | 1 |
[14] | 2012 | Self-proposed | Single-criteria | 1 |
[15] | 2013 | GA, PSO, DE | Multi-criteria | 4 |
[16] | 2016 | AHP | Multi-criteria | Over 30 |
[17] | 2014 | WASPAS | Multi-criteria | 5 |
[18,19] | 2012 | Fuzzy logic | Multi-criteria | 3 |
[20] | 2016 | Fuzzy logic | Multi-criteria | 6 |
[21,23] | 2019, 2017 | Fuzzy goal programming | Multi-criteria | 6 |
[22] | 2017 | Weighted sum | Multi-criteria | 5 |
[24] | 2017 | AHP | Multi-criteria | 14 |
[25] | 2016 | Blade element momentum | Multi-criteria | 6 |
[26] | 2017 | Hybrid AHP–TOPSIS | Multi-crtieria | 4 |
[27] | 2015 | Weibull distribution | Single-criteria | 1 |
[28] | 2017 | Weibull distribution | Single-criteria | 1 |
[29] | 2019 | Pareto dominance | Multi-criteria | 3 |
[30] | 2020 | Hybrid AHP–TOPSIS | Multi-criteria | 9 |
Turbine | Rated Power (KW) | Rated Speed (m/s) | Rotor Diameter |
---|---|---|---|
Acciona AW 70/1500 Class I | 1500 | 14 | 70 |
Alstom ECO 100/2000 Class I | 3000 | 17 | 100 |
DeWind D92 | 2000 | 13 | 93 |
Dongfang DF110-2500 | 2500 | 10 | 110 |
Doosan WinDS3000 | 3000 | 12.5 | 91.3 |
Enercon E-82 E2/2000 | 2300 | 13 | 82 |
Enercon E-82 E4/3000 | 3000 | 16 | 82 |
Gamesa G97-2.0 MW | 2000 | 14 | 97 |
Hanjin HJWT2000-93 | 2000 | 12.5 | 93 |
Leitwind LTW70-2000 | 2000 | 13 | 70.1 |
Nordex N131/3000 | 3000 | 14 | 131 |
Sinovel SL3000/115 | 3000 | 11.5 | 115 |
Vestas V110-2.0MW | 2000 | 11.5 | 110 |
Vestas 112-3.0MW | 3075 | 11.5 | 112 |
Windtec FC 3000-130 | 3000 | 10.5 | 130 |
Turbine | HH | WS | ZP | RP | AEP | |||
---|---|---|---|---|---|---|---|---|
Acciona | 60 | 6.24 | 12.87 | 0.21 | 2,696,078 | 0.068 | 0.051 | 0.429 |
Alstom | 140 | 7.02 | 2.00 | 0.27 | 7,785,749 | 0.057 | 0.083 | 0.591 |
DeWind | 140 | 7.02 | 17.99 | 1.15 | 5,502,655 | 0.057 | 0.074 | 0.564 |
Dongfang | 130 | 6.95 | 7.16 | 10.94 | 8,993,076 | 0.051 | 0.066 | 0.560 |
Doosan | 140 | 7.02 | 7.00 | 1.56 | 6,779,562 | 0.057 | 0.073 | 0.559 |
EnerconE2 | 140 | 7.02 | 1.26 | 1.80 | 5,739,430 | 0.057 | 0.071 | 0.554 |
EnerconE4 | 140 | 7.02 | 4.51 | 0.18 | 5,769,935 | 0.057 | 0.088 | 0.606 * |
Gamesa | 140 | 7.02 | 4.17 | 0.52 | 7,001,725 | 0.057 | 0.076 | 0.569 |
Hanjin | 130 | 6.95 | 7.18 | 1.45 | 6,373,608 | 0.051 | 0.064 | 0.555 |
Leitwind | 130 | 6.95 | 4.59 | 1.06 | 3,802,472 | 0.051 | 0.067 | 0.564 |
Nordex | 140 | 7.02 | 6.45 | 2.84 | 11,578,293 | 0.057 | 0.068 | 0.544 |
Sinovel | 140 | 7.02 | 7.00 | 3.23 | 9,496,276 | 0.057 | 0.073 | 0.561 |
Vestas110 | 140 | 7.02 | 7.01 | 3.51 | 8,133,928 | 0.057 | 0.073 | 0.560 |
Vestas112 | 130 | 6.95 | 10.25 | 1.07 | 9,152,209 | 0.052 | 0.066 | 0.562 |
Windtec | 140 | 7.02 | 8.51 | 7.77 | 11,690,264 | 0.057 | 0.076 | 0.569 |
Turbine | HH | WS | ZP | RP | AEP | |||
---|---|---|---|---|---|---|---|---|
Acciona | 140 | 5.76 | 17.41 | 0.13 | 2,467,511 | 0.057 | 0.109 | 0.656 |
Alstom | 140 | 5.76 | 0.10 | 0.04 | 5,265,803 | 0.057 | 0.123 | 0.681 |
DeWind | 140 | 5.76 | 29.77 | 0.36 | 3,523,561 | 0.057 | 0.102 | 0.640 |
Dongfang | 130 | 5.70 | 12.45 | 5.43 | 6,164,460 | 0.051 | 0.067 | 0.566 |
Doosan | 140 | 5.76 | 12.20 | 0.60 | 4,468,187 | 0.057 | 0.099 | 0.632 |
EnerconE2 | 140 | 5.76 | 2.22 | 0.74 | 3,858,955 | 0.057 | 0.098 | 0.630 |
EnerconE4 | 140 | 5.76 | 7.88 | 0.02 | 3,848,353 | 0.057 | 0.145 | 0.717 * |
Gamesa | 140 | 5.76 | 7.51 | 0.13 | 4,805,785 | 0.057 | 0.106 | 0.649 |
Hanjin | 140 | 5.76 | 12.23 | 0.61 | 4,427,608 | 0.057 | 0.098 | 0.632 |
Leitwind | 140 | 5.76 | 7.86 | 0.35 | 2,602,009 | 0.057 | 0.101 | 0.637 |
Nordex | 140 | 5.76 | 11.58 | 1.74 | 8,185,010 | 0.057 | 0.088 | 0.606 |
Sinovel | 140 | 5.76 | 12.19 | 1.54 | 6,492,396 | 0.057 | 0.089 | 0.609 |
Vestas110 | 140 | 5.76 | 12.2 | 1.69 | 5,703,519 | 0.057 | 0.088 | 0.606 |
Vestas112 | 140 | 5.76 | 17.22 | 0.36 | 6,315,349 | 0.057 | 0.098 | 0.630 |
Windtec | 130 | 5.70 | 14.95 | 3.52 | 7,959,208 | 0.052 | 0.072 | 0.581 |
Turbine | TOPSIS | WSM | FL | GP | Total Score | Total Score (Scaled) | ||||
---|---|---|---|---|---|---|---|---|---|---|
Score | W(t) | Score | Score | Dev(t) | Score | |||||
Acciona | 0.429 | 1 | 0.40 | 2 | 0.26 | 1 | 8,994,208.4 | 1 | 5 | 1 |
Alstom | 0.591 | 14 | 0.52 | 8 | 0.51 | 10 | 3,904,605.7 | 9 | 41 | 11 |
DeWind | 0.564 | 11 | 0.32 | 1 | 0.28 | 2 | 6,187,714.8 | 3 | 17 | 2 |
Dongfang | 0.56 | 7 | 0.63 | 13 | 0.68 | 15 | 2,697,263.2 | 11 | 46 | 14 |
Doosan | 0.559 | 5 | 0.42 | 4 | 0.45 | 6 | 4,910,796.4 | 7 | 22 | 5 |
EnerconE2 | 0.554 | 3 | 0.52 | 9 | 0.50 | 9 | 5,950,923.9 | 4 | 25 | 6 |
EnerconE4 | 0.606 | 15 | 0.42 | 3 | 0.43 | 4 | 5,920,422.3 | 5 | 27 | 7 |
Gamesa | 0.569 | 13 | 0.49 | 7 | 0.47 | 8 | 4,688,631.6 | 8 | 36 | 9 |
Hanjin | 0.555 | 4 | 0.48 | 6 | 0.44 | 5 | 5,316,740.7 | 6 | 21 | 4 |
Leitwind | 0.564 | 10 | 0.47 | 5 | 0.41 | 3 | 7,887,874.5 | 2 | 20 | 3 |
Nordex | 0.544 | 2 | 0.63 | 14 | 0.58 | 13 | 112,063.6 | 14 | 43 | 12 |
Sinovel | 0.561 | 8 | 0.60 | 12 | 0.54 | 12 | 2,194,080.7 | 13 | 45 | 13 |
Vestas112 | 0.562 | 9 | 0.53 | 10 | 0.46 | 7 | 3,556,428.4 | 10 | 36 | 8 |
Vestas110 | 0.56 | 6 | 0.58 | 11 | 0.51 | 11 | 2,538,143.2 | 12 | 40 | 10 |
Windtec | 0.569 | 12 | 0.74 | 15 | 0.65 | 14 | 89.7 | 15 | 56 | 15 |
Turbine | TOPSIS | WSM | FL | GP | Total Score | Total Score (Scaled) | ||||
---|---|---|---|---|---|---|---|---|---|---|
Score | W(t) | Score | Score | Dev(t) | Score | |||||
Acciona | 0.656 | 13 | 0.35 | 2 | 0.29 | 2 | 5,717,531.6 | 1 | 18 | 2 |
Alstom | 0.681 | 14 | 0.53 | 12 | 0.50 | 11 | 2,919,222.4 | 9 | 46 | 15 |
DeWind | 0.64 | 11 | 0.30 | 1 | 0.25 | 1 | 4,661,493.7 | 3 | 16 | 1 |
Dongfang | 0.566 | 1 | 0.62 | 15 | 0.65 | 15 | 2,020,562.4 | 11 | 42 | 12 |
Doosan | 0.632 | 9 | 0.40 | 6 | 0.41 | 6 | 3,716,849.9 | 7 | 28 | 6 |
EnerconE2 | 0.63 | 7 | 0.51 | 11 | 0.46 | 9 | 4,326,071.8 | 5 | 32 | 8 |
EnerconE4 | 0.717 | 15 | 0.40 | 7 | 0.40 | 4 | 4,336,680.2 | 4 | 30 | 7 |
Gamesa | 0.649 | 12 | 0.44 | 8 | 0.44 | 8 | 3,379,247.7 | 8 | 36 | 10 |
Hanjin | 0.632 | 8 | 0.40 | 5 | 0.41 | 5 | 3757429.0 | 6 | 24 | 4 |
Leitwind | 0.637 | 10 | 0.39 | 4 | 0.36 | 3 | 5,583,023.8 | 2 | 19 | 3 |
Nordex | 0.606 | 4 | 0.56 | 13 | 0.59 | 13 | 25.2 | 15 | 45 | 14 |
Sinovel | 0.609 | 5 | 0.51 | 10 | 0.52 | 12 | 1,692,640.0 | 13 | 40 | 11 |
Vestas112 | 0.63 | 6 | 0.38 | 3 | 0.43 | 7 | 2,481,516.8 | 10 | 26 | 5 |
Vestas110 | 0.606 | 3 | 0.50 | 9 | 0.49 | 10 | 1,869,693.2 | 12 | 34 | 9 |
Windtec | 0.581 | 2 | 0.60 | 14 | 0.62 | 14 | 225,818.8 | 14 | 44 | 13 |
Turbine | TOPSIS | Combined | Observation | ||
---|---|---|---|---|---|
Rank Turaif | Rank Wejh | Rank Turaif | Rank Wejh | ||
Acciona AW70/1500 ClassI | Second | First | Second | First | No difference |
Alstom ECO 100/2000 ClassI | Equal | Equal | Second | First | Different |
DeWind D92 | Equal | Equal | First | Second | Different |
Dongfang DF110-2500 | First | Second | First | Second | No difference |
Doosan WinDS 3000 | Second | First | Second | First | No difference |
Enercon E-82E2/2000 | Second | First | Second | First | No difference |
Enercon E-82E4/3000 | Equal | Equal | Equal | Equal | No difference |
Gamesa G97-2.0MW | First | Second | Second | First | Different |
Hanjin HJWT2000-93 | Second | First | Equal | Equal | Different |
Leitwind LTW70-2000 | Equal | Equal | Equal | Equal | No difference |
Nordex N131/3000 | Second | First | Second | First | No difference |
Sinovel SL3000/115 | First | Second | First | Second | No difference |
Vestas 112-3.0MW | First | Second | First | Second | No difference |
Vestas V110-2.0MW | First | Second | First | Second | No difference |
Windtec FC3000-130 | First | Second | First | Second | No difference |
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Rehman, S.; Khan, S.A.; Alhems, L.M. Application of TOPSIS Approach to Multi-Criteria Selection of Wind Turbines for On-Shore Sites. Appl. Sci. 2020, 10, 7595. https://doi.org/10.3390/app10217595
Rehman S, Khan SA, Alhems LM. Application of TOPSIS Approach to Multi-Criteria Selection of Wind Turbines for On-Shore Sites. Applied Sciences. 2020; 10(21):7595. https://doi.org/10.3390/app10217595
Chicago/Turabian StyleRehman, Shafiqur, Salman A. Khan, and Luai M. Alhems. 2020. "Application of TOPSIS Approach to Multi-Criteria Selection of Wind Turbines for On-Shore Sites" Applied Sciences 10, no. 21: 7595. https://doi.org/10.3390/app10217595
APA StyleRehman, S., Khan, S. A., & Alhems, L. M. (2020). Application of TOPSIS Approach to Multi-Criteria Selection of Wind Turbines for On-Shore Sites. Applied Sciences, 10(21), 7595. https://doi.org/10.3390/app10217595