**3. Data and Methodology**

The main analysis focused on the share of each renewable energy source in gross electricity production from renewable sources, which can be written as follows:

$$X\_{ijt} = \frac{GEP\\_RES\_{ijt}}{GEP\\_RES\_{jt}} \cdot 100\% \tag{1}$$

where *GEP*\_*RESijt* is the amount of electricity production from the *i*-th renewable source or biofuel in the *j*-th country in the period *t*, (GWh); and *GEP*\_*RESjt* is the total amount of electricity production from renewable sources and biofuels in the *j*-th country in the period *t* (GWh), where *GEP*\_*RESjt* = ∑*n i*=1 *GEP*\_*RESijt*.

We use publicly available Eurostat's data in the presented study [81]. In the analysis the EU countries (2020 composition) and United Kingdom are included. United Kingdom is counted since this state is the EU member until the end of 2019 and the analysis cover the period 2005–2019.

The Gini coefficient ( *G*) is applied to the concentration analysis in Reference [80]:

$$G\_{jt} = \frac{\sum\_{i=1}^{n} (2i - n - 1) \, GEP\\_RES\_{ijt}}{n^2 \overline{GEP\\_RES}\_{jt}} \tag{2}$$

where *GEP*\_*RESijt* is the amount of electricity production (GWh) from *i*-th renewable source in *j*-th country in period *t*, and *n* = 7; and *GEP*\_*RESjt*= 1 *n*∑*n i*=1*GEP*\_*RESijt*.

The considered sources of renewable energy are as follows: *i* = 1 (hydro), 2 (wind), 3 (solar), 4 (biofuels), 5 (biogases), 6 (renewable municipal waste), and 7 (other: geothermal and tide, wave, and ocean).

The k-means is the research tool applied for data clustering. This algorithm is introduced by Reference [82], (see also the description of the algorithm presented in References [83,84]). A procedure scheme for the application of the k-means is presented by Reference [85], among others. The calculations are prepared by using STATISTICA 13 software (TIBCO Software Inc. Palo Alto, CA, USA). In the first stage, all variables are standardized. Then Euclidean distance is used as a distance measure. The clustering is conducted for a different number of clusters, *k* = 2, ... , 12. The number of clusters is selected by using the silhouette index (SI index [86]; see also References [87,88]. The highest value of SI index indicates the best division. In turn Reference [89] or [88] reports that acceptable divisions are characterized by the values of the SI index at least 0.5 (then the structure of the clustering is considered reasonable).

In the data clustering, seven variables constructed according the Formula (1) are considered. The list of variables is as follows:

*<sup>X</sup>*1*jt*—the share of electricity production in hydro power plants in total electricity production from renewables and biofuels (*GEP*\_*RESjt*) in *j*-th country in period *t*;

*<sup>X</sup>*2*jt*—the share of electricity production in wind power plants in total electricity production from renewables and biofuels (*GEP*\_*RESjt*) in *j*-th country in period *t*;

*<sup>X</sup>*3*jt*—the share of electricity production from solar power (solar thermal and solar photovoltaic) in total electricity production from renewables and biofuels (*GEP*\_*RESjt*) in *j*-th country in period *t*;

*<sup>X</sup>*4*jt*—the share of electricity production from biofuels (primary solid biofuels, pure biodiesels, and other liquid biofuels) in total electricity production from renewables and biofuels (*GEP*\_*RESjt*) in *j*-th country in period *t*;

*<sup>X</sup>*5*jt*—the share of electricity production from biogases in total electricity production from renewables and biofuels (*GEP*\_*RESjt*) in *j*-th country in period t;

*<sup>X</sup>*6*jt*—the share of electricity production from renewable municipal waste in total electricity production from renewables and biofuels (*GEP*\_*RESjt*) in *j*-th country in period *t*;

*<sup>X</sup>*7*jt*—the share of electricity production from other sources in total electricity production from renewables and biofuels (*GEP*\_*RESjt*) in *j*-th country in period *t* (other sources are geothermal and tide wave, ocean).

### **4. Use of Renewable Energy Sources and Biofuels in the Electricity Production in the European Union**

This section presents selected issues related to the use of renewable sources for electricity production in the European Union. In the first part, we present the share of electricity production from renewables and biofuels in the total electricity production. This part of the analysis covers the European Union (EU27, for the period 1990–2019) and the individual EU countries, including the UK (for the years 2005 and 2019). In the second part, we describe the types of renewable sources (RESs, according to the Eurostat's classification) used for the electricity production in the EU and characterize the changes that have occurred in the shares of the five most popular RES in renewable energy production from RES (*GEP\_RES*). In the third part, we report an analysis of changes in the level of concentration (measured by the Gini coefficient) of individual RES in *GEP\_RES* production. We conduct this part of the analysis for the EU area (EU27) for the period 1990–2019 and for the individual EU countries, including the UK, for the years 2005 and 2019).

### *4.1. Renewable Energy in the Electricity Production in the EU*

The main determinant of electricity production is the demand for electricity created by consumers. According to Eurostat data [90], in 2019, final energy consumption in the EU

accounted for 10,879,807.319 GWh and was 5.1% lower than in 2005. The share of electricity in total final energy consumption is 22.8%, which is higher than the corresponding rate from 2005 by 1.6 percentage point (pp). In general, the electricity final consumption increased by 2.1% in the analyzed period. Increasing the share of electricity in the EU's total energy consumption is included in the Clean energy for all Europeans package [11].

Figure 1 shows the gross electricity production (GEP), GEP from renewables and biofuels (*GEP\_RES*) and share of gross electricity production from RES in total GEP in the EU (EU-27). As the presented data dates back to the year 1990, it can be noted that until around year 2005, gross electricity production in the EU had been steadily growing. During that period (1990–2005) GEP increased by 28.2%. As in the period of 2005–2019, one can observe a relatively constant level of GEP in the EU. In 2019, there was even a slight decrease in GEP compared to 2005—by 0.5%. However, analyzing the changes of the production of electricity from renewable sources (*GEP\_RES*) shows that, in the period 1995–2005, there was an increase in its production by 49.2%, while, in the period between 2005 and 2019, there was an intensification and increase amounted by 110.8%. The total increase in the production of *GEP\_RES* in the extended period (1990–2019) accounts for 214.4%. The vast development is also visible from the share of RES in GEP production (columns in Figure 1). In 1990, this share was 14.1%; in 2005, it slightly increased to 16.3%, but in 2019, it was already 34.6%. One of the reasoning behind such increase is the fact that the new member states joining the EU in its largest expansions in 2004 undertook many actions to adopt the guidelines related to the transition to low-emission economies (e.g., reduction of CO2 and other harmful substances emissions and the use of renewable sources for energy production to a greater extent).

**Figure 1.** Gross electricity production (GEP), gross electricity production from renewables and biofuels (*GEP\_RES*), and share of gross electricity production from RES in the total gross electricity production (%RES) in 1990–2019 in the European Union (EU-27). Source: Reference [81].

> Table 1 shows the shares *GEP\_RES* in the total GEP in individual EU countries (including UK) in 2005 and 2019. In 2005, these shares ranges from 0% in Malta to 69.6% in Latvia. In 17 out of 28 analyzed countries, in 2005, the share of RES in electricity production was below the EU level (16.3%). The RES shares in GEP ranges from 10% in Cyprus to 85.9% in Luxembourg in 2019. In three more countries, the share of RES in GEP is greater than 70%; Lithuania (81.9%), Denmark (78.2%), and Austria (77.8%). Numerous countries have recorded a significant increase in the share of RES in GEP. In 11 countries, it is higher by

20 pp, and in three by as much as 50 pp: in Denmark (by 51.1 pp), Lithuania (by 76.3 pp), and Luxembourg (by 61.8 pp). This means that the policy of increasing RES for energy production has brought visible effects, especially in the case of electricity production. As a result, there is a noticeable reduction in the differentiation between EU countries in terms of this feature.

**Table 1.** Share of electricity produced from renewable sources and biofuels in the total electricity production in individual EU countries in 2005 and 2019.


Source: Own study based on data [81].

### *4.2. Types of Renewable Energy Sources Used for Electricity Production in the EU*

Energy data are collected by Eurostat according to a strictly defined methodology [91]. Data are collected in areas that allow to assess, firstly, the origin of energy, secondly, the degree of dependence on energy imports, and thirdly, the types and costs of energy consumed. A key element of the EU's energy policy is increasing the use of renewable sources, in particular regarding electricity production. As previously mentioned, the Clean energy for all Europeans package [11] assumes that, by 2050, electricity will account for over 50% of the energy consumption in the EU, with a significant share of renewable energy sources. Reliable and comparable statistics are therefore essential to be able to evaluate activities and progress in this area. In Table 2, we present the types of renewable sources and biofuels used for electricity production listed by Eurostat. While in 2019 the amount of electricity produced from all sources decreased slightly compared to 2005 (by 0.5%), the production of electricity from renewable sources and biofuels increased by 100.8% and exceeded 1 M GWh. This stands for an increase in the share of RES in the total electricity production by 18.3 pp (from 16.3% in 2005 to 34.6% in 2019).

Table 2 also shows the shares of individual sources used in gross electricity production from renewables and biofuels ( *XEU i* ) in 2005 and 2019 (columns three and five) in the EU-27 area. Figure 2, additionally, presents the changes in the shares of selected sources in an extended period of 1990–2019. In 2005, hydropower constituted the largest share of the RES\_GEP (71.4%). Hydropower [92] noted a grea<sup>t</sup> decrease compared to 1990 (by 22.9 pp), when hydropower was responsible for over 94% of electricity generated from renewable sources (see Figure 2). Continuously, this share significantly decreased by 2019— by 37 pp. (to the level of 34.3%). Even if the actual amount of the electricity produced from hydropower has slightly increased since 2005 (by 1.4%), the highly decreased trend is due to other emerging technologies enabling the use of other renewable sources. In the study period (2005–2019), energy produced from wind; kinetic energy of wind exploited for electricity generation in wind turbines [93] gained a lot of importance, and increased by 439.1%. Its share in the production of electricity from renewable sources in 2019 was 36.5% and is higher by 22.2 pp from that in 2005. In 2019, both wind and hydro were responsible

for 70.9% of electricity produced from renewable sources. Thus, these two sources are currently the main RESs used for electricity production. Another source that has gained in importance in recent years is solar energy. Eurostat distinguishes two types of solar power; solar photovoltaic (sunlight converted into electricity employing solar cells which exposed to light will generate electricity [94]) and solar thermal (heat from solar radiation (sunlight) exploited for useful energy purposes [95]). The second type of energy is produced by using, for example, solar thermal–electric plants, and its technology for the production of electricity is currently under development. According to Eurostat data, in 2005 this source was not used, and in 2019 it accounted for 0.6% of electricity production. In total, in 2019, solar energy was responsible for 12.5% of electricity produced from renewable sources. This indicator was higher than in 2005 by 12.2%. Since 2007, which is the year of the technology development, there has been an increase in the share of this type of energy (see Figure 2). Among the other technologies for the production of electricity from renewable sources, biofuels (solid and liquid biofuels) and biogases are a significant source. Electricity production from solid and liquid biofuels increased by 102.9% in the period 2005–2019, and the share of GEP production from RES slightly decreased (from 8.9% in 2005 to 8.5% in 2019). Furthermore, biogas significantly increased its importance in the production of electricity. In their case, the *XEUi* ratio increased by 3.8 percentage points in the analyzed period, to the level of 5.5%, while the production of electricity from this source increased by 581.5%. RES of minor importance in the entire EU-27 are renewable municipal waste, which in 2019 was responsible for about 2% of electricity produced from RES and geothermal and tide, wave, and ocean. The latter two sources are used by only a few countries. Geothermal is most used in Italy; and tide, wave, and ocean are used in France. While in 2005 their share in *GEP\_RES* was 2%, in 2019, it was only 0.7%. Thus, it is not a technology of strategic importance in the production of electricity, and its importance is marginalized in the scale of the entire EU.



Source: Own elaboration based on Reference [81]; *dGEP*\_*RESEUi* = *GEP*\_*RESEUi*,<sup>2019</sup> *GEP*\_*RESEUi*,<sup>2005</sup> − <sup>1</sup>·100% —means a change in the production of electricityfromthe*i*-thsourceintheperiod2005–2019.

**Figure 2.** Shares of selected renewable sources (*XEUi* ) in the production of electricity from renewable sources (*GEP\_RES*). Source: Own calculation based on Reference [81].

### *4.3. Concentration of Renewable Sources in Electricity Production*

In our analysis, we determine the Gini coefficient (see Formula (2)) by dividing renewable sources into seven categories (see Section 3, Data and Methodology). Figure 3 shows the evolution of this coefficient for the EU-27 area in 1990–2019. In 1990, the value of this coefficient was 0.83. This means that, in the EU, there was a high concentration of renewable sources used to produce electricity, and hydroelectric power plants were mainly used during this period. The energy produced by this method accounted for almost 95% of electricity production from renewable sources. In the following years, we observe a decrease in the value of the Gini coefficient. The pace of its changes is firstly slow, till around 2001, and then it accelerates. This is the result of measures taken to use more diverse sources of renewable energy. After 2001, we observe the use of wind energy and biofuels to a greater extent. In turn, after 2007, we can see that the importance of solar energy was increasing. In 2005, the concentration of renewable fuel sources was 0.704 and was lower than in 1990 by about 15%. In the following years, an even greater decline in the Gini coefficient occurred. In 2019, it was 0.512 and was lower than in 2005 by over 27%. This was influenced by several factors. Firstly, it refers to the largest enlargement of the EU in 2004. The EU-27 area for which we calculate the Gini coefficient includes the countries currently constituting the EU. Before accession, they were not obliged to implement measures for low-carbon economies on the scale that followed. The newly admitted member states had to comply with the introduced rules concerning the use of renewable sources for energy production. It is worth noting that, in the years 1990–2005, the average change in the concentration coefficient of the use of renewable sources for electricity production was higher in the EU-15 countries, and it was 0.11 (refer to the formula from the Methodology section), and for the new coming countries in 2004 or later, this change was only 0.02. In the period 2005–2019, the situation was different. It is in the new member states that the changes intensified (the Gini coefficient dropped by 0.16 on average, and for the EU-15 countries decreased by 0.08). Therefore, it is visible that the greatest progress in this area was recorded by the states of the EU-15 before 2005, and the newly admitted states only after joining the EU structures.

**Figure 3.** Changes in concentration of analyzed types of renewable sources in the production of electricity from renewable sources (*GEP\_RES*) in the EU-27 in 1990–2019. Source: Own calculation based on Reference [81].

Table 3 presents the values of the Gini coefficients for 2005 and 2019 for the EU and UK. In 2005, the highest concentration of RES appeared in Bulgaria, Croatia, Lithuania, Romania, and Slovakia (in their case, the G coefficient exceeded 0.85), as well as France, Latvia, Austria, Slovenia, and Sweden (0.85 > G > 0.8). These are the countries that used mainly hydroelectric power at that time, and the share of this type of source in the generation of electricity from RES was about 90% or more. In 2005, only in eight countries, the concentration level was lower than 0.7. During this period, we notice the greatest diversity in the use of renewable sources in the case of the UK (0.51), Germany (0.562), Estonia (0.583), Belgium (0.584), the Netherlands (0.626), Portugal (0.664), Spain (0.685), and Ireland (0.697). In the UK, the distribution of renewable energy use was as follows: hydro (40%), biogases and biofuels (41%), wind (14%), and other (5%). Germany, on the other hand, made the greatest use of wind (39.6%), hydro (37.6%), biofuels (10.8%), and all others (12%). It is also worth taking a closer look at the diversity of the use of individual sources for the production of electricity. Assuming that the i-th source can be considered significant in the production of renewable electricity, we see that the limit of *Xi* > 1% is set, then in 2005 for two countries the limit of 1% was exceeded in the case of six sources (Germany and Italy). Furthermore, for four countries, *Xi* > 1% was recorded for five sources (Belgium, Luxemburg, Netherlands, and the UK). For 14 countries, there were only three or fewer sources. In 2019, the concentration level above 0.8 was recorded only in Malta (0.849), which mainly uses solar energy (97%), and Slovenia (0.807), where hydro is mainly used (89.3%). In nine countries, the concentration level was below 0.6. The lowest values of the Gini coefficients were recorded for the Czech Republic (0.409) and Italy (0.448). The Czech Republic used mostly hydro (28.3%), biogases and biofuels (43.9%), and solar (20.6). On the other hand, in Italy, hydro (40.9%), solar (20.1%), and winds (17.2%) are used the most. Considering the diversity of the use of sources, the shares of *Xi* > 1% for each of the seven sources, this was the case only for Italy. For seven other countries (Belgium, Germany, France, Lithuania, Luxembourg, Hungary, and the UK), *Xi* > 1% were recorded for six sources. For only two countries (Malta and Cyprus), the number of valid sources was three (Cyprus) or less (two—Malta). In Cyprus, mainly 46.3% winds and 42.4% solar and 11.3% biogases were used, while in Malta, the main source of renewable electricity was solar energy (97.04%) and, to a much lesser extent, biogases (2.93%). Looking at the changes in the concentration factor, it is clear that the concentration of renewable sources in electricity production increased in the analyzed period (2005–2019) in three countries. It is

most noticeable in Estonia, where the value of the Gini coefficient increased by 0.104, due to an increase in the use of biofuels by 58.8%. An increase in concentration coefficient was also recorded in the case of Ireland ( Δ *G* = 0.074) and the UK ( Δ *G* = 0.057). The largest drops in the concentration level were recorded in the Czech Republic ( Δ *G* = −0.373), Bulgaria (Δ *G* = −0.342), Hungary ( Δ *G* = −0.274), Italy ( Δ *G* = −0.265), and Lithuania ( Δ *G* = −0.244). The Czech Republic has significantly reduced the share of hydropower (to 28.3% in 2019) in favor of solar energy and biofuels and biogases. In Hungary, in 2005, the largest share was recorded for energy produced from biofuels; in 2019, the importance of this source was reduced in favor of a greater use of solar and winds.

**Table 3.** Concentration of types of sources in the production of electricity from renewable sources in the EU countries—the values of Gini coefficients.


Source: Own calculation based on Reference [81]. Δ*G* = *G*2019 − *G*2005.

In summary, we note that there has been a significant reduction in the concentration of renewable source types used for electricity production in almost all EU countries over the period analyzed. In those countries with slightly higher levels of concentration, windgenerated electricity in particular has gained in importance. In general, we are now seeing trends across the EU where two sources in particular are gaining in importance: wind and solar. Supporting these sources is part of the EU's energy policy.

### **5. Classification of the EU Countries by the Usage of Renewable Sources for Electricity Production**

To examine similarities and differences in the use of renewables for electricity generation, we conducted the classification of the EU countries (including the UK) by applying the k-means algorithm. As in previous parts of the paper, the year 2019 was set as the reference year. The selection of the number of clusters was made based on the values of the silhouette coefficient (SI) presented in Table 4. The highest value of SI = 0.603 in the 2019 classification was obtained for 10 groups, and thus it was adopted as final. This is a satisfactory result because, with SI > 0.5, it is considered that the obtained division is characterized by a strong class structure. In the 2005 classification, the SI value for 10 groups is 0.81 and is slightly lower than the highest score for 12 groups (0.852). With an SI score > 0.7, the obtained division is considered to have a strong class structure. In addition, for the classification of data from 2011, the best division turns out to be the one into 12 groups (SI = 0.832). However, to ensure the comparability of the results, further analysis considered the division into 10 clusters, which is considered satisfactory, because the value of SI = 0.554 exceeds the limit of 0.5.


**Table 4.** Silhouette coefficients for the 2005, 2011, and 2019 classifications and the selected number of clusters.

Source: Own calculations.

The breakdown for 2005 (see Table 5) shows, first, numerous of one-object (oneelement) clusters—as many as 7 out of 10. These are the following groups: 1 (UK), 3 (Hungary), 4 (Denmark), 5 (Netherlands), 8 (Malta), 9 (Cyprus), and 10 (Italy). Those clusters constitute countries classified as standing out from the others in terms of the use of renewable sources for the production of electricity.

**Table 5.** The results of the classification of EU countries according to the shares of individual renewable energy sources in the production of electricity (clusters averages, %)—data from 2005.


Source: Own calculation in STATISTICA based on Reference [81]. Country abbreviations refer to those used by Eurostat; see Table 3.

> In 2005, Malta did not use renewable sources to produce electricity. Therefore, this country is naturally classified as a separate group. However, to maintain the consistency of the samples with the samples used in the other classifications (for 2011 and 2019), it is also included in the analysis for 2005. Italy in 2005 is distinguished primarily by the fact that it used sources that for the purposes of the presented classifications are categorized as other (variable *X*7). In Italy, geothermal is a popular source of energy. In 2005, this source contributed to the generation of almost 10% of renewable electricity. In the case of Cyprus, the main characteristic is that, in 2005, solar energy was mainly used to produce renewable electricity (over 61%). Moreover, in 2005, only two renewable sources were used in Cyprus—apart from solar energy, Cyprus used wind energy (over 38% share). Hungary is distinguished as a single-element group due to the fact that biofuels (over 84%) has a significant share in the production of renewable electricity. On the other hand, in the case of Denmark, the distinguishing factor is the share of wind energy (over 67%). The Netherlands and the UK are distinguished from other EU countries by the considerable variety of renewable sources they use. In the case of the Netherlands, these are biofuels

(almost 50%), wind (over 27%), and waste (17%). The Netherlands is the only country where waste is classified as meaningful. In turn, the UK uses mainly hydro (almost 40%), as well as wind, biofuels, and biogases, the share of which in the production of renewable electricity is greater than 10% (for each of the sources). The UK is distinguished by the share of biogases (almost a quarter of renewable electricity generated). Great diversification of renewable sources in the case of the UK is confirmed by the low value of the Gini coefficient (see Table 3).

The most numerous cluster is cluster #2. The algorithm classified 13 countries into it (46% of the analyzed objects). This cluster is distinguished by a high share of energy produced in hydroelectric plants. The group mean for this feature is *X*<sup>2005</sup> 1 = 93.3%, and the group included countries for which these shares ( *X*1) are at least 80%.

Cluster number six joins four countries with large share of wind energy: Germany, Estonia, Ireland, and Spain. The group mean for this feature is *X*<sup>2005</sup> 2 = 45.844, and the individual values of this coefficient ( *X*2) for these countries ranged from 39% to 51%. The algorithm assigns Belgium, Poland, Portugal, and Finland to Cluster #7. These countries are characterized by a similar level of hydropower consumption ( *X*1 between 46% and 70%) with a simultaneous significant consumption of biofuels (group average *X*<sup>2005</sup> 4 = 27%, and the individual values of the *X*4 feature are between 15% and 40%).

In the 2011 classification (Table 6), only four clusters are single-object. As in the previous classification (from 2005), Malta (#5), Italy (#10), and the Netherlands (#9) are classified as single-object clusters. In Malta, in 2011, two sources of renewable electricity were used: solar ( *X*3 = 50.4%) and biogases ( *X*5 = 49.6%). It is worth noting that, compared to other countries, Malta has the largest share of solar energy use. Italy, as in the previous classification, is distinguished due to the high level of use of other sources ( *X*7 = 6.66%) compared to other countries. However, this share is lower than in 2005, as, at that time, Italy began to use wind and solar panels on a larger scale. In the case of the Netherlands, there is a significant share of waste ( *X*6 = 16.5%), comparable to the previous classification. Other sources with a high share of renewable electricity production are wind and biofuels, but in 2011 their proportions changes in favor of greater use of the wind. Finland is also classified in a separate cluster, which is distinguished by the fact that the main sources used in the production of renewable electricity are hydro ( *X*1 = 51.48%) and biofuels ( *X*4 = 44.75%), totaling 96.23%.

In the 2005, Finland is classified together with Belgium, Poland, and Portugal. In the case of Belgium and Poland, in 2011, a much smaller share of renewable electricity production in hydroelectric plants is recorded, and in the case of Portugal, the importance of using biofuels decreased. The values of the coefficients have changed so significantly that these countries are no longer characterized as similar. This time Poland joined the group together with Estonia and Hungary (cluster #6). This cluster is distinguished by the significant use of biofuels (average *X*<sup>2011</sup> 4 = 58%). Furthermore, Belgium is classified together with the Czech Republic (#3). Characteristic for this cluster is the use of various sources. Cluster means greater than 10% are observed for the following traits: *X*1 (hydro), *X*2 (wind), *X*3 (solar), and *X*4 (biofuels). Due to the increased production of renewable electricity from wind in Ireland (the share increased from 50% to 80%), the algorithm classifies it together with Denmark (#4). The clusters' mean of this coefficient ( *X*<sup>2011</sup> 2 ), in this case, accounted for almost 75%. Ten countries remain classified in the largest cluster (#8). Their main source of renewable electricity production is hydro, with the mean is *X*<sup>2011</sup> 1 = 84.5% and range from 71% to over 95%. Cluster #7 (Greece, Spain, Portugal, and Lithuania) is distinguished by the largest shares of two sources: hydro ( *X*<sup>2011</sup> 1 =49.78%) and wind ( *X*<sup>2011</sup> 2 = 38.11%). The last cluster (#2) includes Germany, UK, and Cyprus, with the main sources in the production of renewable electricity being wind ( *X*<sup>2011</sup> 2 = 48.20%), biogases ( *X*<sup>2011</sup> 5 = 20.64%), and hydro ( *X*<sup>2011</sup> 1 = 13.55%). It is worth adding that, in the case of Cyprus, the role of the solar source has significantly decreased, from 61.45% in

2005 to 6.7% in 2011, with a simultaneous large increase in energy production from these two sources.

**Table 6.** Results of the classification of EU countries according to the shares of individual renewable energy sources in the production of electricity (clusters averages, %)—data from 2011.


Source: Own calculation in STATISTICA based on Reference [81]. For country abbreviations, refer to those used by Eurostat (see Table 3).

> The compositions of clusters change again for the 2019 classification (see Table 7). Five countries are classified into single-object clusters. As in the previous classification, these are Malta (#8) and Italy (#1), as well as the Czech Republic (#3), Hungary (#5), and Estonia (#6). Italy, as in the previous cases, is distinguished primarily by a high share of other sources (*X*7 = 5.16%) compared to other countries. Although it decreased compared to 2011, the amount of electricity generated with this method has increased. It is also worth noting that, in Italy, the importance of the use of solar and wind energy has increased. In 2019, in Malta, solar is the dominant source used for the production of renewable electricity, with the share of *X*3 = 97.04%. This is a significant increase compared to 2011, by over 45 pp. Estonia is distinguished by a high consumption of biofuels, with a significant consumption of wind energy and a significant reduction in the share of hydropower compared to that in 2011. In Hungary, significant shares of biofuels ( *X*4 = 37.74%) and solar energy ( *X*3 = 31.94%) are recorded. On the other hand, the Czech Republic still stands out due to the significant— compared to other countries—use of biogases in the mix of renewable sources ( *X*5 = 22.54%) and the burden of electricity production being distributed among four sources: in addition to the mentioned biogases, hydro ( *X*1 = 40.92%), biofuels ( *X*4 = 21.38), and solar energy (*X*3 = 20.13%). Thus, a low level of concentration of RES in the production of electricity.

> The cluster with the highest share of hydro is Cluster #4: Croatia, Austria, Romania, and Slovenia. The clusters' mean for this variable was as high as *X*1 = 74.81%. Another cluster with high hydro consumption is Cluster #2 (Bulgaria, France, Latvia, Luxembourg, Slovakia, Finland, and Sweden). At the same time, in this cluster, there is a significant consumption of biofuels ( *X*4 = 16.7%), which distinguished it from #4. Eight countries are classified to the largest Cluster #9, distinguished by the significant use of wind energy (*X*1 = 57.35%). The other two clusters are Clusters #8 (Belgium and the Netherlands) and #10 (Germany and Cyprus), which are also characterized by significant use of wind energy (group averages for this variable being, respectively, 49.16% and 48.52%). However, significant use of other sources is also important for the breakdown. In the case of Belgium and the Netherlands, these are solar ( *X*3 = 22.15%) and biofuels ( *X*4 = 14.49%). Menawhile, in the case of Germany and Cyprus, these are solar ( *X*3 = 30.54%) and biogases ( *X*5 = 12.25%).


**Table 7.** Results of the classification of EU countries according to the shares of individual renewable energy sources in the production of electricity (clusters averages, %)—data from 2019.

Source: Own calculation in STATISTICA based on Reference [81]. Country abbreviations refer to those used by Eurostat (see Table 3).
