© 2023 IIETA. This article is published by IIETA and is licensed under the CC BY 4.0 license (http://creativecommons.org/licenses/by/4.0/).
OPEN ACCESS
This article is the second of the author’s works devoted to a comprehensive study of the economic efficiency of Russian renewable energy (RE) projects. The main goal of this paper is to study the level of influence of political risk on the economic efficiency of RE projects that are implemented in the Russian energy market using a state support program. Fifty-two solar, wind and small hydropower projects, which have received support in the form of a capacity-based support scheme in 2018-2020, were selected as objects of research. The methodological basis of the work was the classical methods of investment analysis and specific industry approach. They were supplemented with the author’s tool for calculating the monetary equivalent of political risk that takes into account the probability of the termination of support from the state. The practice-based assessment utilized the developed scenarios depending on changes in foreign and domestic international credit ratings of the country. The study of the impact of political risk for three stages of RE projects was carried out. Based on the results of the analysis, conclusions were drawn about generally insignificant influence of political risk on the economic efficiency of Russian RE projects. Recommendations for the development of state support programs in the event of the impact of political risks only were generated. The obtained research results are of practical and methodological value. It will be used in studying the impact of other specific risks on the effectiveness of Russian RE projects, as well as in developing recommendations enabling the Russian RE market to give up state support.
capacity-based support scheme, economic efficiency, energy, hydroelectric power, political risk, renewable energy, Russian energy market, solar power, state support, wind power
Risks caused by political factors have a huge impact on the effectiveness of renewable energy (RE) projects and their value in particular. According to references [1-7], political risk in RE projects usually includes the following:
In this paper, political risk is viewed as caused by the provision of state support to Russian RE projects in the form of preferentially priced capacity contracts for the wholesale market (CPS RES) [1] and is associated with the probability of its complete termination or limitation of volumes. The peculiarity of this program consists in conducting competitive selection of projects for the construction of generating facilities operating on the basis of RE, and the signing of 15-year CPS RES for selected projects [8, 9].
The main objective of this work is to study the degree of the influence of political risk on the economic efficiency of Russian RE projects in various scenario conditions during the 15-year term of the CPS RES program. In addition, the task is to systematize methodological recommendations on political risk management within the framework of state support pro- grams for the sector.
The article has the following structure. The second section presents a methodology for assessing the economic efficiency of RE projects based on classical and industry-specific tools; the author proposes an approach to assessing the value of political risk of RE projects based on rating assessment. The initial assessment of the impact of political risk on the effectiveness of projects and the relevant conclusions are presented in the third paragraph. The fourth section contains the main results of the scenario pre-default assessment of the impact of political risk on RE projects. In the conclusions part, the main results of the work are summarized, reasonable conclusions are made about the overall insignificance of the impact of political risk on the economic efficiency of the sector’s projects, and directions for adjusting the support programs for RE projects by their types are proposed.
This paragraph provides the description of classical (section 2.1) and industry-specific (section 2.2) approaches used in the process of assessing the economic efficiency of Russian projects. Section 2.3 contains the tools suggested by the author for assessing the value of political risk for the RE projects.
2.1 Evaluation of the economic efficiency of projects
The general methodology for assessing the economic efficiency of projects is based on the calculation of generally accepted criteria: Net Present Value (NPV), Internal Rate of Return, and Discounted Payback Period [10-13].
The cash flow for RE projects takes into account the following components [14, 15]:
The discount rate is calculated according to the Irving Fisher formula [16], taking into account the following assumptions:
2.2 Calculation of revenue (price) for capacity
The industry-specific approaches to evaluating the effectiveness of Russian projects are related to the calculation of the actual value of the revenue generated by the facility from the sale of capacity in the energy market during the 15-year term of the CPS RES. This indicator is calculated annually and individually for each project.
The rules for determining the price for the capacity of generating facilities operating on the basis of RES are regulated by the Decree of the Russian Government N449 [14]. This paper applies the methodology adopted for projects selected before 1 January 2021.
The price for the capacity of a generating facility is determined as the multiplication of the share of costs compensated by the capacity fee and the total costs, including: (1) capital expenditures, (2) operational expenditures, and (3) property tax costs [14, 15]. The method- ology for calculating the price for capacity under the CPS RES program is presented in more detail in the author’s article [15].
2.3 Assessment of the political risk value
To assess the value of political risk, the author suggested the following hypothesis. The more stable the state’s position in the domestic and international arenas, the less likely it is to face financial and other difficulties, in other words, the lower the probability of default. Under such conditions, the implementation of various state programs, including support for RE projects, is more stable, and the political risk is minimal [2, 3].
To assess the declared degree of stability of the state’s position, it is proposed to use a rating approach - the average value of national credit ratings assigned to the state by domes- tic and foreign rating agencies. The averaging of assigned ratings is used to ensure the degree of objectivity of such a qualitative assessment method. The probability of political risk, i.e., the probability of a default by the state and the impossibility of providing state support to sector projects corresponds to the probability of a default on the received rating, taking into account the number of years from the date of rating assignment.
The monetary equivalent of political risk in each period ‘i’ is calculated by the Eq (1):
PRi=PDi∙RCi, (1)
where, PRiis political risk; PDiis probability of default; RCiis the amount of state support; period i is the year of project implementation, i=0, …, 14, period ‘0’ is the year of launching the construction of the RE facility.
The amount of state support in each period is equal to the revenue received by the facility from the sale of capacity in the energy market in accordance with the CPS RES. Political risk is only taken into account during the first 15 years of the implementation of RE projects when state support is provided.
3.1 Brief description of RE projects
For the period 2018-2020, 52 RE projects were competitively selected and approved for implementation [18], including: 34 wind power plants (WPP), 11 solar power plants (SPP), and 7 small hydroelectric power plants (SHPP). Their brief characteristics are presented in Table 1 of the article [15]. The results of the evaluation of the economic efficiency of these projects are quantitatively presented in Table 2 [15], the main conclusions - in the fourth paragraph of the work [15].
Table 1. The comparison of the international scales of four rating agencies
ACRA |
S&P |
Fitch |
Moody’s |
… |
… |
… |
… |
A |
A |
A |
A |
BBB |
BBB |
BBB |
Baa |
BB |
BBB- |
BB |
|
B |
BB+ |
B |
Ba |
CCC |
BB |
|
B |
CC |
B, CCC |
CCC |
Caa |
C |
CC |
CC, C |
Ca |
RD |
- |
- |
|
… |
… |
… |
… |
3.2 Assessment of the value of political risk
For the primary calculation of the value of political risk, the national ratings assigned to Russia by leading Russian and foreign rating agencies were used. Initial calculations were carried out at the beginning of December 2021. Among the Russian rating agencies accredited by the Bank of Russia, the rating assigned by the Analytical Credit Rating Agency (ACRA) is taken into account. Other domestic rating agencies are not included in this sample as they do not establish a national credit rating. Therefore, the national rating assigned to Russia by the ACRA agency at the level of ‘A’ on the international scale will be used as initial data; the forecast is ‘stable’ [19]. International rating agencies include Standard & Poor’s Global Ratings (S&P), Fitch Ratings and Moody’s, which cover 95% of the global market [20]. The ratings assigned to Russia on the international scale as of December 2021 are as follows: S&P: ‘BBB-’, Fitch: ‘BBB’; and Moody’s: ‘Baa3’, all ratings had ‘stable’ forecast.
A ‘stable’ forecast means that the assigned rating will not change with a high degree of probability. Therefore, for the purposes of testing the approach, it is conditionally assumed that the assigned ratings will not change significantly during the 15-year period.
To estimate the average probability of a default, the international scales of four rating agencies are compared in Table 1 [21-24].
As a result, the average value of ratings assigned to Russia on the international scale is ‘BBB’. The distribution of the probability of a default by a state with a ‘BBB’ rating in accordance with the calculations of the S&P agency [21] and the forecast compiled for a 15-year period is presented in Table 2.
To study the impact of the value of political risk on the economic efficiency of RE projects, the author suggested calculating economic efficiency indicators in the following three stages. The first stage is the decision on the implementation of the project (zero project period). The second stage is before the commissioning of the facility. The third stage is during the 15-year period of the facility operation.
Table 2. Probability of default with a ‘BBB’ rating by period, %
Number of years from the date of receiving the rating (fact by rating) |
Forecast |
|||||||||||||
1 |
2 |
3 |
4 |
5 |
6 |
7 |
8 |
9 |
10 |
11 |
12 |
13 |
14 |
15 |
0,21 |
0,6 |
1,02 |
1,53 |
2,06 |
2,56 |
3,01 |
3,45 |
3,89 |
4,33 |
4,96 |
5,52 |
6,09 |
6,69 |
7,3 |
It should be noted that the fourth stage of the project, lasting up to the full planned life, is not taken into account in this study, since the period of the CPS RES program, and, consequently, the influence of political risk ceases at the end of the third stage.
Then the distribution of the value of political risk calculated according to the Eq. (1) and the indicators of economic efficiency (initial NPV and NPV taking into account risk) by stages are presented in Tables 3-5. Calculations show that the dynamics of changes in the value of political risk in all projects for all types of RE are similar: a gradual increase in the value of risk by the end of the CPS RES program. This is naturally due to a gradual increase in the probability of termination of state support closer to the completion of the CPS RES (Table 2) and the absolute value of support for the project in the form of capacity revenue.
3.3 The impact of the value of political risk on the effectiveness of projects (‘BBB’ rating)
Calculations shown that the value of political risk at the level of the ‘BBB’ rating do not significantly affect the economic efficiency of Russian RE projects.
Table 3. The value of political risk and NPV in wind energy projects (‘BBB’ rating)
Project |
Indicators, thousand rubles |
First stage |
Second stage |
Third stage |
Fourth stage |
The stage of positive effect |
Project |
First stage |
Second stage |
Third stage |
Fourth stage |
The stage of positive effect |
Experi- |
NPV (initial) |
-387778 |
-1083562 |
142046 |
522938 |
3 |
WPP |
-481870 |
-1346377 |
26209,90 |
551809 |
3 |
mental |
NPV (risk) |
-387874 |
-1084015 |
134648 |
522938 |
3 |
Wind- |
-482036 |
-1347167 |
13614,34 |
551809 |
3 |
WPP-121 |
Value of risk |
95,66 |
453,14 |
7397,60 |
- |
|
Farm-38 |
165,65 |
790,51 |
12595,56 |
- |
|
Experi- |
NPV (initial) |
-291057 |
-813296 |
107087 |
393371 |
3 |
WPP |
-481870 |
-1346377 |
-3111,15 |
504198 |
4 |
mental |
NPV (risk) |
-291129 |
-813636 |
101538 |
393371 |
3 |
Wind- |
-482036 |
-1347167 |
-15706 |
504198 |
4 |
WPP-127 |
Value of risk |
71,80 |
340,12 |
5549,52 |
- |
|
Farm-48 |
165,65 |
790,51 |
12595,56 |
- |
|
Experi- |
NPV (initial) |
-775557 |
-2167124 |
284092 |
1045876 |
3 |
WPP |
-481870 |
-1346377 |
-3111,15 |
504198 |
4 |
mental |
NPV (risk) |
-775749 |
-2168030 |
269297 |
1045876 |
3 |
Wind- |
-482036 |
-1347167 |
-15706 |
504198 |
4 |
WPP-130 |
Value of risk |
191,33 |
906,28 |
14795,1 |
- |
|
Farm-49 |
165,65 |
790,51 |
12595,56 |
- |
|
Experi- |
NPV (initial) |
-436251 |
-1219007 |
159973 |
588579 |
3 |
Experi- |
-399707 |
-1346784 |
-293682 |
44928,9 |
4 |
mental |
NPV (risk) |
-436358 |
-1219517 |
151651 |
588579 |
3 |
mental |
-399844 |
-1348393 |
-301558 |
44928 |
4 |
WPP-128 |
Value of risk |
107,62 |
509,78 |
8322,29 |
- |
|
WPP-52 |
137,41 |
1609,23 |
7876,14 |
- |
|
Experi- |
NPV (initial) |
-387778 |
-1083562 |
142046 |
522938 |
3 |
WPP |
-320514 |
-1396471 |
-284221 |
190902 |
4 |
mental |
NPV (risk) |
-387874 |
-1084015 |
134648 |
522938 |
3 |
Wind- |
-320695 |
-1398140 |
-297383 |
190902 |
4 |
WPP-125 |
Value of risk |
95,66 |
453,14 |
7397,60 |
- |
|
Farm-61 |
180,31 |
1668,60 |
13162,82 |
- |
|
Experi- |
NPV (initial) |
-775557 |
-2167124 |
284092 |
1045876 |
3 |
WPP |
-340643 |
-1484170 |
-390705 |
73407 |
4 |
mental |
NPV (risk) |
-775749 |
-2168030 |
269297 |
1045876 |
3 |
Wind- |
-340835 |
-1485944 |
-403940 |
73407 |
4 |
WPP-129 |
Value of risk |
191,33 |
906,28 |
14795,1 |
- |
|
Farm-59 |
191,63 |
1773,39 |
13235,15 |
- |
|
Experi- |
NPV (initial) |
-1058009 |
-2041520 |
345201 |
1011803 |
3 |
WPP |
-340643 |
-1484170 |
-390705 |
73407 |
4 |
mental |
NPV (risk) |
-1058176 |
-2041990 |
332327 |
1011803 |
3 |
Wind- |
-340835 |
-1485944 |
-403940 |
73407 |
4 |
WPP-131 |
Value of risk |
166,93 |
470,01 |
12874 |
- |
|
Farm-60 |
191,63 |
1773,39 |
13235,15 |
- |
|
Project |
Indicators, thousand rubles |
First stage |
Second stage |
Third stage |
Fourth stage |
The stage of positive effect |
Project |
First stage |
Second stage |
Third stage |
Fourth stage |
The stage of positive effect |
Stavropol |
NPV (initial) |
-761640 |
-3310612 |
-86903 |
1153968 |
4 |
WPP |
-340643 |
-1484170 |
-390705 |
73407 |
4 |
WPP-24 |
NPV (risk) |
-761981 |
-3313834 |
-112233 |
1153968 |
4 |
Wind- |
-340835 |
-1485944 |
-403940 |
73407 |
4 |
|
Value of risk |
341,70 |
3222,47 |
25329 |
- |
|
Farm-57 |
191,63 |
1773,39 |
13235,15 |
- |
|
WPP |
NPV (initial) |
-709495 |
-709495 |
-128632 |
163546 |
4 |
WPP |
-340643 |
-1484170 |
-390705 |
73407 |
4 |
Wind- |
NPV (risk) |
-709607 |
-709607 |
-135576 |
163546 |
4 |
Wind- |
-340835 |
-1485944 |
-403940 |
73407 |
4 |
Farm-35 |
Value of risk |
112,15 |
112,15 |
6944,36 |
- |
|
Farm-58 |
191,63 |
1773,39 |
13235,15 |
- |
|
WPP |
NPV (initial) |
-859865 |
-859865 |
-166725 |
183849 |
4 |
WPP |
-309110 |
-1346784 |
-187937 |
334160 |
4 |
Wind- |
NPV (risk) |
-860001 |
-860001 |
-175090 |
183849 |
4 |
Wind- |
-309284 |
-1348393 |
-200739 |
334160 |
4 |
arm-34 |
Value of risk |
135,91 |
135,91 |
8364,77 |
- |
|
Farm-52 |
173,89 |
1609,23 |
12802,51 |
- |
|
WPP |
NPV (initial) |
-717446 |
-717446 |
-140167 |
152011 |
4 |
WPP |
-312598 |
-1361981 |
-202246 |
319851 |
4 |
Wind- |
NPV (risk) |
-717560 |
-717560 |
-147141 |
152011 |
4 |
Wind- |
-312774 |
-1363609 |
-215096 |
319851 |
4 |
Farm-36 |
Value of risk |
113,40 |
113,40 |
6973,96 |
- |
|
Farm-51 |
175,85 |
1627,39 |
12850,37 |
- |
|
WPP |
NPV (initial) |
-712180 |
-712180 |
-187477 |
76727 |
4 |
WPP |
-317472 |
-1383216 |
-119904 |
475133 |
4 |
Wind- |
NPV (risk) |
-712293 |
-712293 |
-194431 |
76727 |
4 |
Wind- |
-317651 |
-1384869 |
-133025 |
475133 |
4 |
Farm-31 |
Value of risk |
112,57 |
112,57 |
6954,36 |
- |
|
Farm-71 |
178,60 |
1652,76 |
13121,08 |
- |
|
WPP |
NPV (initial) |
-717411 |
-717411 |
-195064 |
69140 |
4 |
WPP |
-317493 |
-1383305 |
-181530 |
364904 |
4 |
Wind- |
NPV (risk) |
-717524 |
-717524 |
-202038 |
69140 |
4 |
Wind- |
-317671 |
-1384958 |
-194651 |
364904 |
4 |
Farm-32 |
Value of risk |
113,40 |
113,40 |
6973,83 |
- |
|
Farm-74 |
178,61 |
1652,87 |
13121,36 |
- |
|
Experi- |
NPV (initial) |
-608806 |
-608806 |
-378672 |
-209366 |
N/A* |
WPP |
-348753 |
-1519508 |
-309763 |
236671 |
4 |
mental |
NPV (risk) |
-608902 |
-608902 |
-383203 |
-209366 |
N/A |
Wind- |
-348950 |
-1521323 |
-323313 |
236671 |
4 |
WPP-67 |
Value of risk |
96,23 |
96,23 |
4531,13 |
- |
|
Farm-75 |
196,19 |
1815,61 |
13550,27 |
- |
|
Project |
Indicators, thousand rubles |
First stage |
Second stage |
Third stage |
Fourth stage |
The stage of positive effect |
Project |
First stage |
Second stage |
Third stage |
Fourth stage |
The stage of positive effect |
WPP |
NPV (initial) |
-481870 |
-1346377 |
115420 |
696670 |
3 |
WPP |
-348753 |
-1519508 |
-181130 |
466893 |
4 |
Wind- |
NPV (risk) |
-482036 |
-1347167 |
102825 |
696670 |
3 |
Wind- |
-348950 |
-1521323 |
-194680 |
466893 |
4 |
Farm-41 |
Value of risk |
165,65 |
790,51 |
12595,5 |
- |
|
Farm-78 |
196,19 |
1815,61 |
13550,27 |
- |
|
WPP |
NPV (initial) |
-481870 |
-1346377 |
115420 |
696670 |
3 |
WPP |
-348753 |
-1519508 |
-344065 |
175279 |
4 |
Wind- |
NPV (risk) |
-482036 |
-1347167 |
102825 |
696670 |
3 |
Wind- |
-348950 |
-1521323 |
-357615 |
175279 |
4 |
Farm-42 |
Value of risk |
165,65 |
790,51 |
12595, |
- |
|
Farm-82 |
196,19 |
1815,61 |
13550,27 |
- |
|
WPP |
NPV (initial) |
-481870 |
-1346377 |
26209 |
551809 |
3 |
WPP |
-360179 |
-1569290 |
-390934 |
128410 |
4 |
Wind- |
NPV (risk) |
-482036 |
-1347167 |
13614 |
551809 |
3 |
Wind- |
-360382 |
-1571165 |
-404641 |
128410 |
4 |
Farm-37 |
Value of risk |
165,65 |
790,51 |
12595,5 |
- |
|
Farm-83 |
202,62 |
1875,10 |
13707,04 |
- |
|
*N/A - not achieved
Table 4. The value of political risk and NPV in the solar energy projects (‘BBB’ rating)
Project |
Indicators, thousand rubles |
First stage |
Second stage |
Third stage |
Fourth stage |
The stage |
Project |
First stage |
Second stage |
Third stage |
Fourth stage |
The stage |
SPP-2022-1 |
NPV (initial) |
-59903 |
-167431,62 |
107754,27 |
205278,76 |
3 |
Saratov SPP |
-202387 |
-565483 |
43276,93 |
231545,25 |
3 |
|
NPV (risk) |
-59924 |
-167529,34 |
105356,28 |
205278,76 |
3 |
|
-202457,27 |
-565815 |
36688,03 |
231545,25 |
3 |
|
Value of risk |
20,58 |
97,72 |
2397,98 |
- |
|
|
69,58 |
332,02 |
6588,90 |
- |
|
SPP -2018-1 |
NPV (initial) |
-567480 |
-567480,17 |
-343729 |
-228543 |
N/A |
Orenburg SPP |
-223810,72 |
-625341 |
14412,52 |
222025,59 |
3 |
|
NPV (risk) |
-567569 |
-567569,46 |
-349091 |
-228543 |
N/A |
|
-223887,66 |
-625708 |
7644,27 |
222025,59 |
3 |
|
Value of risk |
89,29 |
89,29 |
5361,60 |
- |
|
|
76,94 |
367,16 |
6768,25 |
- |
|
SPP -2018-2 |
NPV (initial) |
-283742 |
-283742,41 |
-171819 |
-114201 |
N/A |
Privolzhskaya |
-225099,71 |
-628942 |
-8541,13 |
187000,81 |
4 |
|
NPV (risk) |
-283787 |
-283787,06 |
-174500 |
-114201 |
N/A |
SPP |
-225177,09 |
-629311 |
-15320,17 |
187000,81 |
4 |
|
Value of risk |
44,65 |
44,65 |
2680,81 |
- |
|
|
77,38 |
369,28 |
6779,04 |
- |
|
SPP -2018-3 |
NPV (initial) |
-1333600 |
-1333600 |
-638654 |
-277332 |
N/A |
Privolzhskaya |
-165020,79 |
-593807 |
60527,27 |
281696,94 |
3 |
|
NPV (risk) |
-1333810 |
-1333810 |
-651254 |
-277332 |
N/A |
SPP -1 |
-165094,80 |
-594333 |
53146,39 |
281696,94 |
3 |
|
Value of risk |
209,84 |
209,84 |
12599,85 |
- |
|
|
74,01 |
525,57 |
7380,89 |
- |
|
Astrakhan |
NPV (initial) |
-228089 |
-637296,43 |
118302,00 |
359864,31 |
3 |
SPP Kalmykia |
-146105,94 |
-525744 |
103212,98 |
334349,26 |
3 |
SPP |
NPV (risk) |
-228167 |
-637670,61 |
110519,02 |
359864,31 |
3 |
|
-146171,47 |
-526210 |
96694,88 |
334349,26 |
3 |
|
Value of risk |
78,41 |
374,18 |
7782,98 |
- |
|
|
65,53 |
465,33 |
6518,10 |
- |
|
Kalmykia |
NPV (initial) |
-200144 |
-559217,24 |
118266,45 |
349402,73 |
3 |
|
|
|
|
|
|
SPP |
NPV (risk) |
-200213 |
-559545,58 |
111696,33 |
349402,73 |
3 |
|
|
|
|
|
|
|
Value of risk |
68,80 |
328,34 |
6570,12 |
- |
|
|
|
|
|
|
|
Table 5. The value of political risk and NPV in the small hydropower projects (‘BBB’ rating)
Project |
Indicators, thousand rubles |
First stage |
Second stage |
Fourth stage |
Third stage |
The stage |
Project |
First stage |
Second stage |
Third stage |
Fourth stage |
The stage |
SHPP -1_1 |
NPV (initial) |
-680624 |
-1900532 |
-1325168 |
-941320,99 |
N/A |
SHPP |
-364133 |
-702406 |
-450768,73 |
-219078 |
N/A |
NPV (risk) |
-680858 |
-1901658 |
-1335420 |
-941320,99 |
N/A |
Prosyanskij |
-364223 |
-702663 |
-454676,41 |
-219078 |
N/A |
|
Value of risk |
233,89 |
1126,46 |
10251,90 |
- |
|
sbros BSK |
90,24 |
256,86 |
3907,68 |
- |
|
|
Bashennaya SHPP |
NPV (initial) |
-416023 |
-1161676 |
-672595 |
-267216,43 |
N/A |
Gorko- |
-468171 |
-903093 |
-579578 |
-281711 |
N/A |
NPV (risk) |
-416166 |
-1162365 |
-678842,91 |
-267216,43 |
N/A |
Balkovskaya |
-468287 |
-903423 |
-584602 |
-281711 |
N/A |
|
Value of risk |
142,96 |
688,54 |
6247,90 |
- |
|
SHPP |
116,02 |
330,24 |
5024,15 |
- |
|
|
SHPP |
NPV (initial) |
-798703 |
-2230249 |
-1398686 |
-751192,96 |
N/A |
Nizhne- |
-544095 |
-2361209 |
-1366997 |
-587684 |
N/A |
Psygansu |
NPV (risk) |
-798978 |
-2231570 |
-1410660 |
-751192,96 |
N/A |
Krasnogor- |
-544402 |
-2364166 |
-1380460 |
-587684 |
N/A |
Value of risk |
274,46 |
1321,89 |
11973,78 |
- |
|
skaya SHPP |
306,36 |
2957,20 |
13463,07 |
- |
|
|
SHPP |
NPV (initial) |
-306125 |
-854860 |
-567852,93 |
-372028,73 |
N/A |
|
|
|
|
|
|
Segozerskaya |
NPV (risk) |
-306230 |
-855367 |
-572611,14 |
-372028,73 |
N/A |
|
|
|
|
|
|
Value of risk |
105,36 |
506,76 |
4758,20 |
- |
|
|
|
|
|
|
|
3.3.1 Wind energy projects
In wind energy projects, the share of political risk in the initial NPV increases from 0.04% and 0.07% in the first and second stages, respectively, to 32% in the third stage. It is by this amount that the NPV, which was calculated taking into account the cost of risk, is reduced (Table 3). However, such an increasing negative impact of political risk does not reduce the current ability of the projects to achieve economic results at the previous stage. As shown in Table 3, all projects retain the initial stage of achieving a positive economic effect.
3.3.2 Solar energy projects
In solar energy projects, the impact of political risk on the NPV indicator is significantly lower compared to wind energy - with a similar value in the first two stages, the average risk share is 16.3% in the third stage (Table 4). The stages of achieving a positive economic result also remained unchanged.
3.3.3 Small hydropower projects
In the presented hydropower projects, the average share of political risk is the lowest among all the studied cases: 0.03%, 0.06%, and 0.87% at each stage, respectively. This is due to higher specific investments in hydropower projects. Nevertheless, the submitted projects are initially economically inefficient (Table 5), and additional consideration of the value of political risk further reduces this indicator.
4.1 Brief description of scenarios
Three scenarios were developed to assess the value of political risk under the influence of a set of rapidly changing external factors. The first scenario - with only the rating assigned to the state by the domestic agency ACRA taken into account - ‘A-’ on an international scale, the forecast is ‘stable’. The second scenario - with only new ratings assigned by foreign agencies [25]: S&P Global Ratings - ‘CC’, ‘negative’ forecast (assigned 18 March 2022); Fitch Ratings - ‘C’, ‘negative’ forecast (assigned 09 March 2022); Moody’s - ‘Ca’, ‘negative’ forecast (assigned 06 March 2022) - taken into account, the average rating is equivalent to ‘CC’ (Table 1). The third scenario - with current ratings assigned by Russian and foreign agencies factored in, the average rating is equal to ‘BB’ (Table 1).
The initial assessment showed that the credit rating at the level of ‘BBB’ does not significantly affect the economic efficiency of RE projects. In this case, it is natural that the estimated ratings in the first and third scenarios will also not have a significant impact on the final performance indicators. Therefore, subsequent calculations will be carried out for the most pessimistic second scenario, according to which the national rating of the state sharply decreases to the pre-default value of ‘CC’.
4.2 The impact of the value of political risk on the effectiveness of projects (‘CC’ rating)
The distribution of the probability of default estimated by S&P [21] and the calculated fore- cast for the ‘CC’ rating is presented in Table 6. The distribution of the value of political risk by stages and the value of NPV indicators, taking into account new conditions, are presented in Tables 7-9.
Table 6. Probability of default with a rating of ‘CC’ by probability of default with a rating of ‘CC’ by period, %
Number of years from the date of receiving the rating (fact by rating) |
Forecast |
|||||||||||||
1 |
2 |
3 |
4 |
5 |
6 |
7 |
8 |
9 |
10 |
11 |
12 |
13 |
14 |
15 |
26,87 |
36,05 |
41,23 |
44,27 |
46,75 |
47,77 |
48,85 |
49,67 |
50,64 |
51,35 |
51,86 |
52,38 |
52,90 |
53,43 |
53,96 |
Table 7. The value of political risk and NPV in wind energy projects (‘CC’ rating)
Project |
Indicators, thousand rubles |
First stage |
Second stage |
Third stage |
Fourth stage |
The stage |
Project |
First stage |
Second stage |
Third stage |
Fourth stage |
The stage |
Experimental |
NPV (risk) |
-400019,41 |
-1101878,79 |
87355,58 |
522938,44 |
3 |
WPP |
-503066 |
-1378331 |
-66909,91 |
551809,86 |
4 |
WPP-121 |
Value of risk |
12240,46 |
18316,57 |
54690,89 |
- |
|
Wind- Farm-38 |
21195,79 |
31953,85 |
93119,81 |
- |
|
Experimental |
NPV (risk) |
-300245,34 |
-827044,79 |
66059,82 |
393371,03 |
3 |
WPP |
-503066 |
-1378331 |
-96230,96 |
504198,40 |
4 |
WPP-127 |
Value of risk |
9187,41 |
13747,99 |
41027,99 |
- |
|
Wind- Farm-48 |
21195,79 |
31953,85 |
93119,81 |
- |
|
Experimental |
NPV (risk) |
-800038,83 |
-2203757,59 |
174711,17 |
1045876,88 |
3 |
WPP |
-503066 |
-1378331 |
-96230,96 |
504198,40 |
4 |
WPP-130 |
Value of risk |
24480,93 |
36633,14 |
109381,79 |
- |
|
Wind- Farm-49 |
21195,79 |
31953,85 |
|
- |
|
Experimental |
NPV (risk) |
-450021,84 |
-1239613,64 |
98446,69 |
588579,78 |
3 |
Experi- |
-417289 |
-1383304 |
-351911 |
44928,99 |
4 |
WPP -128 |
Value of risk |
13770,52 |
20606,14 |
61527,26 |
- |
|
mental WPP-52 |
17581,71 |
36520,15 |
58228,84 |
- |
|
Experimental |
NPV (risk) |
-400019,41 |
-1101878,79 |
87355,58 |
522938,44 |
3 |
WPP |
-343585 |
-1434338 |
-381534 |
190902,42 |
4 |
WPP-125 |
Value of risk |
12240,46 |
18316,57 |
54690,89 |
- |
|
Wind- Farm-61 |
23070,85 |
37867,50 |
97313,59 |
- |
|
Experimental |
NPV (risk) |
-800038,83 |
-2203757,59 |
174711,17 |
1045876,88 |
3 |
WPP |
-365163 |
-1524416 |
-488553 |
73407,68 |
4 |
WPP-129 |
Value of risk |
24480,93 |
36633,14 |
109381,79 |
- |
|
Wind- Farm-59 |
24519,72 |
40245,60 |
97848,32 |
- |
|
Experimental |
NPV (risk) |
-1079368,80 |
-2069759,83 |
250020,29 |
1011803,82 |
3 |
WPP |
-365163 |
-1524416 |
-488553 |
73407,68 |
4 |
WPP-131 |
Value of risk |
21359,02 |
28239,81 |
95181,64 |
- |
|
Wind- Farm-60 |
24519,72 |
40245,60 |
97848,32 |
- |
|
Stavropol |
NPV (risk) |
-805361,62 |
-3383743,66 |
-274169,19 |
1153968,73 |
4 |
WPP |
-365163 |
-1524416 |
-488553 |
73407,68 |
4 |
WPP-24 |
Value of risk |
43721,39 |
73131,32 |
187266,17 |
- |
|
Wind- |
24519,72 |
40245,60 |
97848,32 |
- |
|
|
|
|
|
|
|
|
Farm-57 |
|
|
|
|
|
WPP |
NPV (risk) |
-723844,33 |
-723844,33 |
-179972,49 |
163546,48 |
4 |
WPP |
-365163 |
-1524416 |
-488553 |
73407,68 |
4 |
WindFarm- |
Value of risk |
14349,22 |
14349,22 |
51340,13 |
- |
|
Wind- |
24519,72 |
40245,60 |
97848,32 |
- |
|
35 |
|
|
|
|
|
|
Farm-58 |
|
|
|
|
|
Project |
Indicators, thousand rubles |
First stage |
Second stage |
Third stage |
Fourth stage |
The stage |
Project |
First stage |
Second stage |
Third stage |
Fourth stage |
The stage |
WPP |
NPV (risk) |
-877255,52 |
-877255,52 |
-228566,57 |
183849,73 |
4 |
WPP |
-331360 |
-1383304 |
-282587 |
334160,06 |
4 |
WindFarm-34 |
Value of risk |
17390,39 |
17390,39 |
61841,27 |
- |
|
Wind- Farm-52 |
22249,97 |
36520,15 |
94649,78 |
- |
|
WPP Wind- |
NPV (risk) |
-731956,65 |
-731956,65 |
-191726,39 |
152011,40 |
4 |
WPP |
-335099 |
-1398914 |
-297249 |
319851,53 |
4 |
Farm-36 |
Value of risk |
14510,04 |
14510,04 |
51558,95 |
- |
|
Wind- Farm-51 |
22501,05 |
36932,26 |
95003,61 |
- |
|
WPP Wind- |
NPV (risk) |
-726584,49 |
-726584,49 |
-238891,38 |
76727,91 |
4 |
WPP |
-340324 |
-1420724 |
-216909 |
475133,62 |
4 |
Farm-31 |
Value of risk |
14403,54 |
14403,54 |
51414,04 |
- |
|
Wind- Farm-71 |
22851,87 |
37508,08 |
97005,00 |
- |
|
WPP Wind- |
NPV (risk) |
-731920,59 |
-731920,59 |
-246622,84 |
69140,39 |
4 |
WPP |
-340346 |
-1420816 |
-278537 |
364904,72 |
4 |
Farm-32 |
Value of risk |
14509,32 |
14509,32 |
51557,98 |
- |
|
Wind- Farm-74 |
22853,34 |
37510,48 |
97007,07 |
- |
|
Experimental |
NPV (risk) |
-621119,11 |
-621119,11 |
-412171,70 |
-209366,96 |
N/A |
WPP |
-373857 |
-1560712 |
-409941 |
236671,90 |
4 |
WPP-67 |
Value of risk |
12312,84 |
12312,84 |
33498,95 |
- |
|
Wind- Farm-75 |
25103,52 |
41203,83 |
100178,04 |
- |
|
WPP Wind- |
NPV (risk) |
-503066,62 |
-1378331,16 |
22300,96 |
696670,25 |
3 |
WPP |
-373857 |
-1560712 |
-281308 |
466893,90 |
4 |
Farm-41 |
Value of risk |
21195,79 |
31953,85 |
93119,81 |
- |
|
Wind- Farm-78 |
25103,52 |
41203,83 |
100178,04 |
- |
|
WPP Wind- |
NPV (risk) |
-503066,62 |
-1378331,16 |
22300,96 |
696670,25 |
3 |
WPP |
-373857 |
-1560712 |
-444243 |
175279,37 |
4 |
Farm-42 |
Value of risk |
21195,79 |
31953,85 |
93119,81 |
- |
|
Wind- Farm-82 |
25103,52 |
41203,83 |
100178,04 |
- |
|
WPP |
NPV (risk) |
-503066,62 |
-1378331,16 |
-66909,91 |
551809,86 |
4 |
WPP |
-386105 |
-1611844 |
-492271 |
128410,22 |
4 |
WindFarm-37 |
Value of risk |
21195,79 |
31953,85 |
93119,81 |
- |
|
Wind- Farm-83 |
25925,96 |
42553,75 |
101337,03 |
- |
|
Table 8. The value of political risk and NPV in solar energy projects (‘CC’ rating)
Project |
Indicators, thousand rubles |
First stage |
Second stage |
Third stage |
Fourth stage |
The stage |
Project |
First stage |
Second stage |
Third stage |
Fourth stage |
The stage |
SPP-2022-1 |
NPV (risk) |
-62536,85 |
-171381,78 |
90025,82 |
205278,76 |
3 |
Saratov SPP |
-211290 |
-578904,64 |
-5435,21 |
231545,25 |
4 |
|
Value of risk |
2633,12 |
3950,17 |
17728,45 |
- |
|
|
8902,32 |
13420,75 |
48712,13 |
- |
|
SPP -2018-1 |
NPV (risk) |
-578905,25 |
-578905,25 |
-383368,58 |
-228543,20 |
N/A |
Orenburg SPP |
-233655 |
-640182,53 |
-35625,57 |
222025,59 |
4 |
|
Value of risk |
11425,08 |
11425,08 |
39638,69 |
- |
|
|
9844,64 |
14841,35 |
50038,09 |
- |
|
SPP -2018-2 |
NPV (risk) |
-289455,00 |
-289455,00 |
-191638,76 |
-114201,07 |
N/A |
Privolzhskaya |
-235001 |
-643869,53 |
-58659,00 |
187000,81 |
4 |
|
Value of risk |
5712,59 |
5712,59 |
19819,41 |
- |
|
SPP |
9901,34 |
14926,83 |
50117,87 |
- |
|
SPP -2018-3 |
NPV (risk) |
-1360449,64 |
-1360449,64 |
-731806,27 |
-277332,96 |
N/A |
Privolzhskaya |
-174490 |
-609014,81 |
5959,91 |
281696,94 |
3 |
|
Value of risk |
26849,37 |
26849,37 |
93151,51 |
- |
|
SPP -1 |
9469,69 |
15207,14 |
54567,37 |
- |
|
Astrakhan |
NPV (risk) |
-238122,37 |
-652421,52 |
60761,96 |
359864,31 |
3 |
SPP Kalmykia |
-154490 |
-539208,90 |
55024,28 |
334349,26 |
3 |
SPP |
Value of risk |
10032,85 |
15125,09 |
57540,04 |
- |
|
|
8384,26 |
13464,08 |
48188,70 |
- |
|
Kalmykia |
NPV (risk) |
-208948,51 |
-572489,26 |
69693,13 |
349402,73 |
3 |
|
|
|
|
|
|
SPP |
Value of risk |
8803,66 |
13272,02 |
48573,32 |
- |
|
|
|
|
|
|
|
Table 9. The value of political risk and NPV in small hydropower projects (‘CC’ rating)
Project |
Indicators, thousand rubles |
First stage |
Second stage |
Third stage |
Fourth stage |
The stage |
Project |
First stage |
Second stage |
Third stage |
Fourth stage |
The stage |
SHPP -1_1 |
NPV (risk) |
-710551,28 |
-1946065,90 |
-1325169,11 |
-941320,99 |
N/A |
SHPP Prosyanskij |
-375679 |
-717839,07 |
-479658 |
-219078,61 |
N/A |
|
Value of risk |
29926,53 |
45533,39 |
0,15 |
- |
|
sbros BSK |
11546,19 |
15432,83 |
28889,70 |
- |
|
Bashennaya |
NPV (risk) |
-434315,50 |
-1189508,21 |
-718786,15 |
-267216,43 |
N/A |
Gorko-Balkovskaya |
-483016 |
-922935,95 |
-616722 |
-281711,45 |
N/A |
SHPP |
Value of risk |
18292,21 |
27831,71 |
46191,14 |
- |
|
SHPP |
14845,10 |
19842,21 |
37143,89 |
- |
|
SHPP |
NPV (risk) |
-833822,25 |
-2283681,86 |
-1487209,74 |
-751192,96 |
N/A |
Nizhne-Krasnogorska- |
-583295 |
-2428320,29 |
-1466530 |
-587684,03 |
N/A |
Psygansu |
Value of risk |
35118,38 |
53432,82 |
88522,95 |
- |
|
ya SHPP |
39199,78 |
67111,14 |
99533,31 |
- |
|
SHPP |
NPV (risk) |
-319605,60 |
-875344,31 |
-603030,64 |
-372028,73 |
N/A |
|
|
|
|
|
|
Segozerskaya |
Value of risk |
13480,60 |
20483,97 |
35177,71 |
- |
|
|
|
|
|
|
|
4.2.1 Wind energy projects
The level of influence of political risk in wind energy projects increases significantly in the new conditions. Its average shares are 4.8%, 2.3%, and 236.4% at each stage, respectively. Such an increase in the share of political risk is provided primarily by three projects (‘WPP WindFarm-48’, ‘WPP WindFarm-49’ [in each - almost 3000% of NPV], and ‘Stavropol WPP-24’ [215%]), in which the payback period is initially achieved only at the fourth stage. In addition, two wind energy projects (‘WPP WindFarm-37’ and ‘WPP WindFarm-38’) have a payback period migrated from the third to the fourth stage. This means that under the new set conditions, these projects fail to achieve a positive economic result within the term of the CPS RES.
4.2.2 Solar energy projects
Similar trends are typical for solar energy projects. The average share of political risk by stages increases to 4%, 2.3% and 120.7%, respectively. The greatest increase in the risk share is shown by the project ‘Privolzhskaya SPP’ (almost 600% of NPV at the third stage), which becomes cost-effective only at the fourth stage. Along with this, in two projects (‘Saratov SPP’ and ‘Orenburg SPP’), the payback period also migrated from the third to the fourth stage.
4.2.3 Small hydropower projects
Undoubtedly, in hydropower projects, the share of political risk also increases in stages to 4.5%, 2.4%, and 5.6%, respectively. However, this growth is less significant compared to wind and solar energy projects. Naturally, such projects remain economically impractical under the conditions of deteriorating national ratings and the increasing influence of political risk.
The calculations have shown that under basic conditions, when the national rating is fixed at the average level of ‘BBB’, the economic efficiency of Russian RE projects decreases. Thus, by the end of the CPS RES program, the NPV of wind projects may decrease by up to 32%, solar energy - 16%, and hydropower - less than 1% under the influence of political risk. However, in such external conditions, Russian projects have enough resilience to maintain the initial stages of payback at the same level, including a third of projects within the frame- work of the CPS RES program.
In stressful conditions, when the national rating is reduced to the critical level of ‘CC’, due to individual projects, the impact of political risk on NPV can reach 236% in wind energy projects, 121% - in solar energy and up to 6% - in small hydropower. Nevertheless, calculations have shown that the margin of safety is also sufficient and the breakeven point of only four of the 52 projects (two each in wind and solar energy) migrated from the third to the fourth stage of project implementation. The other projects remained at the previous payback stages and none of the previously effective projects entered the default zone.
As a result, this means that at the present moment the necessary conditions have been created in the Russian energy market not only to achieve a positive economic result by RE projects, but also to create the necessary margin of safety in case of adverse foreign economic and political changes.
The calculations carried out allow us to offer the following recommendations for the development of state programs to support the sector in the event of the impact of exclusively political risks. Limitation of terms and/or volumes of support for wind and solar energy projects. These projects, especially in the 2019-2020 selection years, demonstrate excellent performance indicators and high reserves of economic strength. Consequently, WPP and SPP can become pilot projects in a transition to predominantly private rather than public investments in the sector that is planned to happen in the Russian energy market after 2035 [26, 27]. Extension of the terms and/or volumes of support for small hydro- power projects. These projects are initially characterized by a high degree of economic inefficiency, which increases in the case of additional consideration of the impact of political risk. Along with economic incentives, an important step for SHPP is the development of appropriate technologies, which will reduce the amount of specific investments in such RE facilities.
The results obtained will be used to producing more specific recommendations in terms of the timing and volume of reduction/extension of state support for RE projects. This requires additional research related to the study of the impact of a set of specific risks of the sector (political, social, and economic) on the implementation of RE projects and the preliminary development of appropriate tools.
The work was supported by a grant of the President of the Russian Federation (МК- 4549.2021.2).
[1] Chebotareva, G., Strielkowski, W., Streimikiene, D. (2020). Risk assessment in renewable energy projects: a case of Russia. Journal of Cleaner Production, 269: 122110. https://doi.org/10.1016/j.jclepro.2020.122110
[2] Shimbar, A., Ebrahimi, S.B. (2020). Political risk and valuation of renewable energy investments in developing countries. Renewable Energy, 145: 1325-1333. https://doi.org/10.1016/j.renene.2019.06.055
[3] Shimbar, A., Ebrahimi, S.B. (2017). Modified-decoupled net present value: the intersection of valuation and time scaling of risk in energy sector. Environmental Energy and Economic Research, 1(4): 347-362. https://doi.org/10.22097/eeer.2018.126021.1025
[4] Chebotareva, G. (2019). Risk assessment of renewable energies: global exposure. International Journal of Energy Production and Management, 4(2): 145-157. https://doi.org/10.2495/EQ-V4-N2-145-157
[5] Chebotareva, G. (2018). Impact of state support mechanisms on the cost of renewable energy projects: the case of developing countries. WIT Transactions on Ecology and the Environment, 217: 881-891. https://doi.org/10.2495/SDP180741
[6] Kolios, A., Read, G. (2013). A Political, Economic, Social, Technology, Legal and Environmental (PESTLE) approach for risk identification of the tidal industry in the United Kingdom. Energies, 6(10): 5023-5045. https://doi.org/10.3390/en6105023
[7] Dia-Core project. (2016). The impact of risks in renewable energy investment and the role of smart policies. https://www.qualenergia.it/sites/default/files/articolo-doc/dia-core-2016-impact-of-risk-in-res-investments.pdf.
[8] Ministry of Energy of Russian Federation. (2021). System of state stimulation of electricity storage in Russia [Sistema gosudarstvennogo stimulirovaniya hraneniya elektroenergii v Rossii]. https://minenergo.gov.ru/node/489.
[9] Energy Policy [Energeticheskaya politika]. (2020). RES 2.0: A new program for the development of “green” energy in Russia [VIE 2.0: Novaya programma razvitiya «zelenoj» energetiki v Rossii]. https://energypolicy.ru/a-maksimov-vie-2-0-novaya-programma-razvitiya-zelenoj-energetiki-v-rossii/energetika/2020/17/13.
[10] Landi, D., Castorani, V., Germani, M. (2019). Interactive energetic, environmental and economic analysis of renewable hybrid energy system. International Journal on Interactive Design and Manufacturing, 13(3): 885-899. https://doi.org/10.1007/s12008-019-00554-x
[11] Herbes, C., Roth, U., Wulf, S., Dahlin, J. (2020). Economic assessment of different biogas digestate processing technologies: A scenario-based analysis. Journal of Cleaner Production, 255: 120282. https://doi.org/10.1016/j.jclepro.2020.120282
[12] Trovato, V., Kantharaj, B. (2020). Energy storage behind-the-meter with renewable generators: techno-economic value of optimal imbalance management. International Journal of Electrical Power and Energy Systems, 118: 105813. https://doi.org/10.1016/j.ijepes.2019.105813
[13] Zhang, Y., Yuan, J., Zhao, C., Lyu, L. (2020). Can dispersed wind power take off in China: A technical & institutional economics analysis. Journal of Cleaner Production, 256: 120475. https://doi.org/10.1016/j.jclepro.2020.120475
[14] Decree of the Government of the Russian Federation No. 449. (2021). On the Mechanism for Stimulating the Use of Renewable Energy Sources in the Wholesale Electricity and Capacity Market [O mekhanizme stimulirovaniya ispol’zovaniya vozobnovlyaemyh istochnikov energii na optovom rynke elektricheskoj energii i moshchnosti]. https://base.garant.ru
[15] Chebotareva, G.S. (2022). Economic efficiency of Russian renewable energy projects in the context of state support of the sector. International Journal of Energy Production and Management, 3(7): 226-244. https://doi.org/10.2495/EQ-V7-N3-226-244
[16] Chebotareva, G.S. (2021). Investments: valuation, industry features, specific types [Investicii: ocenka, otraslevye osobennosti, specificheskie vidy]. Moscow: KnoRus, 39-41.
[17] Interfax. (2021). Rosstat confirmed the estimate of inflation in Russia for 2020 at the level of 4.9% [Rosstat podtverdil ocenku inflyacii v RF za 2020 god na urovne 4,9%]. Retrieved September 1. https://www.interfax.ru/business/744841.
[18] AtsEnergo. (2021). Project selection results [Rezul'taty otborov proektov]. Retrieved September 1. https://www.atsenergo.ru/vie/proresults.
[19] Kommersant. (2019). ACRA has assigned a sovereign rating to the Russian Federation [AKRA prisvoilo suverennyj rejting Rossijskoj Federacii]. Retrieved June 10, 2022, from https://www.kommersant.ru/doc/4102683.
[20] Tyulyagin. (2019). Credit ratings of the countries of the world: S&P, Fitch and Moody’s [Credit ratings of the countries of the world: S&P, Fitch and Moody’s]. Retrieved June 10, 2022, from https://tyulyagin.ru/ratings/kreditnye-rejtingi-stran-mira-sp-fitch-i-moodys.html.
[21] S&P Global Ratings. (2022). Ratings. Retrieved June 10, 2022, from https://www.spglobal.com/ratings/ru/.
[22] FitchRatings. (2022). Ratings. Retrieved June 10, 2022, from https://www.fitchratings.com/.
[23] Moody’s. (2022). Ratings. Retrieved June 10, 2022, from https://www.moodys.com/.
[24] ACRA. (2022). Ratings [Rejtingi]. Retrieved June 10, 2022, from https://www.acra-ratings.ru/.
[25] Finance. (2022). Sovereign credit rating of Russia [Suverennyj kreditnyj rejting Rossii]. Retrieved June 10, 2022, from http://global-finances.ru/suverennyie-kreditnyie-reytingi-rossii.
[26] Kommersant. (2017). Green energy is eroding [Zelenaya energetika vyvetrivaetsya]. Retrieved January 11, 2022, from https://www.kommersant.ru/doc/3342654.
[27] Vedomosti. (2020). Ministry of Economic Development proposed to cut the renewable energy support program in half [Minekonomrazvitiya predlozhilo urezat’vdvoe programmu pod- derzhki VIE]. Retrieved January 11, 2022, from https://www.vedomosti.ru/economics/articles/2020/10/20/843976-minekonomrazvitiya-predlozhilo.