**1. Introduction**

Climate change is widely considered as the greatest challenge facing humanity and growing emissions, especially from the energy sector, are the main drivers of global climate change [1]. Although the use of renewable energy sources globally has grown dramatically, the continued reliance on fossil fuels has resulted in emission increase of nearly 2% to 33.1 Gtons of CO2 in 2018 [1].

In view of these facts, specialists and governments around the world have become increasingly aware of the importance of addressing climate change through the use of renewable energy sources (RES) and efficient energy management. Renewable energies are also becoming increasingly competitive as they are clean and inexhaustible sources with marked differences from fossil fuels, mainly because of their diversity, abundance, potential for use anywhere on the planet and, above all, they do not produce greenhouse

**Citation:** Alberto Alvarez, E.; Korkeakoski, M.; Santos Fuentefría, A.; Lourdes Filgueiras Sainz de Rozas, M.; Arcila Padura, R.; Luukkanen, J. Long-Range Integrated Development Analysis: The Cuban Isla de la Juventud Study Case. *Energies* **2021**, *14*, 2865. https://doi.org/10.3390/ en14102865

Academic Editor: Rafael Sebastián Fernández

Received: 19 April 2021 Accepted: 6 May 2021 Published: 15 May 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

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gases. The global weighted-average levelized cost of electricity (LCOE) of utility-scale solar photovoltaics (PV) decreased by 82% between 2010 and 2019 and onshore wind by 39% according International Renewable Energy Agency (IRENA). The same trend is likely to continue in the short-term and out to 2030 [2]. Just in 2018 the share of electricity produced from renewables grew by over 7% [1]. The increased use of renewable energy sources is facilitating new economic opportunities and access to energy for millions of people who still live without electricity services. According to the United Nations, in 2018 11% of the world's population has no access to electricity [3]. The amount of population without access continued to decrease in 2019 from 860 million in 2018 to 770 million in 2019 [3,4]. Achieving a universal access to affordable, reliable, sustainable and modern energy for all is one of the Sustainable Development Goals (SDGs) set by the United Nations. [5]

In line with the efforts made worldwide, Cuba adopted a new program in 2011 to modernize and strengthen the electricity sector, promoting the use of different renewable energy sources, mainly biogas, wind, hydro, biomass and solar energy [6]. This led, in 2017, to a policy for the "development of renewable energy sources and energy efficiency". The main objective of this policy is to increase generation by renewable sources of energy to 24% of the primary energy sources by 2030 through:


At the end of 2018 the Cuban energy production was highly dependent on fossil fuels, with around 95.5% of production coming from fossil fuels and only 4.5% from renewable energy sources [8]. The national electrical power system has been structured through a combination of condensing power plants and combined heat and power (CHP) baseload, diesel and fuel oil decentralized power generation, bioenergy from sugarcane bagasse and small amounts of power from biogas, hydro, solar and wind sources. In total, in 2013 renewables accounted only for 4.3% of the total electricity production of the country [8].

Cuba has a vast renewable energy potential to be harnessed. According to IRENA, Cuba has a good potential in both solar and wind resources with an average solar irradiance of 223.8 W/m<sup>2</sup> (5.4 kWh/m2/day) and average wind speed at around 5.7 m/s, and in the southeast above 7 m/s [8,9].

The Cuban governmen<sup>t</sup> estimates that \$3.5–4.0 billion in investments is needed to achieve their 2030 renewable energy targets with a significant share of foreign direct investments. The investments are foreseen in the wind and solar photovoltaic production. However, the governmen<sup>t</sup> promotes investments in other renewable energy sources such as biogas, forestry biomass, agro-industrial residues and municipal solid waste [10].

Although transition to more renewable based energy systems are becoming more desirable, there are various technical challenges to overcome. Vazquez et al. argue that "*increased share of RES in future electrical power system brings several challenges to system planning and operation. Weather dependence of wind power and solar PV generation increases uncertainty in the premises of system design, which should be taken into account in decision making about required generation capacity and reserves, need of energy storages, control strategy and flexibility capacity of the system*" [11].

The study case, Isla de la Juventud, is the second largest island in Cuba, located in the southwestern part of the country, with an area of 2419 km<sup>2</sup> and a population of approximately 89,000 (35.73 persons/km2). Isla de la Juventud has similar characteristics to the electric power system around Cuba although on a smaller scale, making it an ideal case to examine behavior of the radial electricity system with 100% distributed generation, made up of five main 34.5 kV circuits that supply energy to the distribution substations. The electrical power system under study is isolated from the National Electrical Power System (NEPS), operating autonomously. The generation of the system is made up by 11 diesel and fuel oil generators with an installed capacity of 35.44 MW and three solar parks (La Fe (0.8 MW), Universidad (2.4 MW) and Los Colonos (1 MW)) with 4.2 MW; a biomass plant (La Melvis) with 0.5 MW and one wind farm (Los Canarreos) with 1.65 MW of capacity. Currently 16% of installed capacity is from RES. The system is made up of fossil fuel-based generators with installed capacities up to 3.9 MW each, with similar maximum and minimum active power, power factor, ramp rates and fuel consumption in g/kWh (four MAN generators with capacity of 3.85 MW each, four BAZAN generators with a capacity of 3.6 MW each and three MTU generators with a capacity of 1.88 MW each). For this reason, the load share served by each generator is quite similar, and any of these generators, which act as the base load generation, can be used in the normal operation of the power system. The MAN type generators represent the basic generation system, with the BAZAN type for the reserve and MTU generators supporting the maximum peaks [12,13].

A desk review of RES utilization on islands globally shows that different approaches and tools have been employed e.g., to evaluate the situation of the existing electricity generation mix [14,15], to analyze the potential of energy efficiency to reduce electricity demand [16], to determine the existing barriers to the RES projects considering financial, and institutional, social or political aspects [17].

An implementation of long-range development analysis is crucial to achieving Cuba's energy and climate goals. The long-term planning analysis identifies overall transmission needs for a future timeframe, given demand growth, the targeted energy mix, interconnection policies and RES locations, among other factors [18]. In particular, alternative forecasting with existing renewable energy potentials, economic and technological variables is needed to decide the best alternatives. Long-term energy planning models are used to define investment paths and to inform long-term strategic decision making over the development of a national energy system. Long term planning models and tools have been used widely for generation expansion planning with a long (15–40+ years) planning horizon [19].

Internationally, a wide range of diverse energy planning tools are available based on the objectives they fulfil, the technologies they consider, and the time-steps they analyze. Connolly et al. sugges<sup>t</sup> that to generate a long-term 'storyline' for implementing 100% renewable energy-systems, Invert simulation tool, EnergyPlan and the Low Emissions Analysis Platform (LEAP) may be the most suitable due to their lengthy scenario-timeframe [19]. Similarly, according to IRENA tools such as e.g., MESSAGE, TIMES, MARKAL, OSeMOSYS, WASP and BALMORE can be suitable tools for 20–40 year timescale in similar analysis [18].

IRENA found that most developing and emerging economies suffer from a lack of data availability and technical know-how that pose serious challenges to focus on ensuring solid capacity, flexibility, transmission capacity and—in certain contexts—stability, which can also compromise the use certain tools. In the end, there are no ideal tools to suit all purposes but data availability, specific objectives and purpose of the study and the conditions of the site define the choice of the right tool [18]. In this article the criteria in selecting the most appropriate tool considered the accessibility to the tool (free open access), the type of tool, future orientation, and previous studies carried out with the tool. Thus, this research utilizes the Long-range Integrated Development Analysis (LINDA) model to project future scenarios for Isla de la Juventud. LINDA is an Excel-based tool used for energy systems analysis and building future scenarios. It has been used to model future energy systems e.g., in Cambodia and Lao PDR [20], Thailand [21], China [22], Barbados [23] and Cuba [24].

This article provides the technical basis for integrated development roadmap analysis that helps Cuba to achieve best RES penetration composition. We analyze two alternative scenarios for future development in accordance with existing renewable energy potentials and technological variables with Isla de la Juventud as a case study. The results can be applied to model provincial and national level power electric systems as Isla de la Juventud has similar characteristics to the electric power system around Cuba. The analysis can provide direction on how the Cuban national system would behave with high levels of renewable energy sources integration, and point out solutions for different shares of RES in the national grid in the future.

## **2. Materials and Methods**

This article utilizes The LINDA (Long-range Integrated Development Analysis) model which is based on intensity approach, building on the Extended Kaya Identity, which is used for the calculation of CO2 emissions as depicted in equation below:

$$\text{CO}\_2 = \frac{\text{CO}\_2}{\text{TPES}} \times \frac{\text{TPES}}{\text{FEC}} \times \frac{\text{FEC}}{\text{GDP}} \times \frac{\text{GDP}}{\text{POP}} \times \text{POP} \tag{1}$$

where,


LINDA is a so-called 'Accounting Framework' type of model which allows the user to construct various economic scenarios by choosing different economic growth rates for different sectors including agriculture, industry, transportation and services as shown in Figure 1. Here, the energy use is divided into fuels and electricity, with energy intensity defining how much economic output is generated with a certain amount of energy used. Economic structures will affect the energy demand as intensities differ by economic sectors. By changing the energy intensities in the scenarios, the user can have an impact on the final energy demand. The energy intensity of a sector can decrease due to the introduction of a more efficient technology or shift to less energy intensive products or production structure [20,22,24].

**Figure 1.** Calculation procedures based on the historical development and user inputs to define future energy demand [20].

The scenario construction process with the LINDA model starts with the decision of annual future economic growth level for different sectors and the future changes in the sectoral energy intensities. These provide data for annual future energy demand in different sectors. The load curve and its future changes for different consumer sectors for weekdays and weekends as well as different months are given to construct hourly consumption scenarios based on the yearly demand data. The yearly investments in electricity production capacity by power plant type are given and the model balances the production and consumption every hour by calculating the supply from variable renewable sources (wind and solar) and subtracting this from the total demand to ge<sup>t</sup> the residual load which is produced with the other power plants based on their given priority order. The model calculates the CO2 emissions based on the characteristics of different fuel and the used amounts. The calculation linkages between different modules are shown above in Figure 2.

**Figure 2.** Calculation linkages between different modules in the LINDA model [20].

The data used in the modeling for the scenario analysis are taken from the International Energy Agency (IEA) World Energy Statistics [25], National Statistics Office of Cuba (ONEI) [26] and the electric company of Isla de la Juventud [27]. For the percentages and estimates on future growth, experts from the UNE were consulted, who provided sensitive information on investments that would be made in the Isla de la Juventud in renewable sources, as well as the real load curve of the power system. The information was further processed to create an annual load curve for 2019 and cross checked with published data on the ONEI website. The historical data from ONEI provides statistical information on all sectors, divided by provinces. From the classification of the obtained information, the LINDA model allows a sectoral analysis on:


On the growth projections the authors defined sectoral growth rates for the future based on the historical data available and in relation to the projections of the electricity demand growth and electricity intensity. The LINDA model utilizes hourly load curves for different sectors of the economy to analyze future sectoral and total electricity demand. The model user inputs the hourly load curves for weekdays and weekends and for different months for one year for different sectors of the economy as well as future projected load curves for all the future years of the scenario. The estimations of the future growth in electricity consumption are based on the views of experts including the UNE. Figures 3 and 4 illustrate the examples of a typical weekday in January in household and commercial sectors.

**Figure 3.** Load curve for household electricity consumption for a weekday in January 2019 (percentage of the sectoral maximum load). Source: own elaboration with the model [27].

**Figure 4.** Load curve for commercial sector electricity consumption for a weekday in January 2019 (percentage of the sectoral maximum load). Source: own elaboration with the model [27].

Data on solar radiation and wind are obtained from The Modern-Era Retrospective analysis version 2 (MERRA 2) databases [28,29] and are shown in Figures 5 and 6.

In the electrical power system, the demand and supply have to be in the balance every hour of the year. LINDA calculates the electricity demand for every hour of the year and matches supply with the demand. The residual load is first calculated for different types of production. This residual load is the hourly demand minus the hourly production by the intermittent renewable energy sources, in this case, wind and solar. The calculation is illustrated in the below equation.

$$\text{RL} = \text{D} - \text{G} \tag{2}$$
