**3. Results**

The results are organized into sections to introduce the current situation: base year situation in 2019 in 3.1, renewable energy scenario (RENES) in 3.2, 100% renewable energy scenario with (MAXRES) in 3.3 and a comparison of results in 3.4. The authors used the data of the historical economic growth rates of Isla de la Juventud [25,26]. The inputs introduced in the model consider the country's policies to achieve a 30% penetration (of installed capacity, 24% of electricity generation) of renewable sources by 2030 [6] and a total growth of user defined GDP growth of 11.7% until 2030. For the different scenarios we have assumed that the installed capacities for RES increase in a renewable scenario (RENES) for solar PV up to 19 MW (34% of the total installed capacity) with biomass remaining the same (1% of the total installed capacity) and in the maximum use of renewable sources (MAXRES) scenario solar PV is increased up to 19 MW (31% of the total installed capacity), wind to 6.65 MW (11% of the total installed capacity) combined with a fuel switch from diesel and heavy-fuel oil to biofuels up to 35.94 MW (58% of the total installed capacity). Furthermore, in both scenarios, 10 MW in batteries are installed to store excess energy.

## *3.1. Base Year (2019)*

The LINDA model utilizes the information provided by the national statistics office in its annual summary of the development of each province and its historical rates of economic growth. [26] The historical data from 2012 to 2019 is used for each sector of the economy.

Figures 7 and 8 show the economic growth and historical energy use for the different sectors for the period from 2012 to 2019. The gradual growth can be seen in both the value added and electricity consumption. The analysis indicates that the residential sector is historically the largest consumer in the system under study [26].

**Figure 7.** Historical data for Value added (GDP) in Isla de la Juventud (2011–2019) Source: own elaboration with the model [27].

**Figure 8.** Electricity consumption by sector in Isla de Juventud in 2012–2019. Source: own elaboration with the model [27].

This is due to the low activity in the service, industry and agriculture sectors, similar to the structural behavior on the main island of Cuba. As electricity production is dominated by generators fueled by petroleum products as primary energy sources (Figure 9) in 2019, the base year, total CO2 emissions were 82 Mt.

**Figure 9.** Electricity production in Isla de Juventud in 2012–2019. Source: own elaboration with the model [27].

Figure 10 shows the behavior of a typical winter day versus a summer day, showing that the system is predominantly residential with similar characteristics to the Cuban electro-energetic system. The main characteristics of the system under study reveal the following details:

• Residential sector electricity consumption defines the overall load profile of the total demand with maximum peak taking place in the evening from 18:00–22:00 during both winter and summer season.


**Figure 10.** Demand behavior curves for a typical winter/summer day in 2019. Source: own elaboration with the model [27].

Figure 11 shows total monthly energy consumption in Isla de la Juventud in 2019. [27]. It can be seen that summer months, mainly July and August, are the months with the highest energy consumption, with over 10,000 MWh. In the winter months, this consumption decreases considerably, with just over 7000 MWh consumed in February. In February, electricity consumption is 36% less than in July. The annual demand of the system under study in 2019 was 114,548 MWh [27].

**Figure 11.** Total electricity demand on Isla de la Juventud in different month of 2019 Source: own elaboration with the model [27].

In Isla de la Juventud, by the end of 2019, there was around 10–13% of penetration of renewable energy into the electrical system. Figure 12 shows the contribution to electricity generation by different renewable energy sources, mainly wind and solar (biomass use for electricity production is minimal) and the total penetration in 2019. The results show a maximum penetration of just under 14% in total for all the RES. During the months from February to April RES provide a larger share of the energy of the total demand because of more solar production. February has the highest RES penetration rate, covering more than 13% of electricity demand. Solar energy has the highest penetration in the months from February to April with more than 8%, and at least 6% in all months of the year.

**Figure 12.** Renewable energy penetration rate (%) in 2019. Source: own elaboration with the model [27–29].

The share of wind energy does not exceed 5% of monthly consumption. During the months from August to October, wind power production has the lowest share and from December to February, the penetration is higher.

An important aspect for the analysis is to compare the penetration of renewable energy sources and hourly demand with the residual load curve. The behavior of the system has been analyzed against the influence of variable renewable sources. From the point of view of operation, it is necessary to observe the part of consumption to be covered by conventional generation each hour of the year. Figure 13 illustrates the demand versus residual load on a typical summer day. A further analysis shows that the greatest influence of renewable sources occurs during 9:00–16:00, mainly due to solar energy production. The biggest difference between the load curve and the residual load curve is at midday due to the peak of solar production. The difference is smaller at night and at dawn, because solar energy production reaches zero and only wind energy contributes to the generation and is proportionally reflected on the residual load curve. The difference between the load curve and the residual load curve is around 6 MW at maximum.

#### *3.2. Modeling Renewable Scenario Analysis (RENES) in 2030*

This scenario is based on the historical growth rates of previous years and the assumed future growth rates. The installed capacity in solar energy increases to 19.2 MW (34% of total installed capacity), wind power capacity remains at 1.65 MW (3% of total installed capacity), as well as 0.5 MW (1% of total installed capacity) of biomass. The renewable share reaches 38% of the total installed capacity by the year 2030. The assumptions in increase of solar and wind reflect the governmen<sup>t</sup> plans and user defined inputs. With the assumed GDP growth of 11.7% in the different sectors the final energy consumption of the residential sector is expected growth by 10.5%, and industry and commerce, by 8% and 7.5% respectively.

**Figure 13.** Residual load curve vs. load curve in 2019 for an example day. Source: own elaboration with the model [27].

The growth behavior is shown in Figure 14 with the residential sector clearly dominating. Similarly, in Figure 15 we can see the dominance of residential sector in the electricity consumption. Figure 16 shows that despite the increase in the installed capacities of RES into the system under study, fossil fuel consumption dominates the electricity production for the period from 2015 to 2030. These results show that the electric power system remains highly dependent on fossil fuels in the scenario with RES production at covering around 25% of the total electricity generated in a year as can be seen in Figure 17. The greatest contribution from renewable energy sources can be observed from February to April, as solar power capacity increases, its contribution grows considerably, with monthly penetration values of over 30%, and an annual average penetration of 28.5%. These values are in line with the Cuban energy sector targets 24% by 2030.

**Figure 14.** Final energy consumption in Isla de la Juventud for RENES scenario by sector. Source: own elaboration with the model [27].

**Figure 15.** Electricity consumption of Isla de la Juventud in 2030 in the RENES scenario. Source: own elaboration with the model [27].

**Figure 16.** RENES scenario for electricity production until 2030. Source: own elaboration with the model [27].

Figure 18 shows coverage of demand by different energy sources for one day in April and Figure 19 one week in April 2030. The contribution from solar is highest during the day hours while in the early mornings and night time the most contribution is from diesel. Solar energy reaches a maximum of about 12 MW during the midday hours and wind energy with a maximum occurring mainly at night and early in the morning.

**Figure 17.** Renewable energy penetration rate (%) in different months in the RENES scenario. Source: own elaboration with the model [27–29].

**Figure 18.** Electricity production for a day (19 April 2030) for the RENES scenario. Source: own elaboration with the model.

**Figure 19.** Residual load curve for a typical winter week versus summer week in 2030 for the RENES scenario. Source: own elaboration with the model.

As shown in Figure 17 the winter months have the highest contribution of RES to the system; during the winter months there is an excess of solar production which could be stored in battery systems. On the contrary, in the summer months the consumption is higher and the contribution of the RES cannot cover the demand. In Figure 19 we can observe the residual load during a winter and summer week in 2030, showing the residual load to be less in the winter and more in the summer. The residual load shows that the batteries would be an alternative to take advantage of the hours of maximum solar production by storing the energy to give the electrical power system a backup during the hours of maximum generation

The introduction of batteries as shown in Figure 20 would increase the installed capacity in the system under study by 10 MW and therefore the penetration of the RES in this simulation would reach over 40% giving the system more independence. As solar energy generation capacity increases, it is noticeable that the demand for fuels (oil and its derivatives) decreases by 5% in the period from 2020 to 2030. Figure 21 shows the CO2 emissions to the atmosphere from 2020 to 2030. Firstly, an increase in emissions is observed, due to the increase in demand and the use of diesel and fuel generators to cover this increase. However, after installing the 19 MW of solar energy according to the plan, a decrease in emissions is observed, reaching 78.2 Mtons in 2030.

**Figure 20.** Capacity of power plants in Isla de la Juventud for the RENES scenario with storage batteries. Source: own elaboration with the model.

#### *3.3. Modeling Scenario for Maximizing the Use of Renewable Energy Sources (MAXRES) by 2030*

In this scenario we maintain the growth rates of RENES and increase the solar capacity to 19.2 MW, wind capacity up to 6.2 MW and 10 MW in energy storage. In addition, fuel switch from fuel oil and diesel to biofuels is realized with a total of 35.94 MW of biofuel generators. This significantly increases the penetration of renewable energy sources gradually up to 100% in electricity generation on Isla de la Juventud with the fuel switch from a non-renewable to renewable fuels (Figures 22 and 23).

**Figure 21.** Total CO2 emissions in the RENES scenario. Source: own elaboration with the model.

**Figure 22.** Power plant capacity on Isla de la Juventud for the MAXRES scenario. Source: own elaboration with the model.

In this scenario, the newly installed wind energy capacity results in an increase of 50 GWh annually more than in the RENES scenario. This extra energy, added to that of solar energy, is stored in the batteries to be used as a backup in case of emergency or during peak demand hours, thus avoiding generation losses in the system.

With the transformation of the energy matrix to 100% RES based for 2030, the amounts of CO2 emitted to the atmosphere in this period gradually achieve a 100% reduction of emissions as shown in Figure 24.

**Figure 23.** Electricity production on the MAXRES scenario. Source: own elaboration with the model.

**Figure 24.** CO2 emissions in the MAXRES scenario. Source: own elaboration with the model.

#### *3.4. Comparison of the Scenarios*

The results show that both the RENES and MAXRES scenario comply with the country's energy policy targets for 2030, reaching a minimum of 30% of renewable sources in the total installed capacity. The residual load shows that in RENES scenario, photovoltaic solar energy makes the greatest contribution during the midday hours with the possibility to be used as a backup with the battery storage. Moreover, in the case of MAXRES scenario wind complements the demand requirements with biofuels and provides additional potential for storage especially during the night time. In terms of CO2 emission from electricity generation, we see the gradual decrease from RENES and a reduction to 13.9 in the MAXRES scenario compared to base year.

The comparison of results in different scenarios is shown in Table 1 based on:


