# 223

Dear Khashayar Lak, Arash Haghparast Kashani, Amir Azizi, Naser Karimi, Morteza Hosseinpour

I read your paper:

Application of simultaneous evaluation of criteria and alternatives for prioritization of photovoltaic power plant location

My comments:

1- In the abstract: “Hence, a recently developed multi-criteria decision-making technique tool is proposed for simultaneous evaluation of criteria and alternatives (SECA)to find an optimal site for establishing photovoltaic power stations in Iran”

Normally the criteria weights are determined in most methods once the alternatives have been defined. Alternatives may have weights but, in most cases, they are affected by coefficients and what you got at the end of the evaluation process, are the alternatives scores, not weights

There are not optimal sites in MCDM methods, only a balance or compromise. You cannot maximize benefits and at the same time minimize costs, it bis one or the other, or find a balance

2- Page 2 “According to Dominguez, as the construction of solar farms increases, its waste is also expected to increase”

This is very true but surprisingly almost never mentioned in other similar papers

3- “In this article, for the first time, the potential of building renewable energy power plants has been measured from environmental and economic perspectives”

I am surprised for your assertion since from long time these facts are being considered by most MCDM methods

4- “In this article, using a multi-criteria combined decision-making method based on the neutrosophic environment, indicators related to technical, economic, environmental, socio-political, and their risks are analysed and prioritized using the Delphi technique”

The Delphi technique is biased. It is also ambiguous because it is not defined what is consensus. It guides the different participants to think in a particular way by iterative feedback

5- “SWOT analysis was applied for the determination of optimal renewable energy growth strategies in Khalid Almatairi et al”

SWOT is not designed to determine the optimal growth strategies. It delivers a set of reasoned strategies. To determine the best, not the optimal, you need MCDM

6- Page 4 “as a new decision-making tool shows that many fields will benefit from this scheme”

Sorry, I do not think that it shows that

“The temperature of the modules, which is influenced by the surrounding temperature, wind velocity, and direction of the wind, affects the extracted power of the panels as well”

Very true, but it appears that you forget that one of the solar irradiations, the infrared, can reach the cells, heats them and reduces output. IR can reach cells even in cloudy days more easily than light

7- “In order to build a 1 MW photo voltaic, power plant, five criteria—annual humidity, radiation, temperature, cloud cover, and height above sea level—haven researched and compared”

In my opinion, 5 criteria are not even close to the number of criteria you need

8- “This method’s capability to integrate qualitative and quantitative data ensures a comprehensive evaluation, reducing subjectivity”

Did you know that this mix has being done during decades? And it is not related to decreasing subjectivity

9- “Furthermore, SECA’s efficiency and adaptability to complex, interdependent criteria make it particularly suited for the solar energy sector, offering a more streamlined and objective decision-making process”

I have not seen yet that all these attributes apply to your method. What you describe is only a collection of words, that can refer to anything and said nothing to the reader

10- “Compared to other MCDM methods like TOPSIS and PROMETHEESECA avoids predefined ideals or detailed preference extraction, providing a flexible framework that better accommodates the multifaceted nature of solar energy decisions”

This is a bold assertion that you did not sustain with proofs. Both mentioned methods are rational, they do not work with assumptions but with facts. It is also the first time I see an author that glorifies his method without any proof and projects solved, as PROMETHEE and TOPSIS do

11- “The SECA method aims to rank the options of study. In this method, unlike other methods, both the criteria weight and the ranking of the options are done simultaneously”

As far as I know this is inexact. Normally, methods like PROMETHEE, TOPSIS, ELECTRE, VIKOR, etc. select the alternatives and after that aims at weighting the criteria. Unless you decide front, which alternative is better than another or preferable, you need alternatives in order to define criteria, not the opposite.

You cannot choose the factors out of the dark because one criterion may apply to some alternatives and not to another. I is like saying that you use the same set of criteria to evaluate a hospital performance when you also have to evaluate government policies for export

12- “With the increase of diversity in criterion and the degree j of difference between criterion j and other criteria j, the importance (weight) of the criterion will increase”

To increase diversity in a criterion you must change somoe of the inner values of said criterion, and then increasing or decreasing dispersion (Shannon Theorem), of course, this not related with its weight. Most probable there will be a change in the difference with another criterion, but this is not related to the weights that only measure the subjective importance given to a criterion. Therefore, I would be interested and possible readers too, to know where you extract that conclusion from. On that base you build your mathematical development, so, I suggest to think about what you are comparing, and use math after you proved it.

13- “These datasets, when integrated and adjusted for resolution matching and bias correction, offer unparalleled insights into solar potential and environmental, conditions, crucial for the application of the SECA method and, MCDM approaches in solar energy projects”

Your opinion

14- “This paper selected ten cities from the situation of Iran with different weather conditions in different meteorological climates chosen under the SECA method. These cities include Shahrekord, Zahedan, Yazd, Kerman, Isfahan, Semnan, Bandar. Abbas, Urmia, Ahvaz and Bojnord

Your method chose Kerman? Have as look of what AI says about this

“ Kerman, Iran receives very high levels of infrared (IR) radiation, especially during the summer months. While exact IR measurements aren’t typically listed in public weather reports, we can infer IR intensity based on related indicators like temperature, sunshine duration, and UV index:

📈 Extreme UV Index Kerman regularly hits a UV index of 11–12, which is classified as extreme. Since UV and IR are both components of solar radiation, high UV levels usually correlate with strong IR exposure.

🌡️ High Surface Temperatures Daytime temperatures in July often exceed 40°C, and surfaces like buildings and roads can absorb and re-radiate IR, intensifying heat effects.

☀️ Long Sunshine Hours Kerman enjoys 13–14 hours of sunshine per day in summer, allowing sustained IR radiation to reach the ground with minimal atmospheric interference.

🌵 Desert Climate Advantage Its dry, clear-sky conditions—especially near the Lut Desert—mean low humidity and minimal cloud cover, which allows IR to penetrate efficiently and accumulate at the surface.

So while we don’t have a direct IR watt-per-square-meter figure, all signs point to intense IR radiation in Kerman, making it a hotspot for solar energy—and a challenge for thermal comfort”

Therefore, it seems that the very high UV and IR radiation were not considered

These are my comments. I hope they can help

Nolberto Munier