# 160

Dear Mahammad Nuriyev, Aziz Nuriyev, and Jeyhun Mammadov

I read your paper:

Renewable Energy Transition Task Solution for the Oil Countries Using Scenario-Driven Fuzzy Multiple-Criteria Decision-Making Models: The Case of Azerbaijan

My comments:

1- I agree with you in a 100% when you speak of an ambivalent situation: On one side you depend of oil because it is your main export, and on the other, you are constrained because the universal policy of complete decarbonization from oil, which with no doubt will hurt your country economy.

2- In page 2 you say “The transition to a renewable-based energy system is not a one-step process, especially for countries with a high share of oil and gas in their GDP”.

You are right and it is not either a short one. I am working in energy transition and reckon that the zero decarbonization of electricity generation takes many steps and decades. The objective of having zero CO2by 2050 is, is in may humble opinion, an illusion in most countries that will benefit economically by no importing oil, but in your country is worse. There is not a dichotomy here, because it is not a 1 to 0 game, but in reaching gradually that condition, i.e., achieving an equilibrium.

For instance, in my research I propose a long-term plan to be executed in periods, lasting five or six-years each, until 2050, to reach an acceptable compromise, because in those 26 years period, oil contaminated plants must be shutdown, but at the same time being replaced by new technologies, that are not built overnight. Therefore, oil will be continued in use still for years to come.

In your case, you would need not only to build renewable energy plants, but also, to find another uses for your oil. My wrighting follows he same pace as reading your paper, and for that reason, later on, reading the whole paper several pages from here, I learned that you also have gas, and that is a big difference.

Needless to say, I agree with what you say regarding MCDM, however, I do not think that fuzzy can help on this. This scenario is not a matter of using exact numbers but in following right procedures and policies. It is not a matter of only mathematics, but rather involving in a very large extent government, exports, environment, developing of products oil based like plastics, hydrogen, fertilizers, etc.

3- In page 4 you refer to SAW as a fuzzy method. Not in my opinion. If you refer to the fact that weights are needed, and I agree, the problem is to determine how these weights are generated. If you are talking about subjective weights, have you wondered what is the purpose of using fuzzy logic on invented weights, that can change if another DM computes them? Don’t you think weird that the solution of a problem may be valid, ONLY considering what a group of people decide?

Of course, fuzzy can be used to find average values and determining DM coherence in crisp values, and have near transitivity or ‘consistency’. And what is that good for, if there is no guarantee that results can be applied to a problem in the real world? Because, as far as I know there is not a mathematical axiom or theorem that supports that assumption. Convenient of course, but also false

4- Page 4 “The above-mentioned papers demonstrate the effectiveness of the fuzzy approach in formalizing uncertainty in decision making within the energy sector”

Could you please inform the reader how that demonstration could prove effectiveness if you do not have any yardstick to compare?

5- Page 5 “Expert evaluation of the importance of weights and each alternative with respect to each criterion”

Weights are useless to evaluate alternatives, since even if for a criterion you multiply each performance value by the criterion weight, it affects all values equally, i.e., the proportion or distances between performance values does not change with the multiplication. It only provokes that the corresponding criterion line displaces parallel to itself.

6- Since you are using experts estimates it does not make sense to use fuzzy, because you are certainly decreasing uncertainty, but on the subjective opinion of a DM or a group of them. There is no mathematical support for this, although it is extensively used. What if another group thinks differently, which group will you choose? This is an over simplification of the problem, not by you, but by 99 % of MCDM methods. Why this happens? Because many people believe that a MCDM method consists in filling a matrix, without analysing the sequence and reason of each step. Since there is no way to know the reality, any result is accepted and heralded as a success. Who is going to check? Not the reviewers certainly.

7- Page 11 “Rising domestic and foreign demand for electricity will be offset by renewables. There are significant differences in the capacity of the available renewables in the country”

Are you sure? How will you replace an oil-fired power plant generating say 600 MWh, and working 24/7 with renewables, especially solar and wind, that can only work a couple of hours per day, and assuming that there is wind and enough solar irradiation? As you can see the problem is not that simple, and regarding hydro, assuming that river flows are constant.

8- In page 11 you detail the eight criteria and I think that it is a very good set, although incomplete. For instance, in my opinion, you should add ‘Job generation’, ‘Land use’, ‘Site selection’, ‘Necessary investment’, ‘Return’, etc

.

9- As a final result you say that A7 is the best, followed by A9. Obviously, the main actor in both is gas, which in my opinion is quasi mandatory, but this result is lacking realism because:

First: You use different MCDM methods, compare their results, which is useless, since you do not have a yardstick for comparison, and in any case, you get a set of solutions instead of only one.

Second: In all methods a criterion is considered in isolation, when all criteria should be taken into account and simultaneously This is another false procedure used by 99 % of MCDM methods. Why do I say this?

Because all criteria and alternatives constitute a system, and as that, normally all of them are interrelated. For instance, you cannot consider cost per se, because any increase or decrease may affect say resources; as an example, a decrease in capital investment may reduce the availability of resources for education, and at the same time, increase noxious emissions.

This multi cross analysis cannot be made my hand, but only by an adequate MCDM method

Third: In addition, since all criteria are direct or indirectly related, you cannot use AHP to compute weights because this method works only under the condition that criteria are independent. By the way, and explained by Saaty himself, AHP should no be uses with fuzzy as in FAHP, because it is already fuzzy.

These are my comments, and I hope they can help

Nolberto Munier