Sustainable Indicators for Integrating Renewable Energy in Bahrain’s Power Generation

Abstract

The selection of sustainable indicators is crucial in measuring and understanding the required targets within the theme of sustainability for an energy system. This is because sustainability, as a term, is used in several fields and covers a variety of indicators based on the problem’s context and identity. Each researcher looks at sustainability from their own perspective and selects the indicators which align best with their objectives and their understanding of the topic. This paper aims to implement a systematic approach to choosing the sustainable indicators for Bahrain’s electrical production with renewables. The proposed framework analyses the frequency of indicators in a sample of 73 studies and screens them in accordance with the selection principles and experts’ views. The results reveal 15 indicators with strong relevance to sustainable growth for the power sector with renewables. These indicators are classified as either qualitative or quantitative, depending on our case study’s context and the appropriate practice according to the literature. Finally, each of the selected indicators was defined to reflect its intended purpose in our study, since the common practice within the present literature is to provide such indicators without explaining their actual purpose.

1. Introduction

The term ‘sustainability’ has become a widespread catchphrase in modern development discourse, and its theme has become a significant target for society development. However, before that, the notion of sustainability had emerged through discussion of separate but related concepts since 1950. These concepts emphasised the interrelationships between resource availability, population growth and stress on the environment. The investigation of these thoughts and ideas was conducted before the term ‘sustainable’ itself was used [1]. This explains why sustainability as a concept is still not clearly defined, since it is based on deeply differing thoughts and perspectives. According to Schaller (1993), sustainability is similar to truth and justice, in that it cannot be presented in an explicit and limited definition [2]. This is because the concept itself can vary from individual to individual based on the context and time. For instance, what could be considered as truth in one civilisation may be considered lies in other cultures.

There have been several attempts to define sustainability and shed some light on its positive impact on developing communities. Without a doubt, the Brundtland report’s definition of sustainable development (SD) is considered the most common definition. Even though sustainability and SD are interchangeable concepts in the literature, the journey of SD could be more effective in putting the concepts of sustainability into practice. The focus of SD is to transfer the theoretical concepts of sustainability, which are difficult to define within a realistic action plan. For instance, in its SD strategy, the UK government defines SD as ‘enabling all people throughout the world to satisfy their basic needs and enjoy a better quality of life without compromising the quality of life of future generations [3]’. The strategy is established to identify a set of indicators through which the government’s progress could be tracked and reviewed for achieving the SD goals.

Returning to sustainability as a notion, several attempts have been made to define it and explore its positive effect on developing communities. Mebratu [4] states that sustainability has over 80 separate definitions and Ciegis, Ramanauskiene and Martinkus [5] count more than 100 definitions when it is associated with economic challenges. The meaning of sustainability could be generated from the difference between the disciplines in the analysed literature. Some of these definitions spin around enhancing and maintaining a healthy economic, environmental and social system for human development [6,7]. This leads to three interconnected relationships between the economic, environmental and social domains, which are also known as sustainability pillars [8]. The relations between these pillars imply that any human action or decision has an interrelated impact on the economy, environment and society, which in turn will affect the wellbeing of future generations.

The application of the concept of sustainability is a difficult endeavor, in addition to its lack of precise definition. Hák, Janoušková and Moldan [9] believe that changing the global economy, society and environmental agenda toward a sustainable one is a challenging target. This explains the call of the World Bank [10] for innovative methods to incorporate sustainability in our lives. Furthermore, the conception of cross-generational equity should be considered in our seeking of sustainable strategies, and this itself poses several challenges, as the needs of future generations are not easy to either determine or define. This adds more complexity to the already complicated idea, since we cannot precisely know and accurately predict the future requirements of humanity. As a result, the modern tendency in approaching the concept of sustainability relies on a balancing and ranking between the economic, social and environmental components required to meet human needs, and on tackling the exciting challenges while guaranteeing the benefits for current and future generations [11].

Another approach to understanding the meaning of sustainability is conducted by Salas-Zapata and Ortiz-Muñoz (2019) through considering the use of the term in the literature, rather than its various definitions [12]. The study revealed that there are four uses for the term:

(1)

A set of social-ecological criteria that steer human action;

(2)

A vision of humankind which facilitates convergence among environmental, economic and social targets for a particular system under study;

(3)

An object or phenomenon which occurs in specific social-ecological systems;

(4)

An approach that includes the study of economic, social and ecological dimensions of human activity, systems and products.

By identifying these four meanings, the lack of clarity of the concept of sustainability can be partially tackled. Several studies include the term ‘sustainability’ in their title without providing a definition of it or a clear approach of reflecting their understanding of it. Salas-Zapata, Ríos-Osorio and Cardona-Arias [13], who studied the published research in 2013, found that 91.3% of those including the term ‘sustainability’ in their title did not explain what it means.

It is essential to highlight here that the overarching aim of sustainability is to enhance and improve the progress of the three pillars of sustainability collectively. This can be achieved by selecting the most significant indicators, which may vary from case to case based on the context and challenges under consideration. Several principles were proposed to control and monitor the selection of sustainability indicators and to measure progress toward sustainable development. The essential principles were suggested in 1996 at Bellagio, Italy by international researchers and practitioners from five continents; these are known as the Bellagio Principles for sustainable development. Some of the principles addressed the need for a clear definition of sustainability and an emphasis on its holistic meaning. The Bellagio Principles also attempted to manage the selection process of indicators by ensuring wide participation and by standardising the method of measuring the indicators [14]. In other words, these principles aim to operationalise sustainability from concept to practice by picking limited and crucial indicators for the case under study. It is impossible to cover every sustainability indicator that could potentially be available. Consequently, indicators are usually clustered in several ways, depending on their dimension and purpose.

There is no precedent study that covers sustainability assessment for renewable technologies in Bahrain’s electrical production sector. Thus, this study aims to select and formulate the sustainable indicators that can evaluate the sustainable theme of power generation with renewables in Bahrain. In addition, indicators with high importance and relevance to our case study could be identified and used for future energy planning.

2. Materials and Methods

According to Shaaban and Scheffran (2017), few studies focus on the full spectrum of sustainability aspects for electricity generation technologies [15]. Even the ones concerned with sustainability assessment do not usually provide a basis for selecting the indicators. Singh et al. (2009) suggested a set of guidelines for selecting a process and emphasis on data availability and how relevant the indicators are to the purpose of sustainability [16]. The study stated that the chosen indicators should be measurable and comparable to provide meaning to the assessment, and their target has to be straightforward and flexible. Furthermore, Wang et al. (2009)’s principles for selecting indicators intersect with Singh et al. (2009) in relevancy, measurability and comparability; however, consistency and independence are added [16,17]. These two extra conditions are essential for the appropriate construction of a sustainability assessment, as consistency between the indicators contributes to homogenising outcomes and independently minimising repetition among the indicators. It is essential to mention here that these attributes are subjected to relativity in selection and measuring. For instance, there is always partial dependency between some of the indicators, regardless of attempts to isolate them, and this dependency could be directly or indirect. This is because they share similar themes, and the interactions among the sustainability pillars are interconnected.

Rovere et al. (2010) expanded the attributes for the selection process to fifteen and grouped them into three main themes: conception, application, and consistency [18]. Despite the additional guidelines for choosing the indicators, the content of these fifteen attributes is very similar to those mentioned in Singh et al. (2009) and Wang et al. (2009) [16,17]. However, Rovere et al. [18] shed light on two crucial attributes: the first is “sensitivity”, which represents the capacity of an indicator to allow for trend analysis; and the second attribute is “reliability”, which reflects the suitability of an indicator for capturing negative and positive aspects. Liu (2014) and Mainali and Silveira (2015) suggested other principles for sustainable indictors, different from the previous guidelines based on reflecting the strategic view of sustainability as well as the feasibility and transparency of the selecting process [19,20].

It is worth drawing attention to the central idea behind using the indicators and why they are widely implemented to evaluate our dynamic and complex environment. The main characteristic of indicators is their ability to break down a complex system into its components and then process them into meaningful information. Essentially, the indicators are developed to answer the question “How might I know objectively whether things are getting better or getting worse?” [21]. The objective of a study has a significant role in choosing and structuring the relevant indicators, which should be performed without losing other essential underlying information related to the topic of research. Thus, constructing the indicators does not mean that we can analyse every aspect of the system, but it means we can evaluate this system as per the selected indicators.

For this reason, there is no consensus on the sets of indicators that should be chosen for sustainability assessments since each study deals with different aspects to measure sustainability. For example, the challenges related to sustainable growth are dramatically different among developed and developing countries. Developing countries concentrate more on the infrastructure and diversification of their economy, while developed countries focus more on structuring policies and strategies [22]. The common practice in the literature confirms the above fact about the universal approach or set of indicators for energy application since each study proposed different methods and indicators. In addition, the researchers themselves acknowledged this fact, for example, in Cartelle Barros et al. (2015), Milne and Gray (2013), and Shi et al. (2019) [23,24,25].

2.1. Proposed Framework for Selection of Indicators

Several energy indicators have been selected to examine sustainable assessment for particular cases. The United Nations Department of Economic and Social Affairs (UNDESA), the Statistical Office of the European Communities (EUROSTAT), the European Environment Agency (EEA) and the Atomic Energy Agency (IAEA) together derived 30 indicators aimed at evaluating the sustainability of energy systems by considering the relevant social, economic and environmental dimensions [26]. The United Nations Commission on Sustainable Development (UNCSD) developed 58 indicators from its worldwide working list of 134 indicators [16]. Neves and Leal (2010) suggested a framework be established for assessing and planning in the energy sector with 18 indicators [27]. Shaaban and Scheffran (2017) proposed another framework for choosing sustainable indicators that applies to Egypt’s electrical grid, and 13 indicators were selected [15].

Overall, two aspects require more attention when we construct and select sustainable indicators for energy applications. Firstly, the principles for the selection process should be followed precisely to guarantee a high level of objectivity and the reflection of the purpose of the study. Secondly, each case study has its unique challenges under the broad umbrella of sustainable growth. Consequently, each case requires a different set of indicators to be considered and measured. Figure 1 presents the framework for selecting the sustainable indicators for Bahrain’s electricity generation planning with renewable energy. The various steps are described in detail as follows.

Firstly, the protocol for finding relevant studies for our research in the literature is performed. This includes the search for topics related to GEP, sustainability, MCDA and renewable energy with alteration of the wording and crossmatching between the words during the searching process. As a result of this step, 59 indicators were collected from 73 studies, and they are classified into technical, economic, environmental and social indicators.

Secondly, the collected indicators are assessed based on their frequency in the selected studies. Then, the ones repeated more than 20% in the studies are considered for further evaluation. The next step is to screen the selected indicators against the selection principles in

Table 1. Selection principles of indicators.

Selection Principles	Description	Reference/s
Data availability	The possibility to gather data for the selected indicator.	Singh et al., 2009 [16]
Broad participation	Wide involvement in selection process minimises subjectivity and human biases.	Hodge and Hardi, 1997 [14]
Relevancy	The appropriateness of the chosen indicators to serve the purpose of the study in a spatial and temporal manner.	Singh et al., 2009 [16], Wang et al., 2009 [17]
Simplicity	The clarity of indictors and ease of practical applications.	Singh et al., 2009 [16], Rovere et al., 2010 [18]
Independency	The chosen indicators must not include any relationship at the same level and should measure the performance from different perspectives.	Wang et al., 2009 [17]
Measurability	The indicators have to be measurable either in quantitative or qualitative terms, which is consistent with the specific goal of the study.	Singh et al., 2009 [16], Wang et al., 2009 [17]
Sensitivity	The ability of indictors to permit trend analysis.	Rovere et al., 2010 [18]
Comparability	The indicators should be comparable among each other, which also includes their suitability to be normalised for an appropriate comparison.	Singh et al., 2009 [16], Wang et al., 2009 [17]
Consistency	The selection of indicators should be in line with the study’s objectives, and each indicator has to complement each other to achieve the holistic theme of the research.	Wang et al., 2009 [17], Rovere et al., 2010 [18]
Reliability	The ability to reflect both positive and negative performance.	Rovere et al., 2010 [18], Liu, 2014 [19]

. The indictors are determined in this stage based on three features:

(a)

Considered in the literature as appropriate for the sustainable growth of electrical generation;

(b)

Related to power generation with renewable energy applications;

(c)

Appropriate for Bahrain’s challenges profile.

Bahrain is classified under the category of a small island developing state (SIDS) by the UN. SIDS share similar sustainable development challenges, which include limited resources, growing populations, fragile environments and limited human and institutional capacities. Bahrain also has a high level of energy consumption and decent living conditions, which is dissimilar to most other small island developing states [28,29].

The selected indicators are subjected to the experts’ views for rejecting or amending or suggesting other indicators. Those experts are from different backgrounds, and they have been assigned to evaluate the indicators related to their area of expertise. Finally, the final list of indicators is also assessed against the principles in Table 1, and the final selection of indicators is clustered under the technical, economic, environmental and social dimensions.

3. Results and Discussion

After following the protocol set out in the Methods section for finding relevant studies to our case study, 73 studies were found to meet the study’s purpose. Figure 2 shows the distribution of the papers according to the year of publication. It can be observed that interest in investigating and studying sustainable power generation with renewables gradually increases.

In terms of the studies’ geographical distribution, Figure 3 presents their distribution in Asia, Africa, Europe, North and South America. Some studies are not related to a specific location and are considered here under the “General” cluster. The graph shows that Asia has the highest number of studies, 42 out of 73. This could be explained by Asia having the largest share of gas reserves worldwide, which is normally used for producing electricity and creates government revenues [30]. In other words, Asia’s countries have the fiscal capacity and the natural resources to diversify their energy mix. Another essential factor is that Asia has the second-highest number of developing countries amongst the continents [31]. This highlights the necessity and opportunity of restructuring power generation to be in line with the UN agenda for prompting sustainability in each sector.

3.1. Collection of Indicators

The process of clustering the indicators depends on the researcher’s explanation of each indicator’s meaning or the problem’s context if the definition is not available. Fifty-nine indicators are derived from the studies and are classified into technical, economic, environmental and social dimensions. Some indicators could be counted as two, and others could be a part of one. The approach of grouping these indicators is associated more with their meaning, rather than listing them without an appropriate examination. Nevertheless, it is not a straightforward process since the requirement is to classify each indicator strictly into one of four dimensions when some could be suited to more than one. For instance, the “Job creation” indicator is considered by some researchers under the socioeconomic dimension as it contributes to both the social life of the people as well as the economy [32,33]. The most convenient approach to deal with these indicators is to look at the most dominant effect of them, which is more related to the objectives of the problem, and to categorise them based on that assessment. It will also be more appropriate if other indicators could cover the overlooked part of the indicators in question. For example, if “Job creation” is classified under the social dimension, its economic effect is considered to contribute to the economic indicator.

Table 2. List of the collected indicators.

Technical		Economic		Social		Environmental
T1	Risk	E1	R&D cost	S1	Societal equity	N1	Life-cycle of emission
T2	Technical feasibility	E2	Capital cost	S2	Accident fatality	N2	Adoption of independently audited environmental management systems
T3	Loss of Load Expectation	E3	Economic value/ viability	S3	Social cost	N3	Waste reduction and management
T4	Equivalent inertia	E4	O&M cost	S4	Electric energy consumption by the population	N4	Implementation of EU and national environmental policy
T5	Technology progress	E5	Electricity cost	S5	Population growth	N5	Air quality
T6	Deployment time	E6	Contribution to the economy	S6	Social acceptance	N6	Progress on international environmental agreements
T7	Distribution grid availability	E7	Return on investment	S7	Job creation	N7	Climate changes
T8	Efficiency	E8	External cost	S8	Social benefits	N8	Impact on environment
T9	Expert human resource	E9	levelised costs	S9	Cultural heritage protection	N9	CO2 emission
T10	Grid Availability	E10	Fuel costs	S10	Community relations	N10	Stress on ecosystem
T11	Heat rate of thermal	E11	Private participation			N11	Land requirement
T12	Installed capacity	E12	Utilisation factor			N12	Emission and Pollution
T13	Reliability	E13	Total costs			N13	Resource depletion
T14	Resource availability	E14	Average debt ratio of electric power enterprises
T15	Safety in covering peak load demand	E15	Cost of generation
T16	Stability of the network	E16	Economic availability
T17	Maturity
T18	Operational indicators
T19	Expected life
T20	Continuity and predictability of the performance

presents the collected indicators, and the reference of each indicator is depicted in Supplementary File.

Figure 4 presents the frequency of the used indicators in the literature. The most frequent indicator is “Capital cost” (E2), which has been used in 44 studies with a frequency of 72%, followed by “Impact on emission level” (EN12) with a frequency of 67%. While the social indicators have the lowest attention in the literature among the other dimensions, the third-highest indicator is under its category, which is “Job creation” (S7) with 65%. All indicators with a frequency equal to or bigger than 20% are presented in

Table 3. Indicators with a frequency equal to or bigger than 20%.

Technical		Economic		Social		Environmental
T6	Deployment time	E2	Capital cost	S6	Social acceptance	N9	CO2 emission
T8	Efficiency	E4	O&M cost	S7	Job creation	N10	Compliance with local conditions
T9	Expert human resource	E5	Electricity cost	S8	Social benefits	N11	Land requirement
T12	Installed capacity	E6	Contribution to the economy			N12	Emission and Pollution
T13	Reliability	E7	Return on investment
T14	Resource Potential	E9	levelised costs
T17	Maturity

.

In the technical dimension, it is more appropriate to merge the “Installed capacity” indicator (T12) with the potential resource indicator (T14). This is because the former is about the technological potential for producing electricity, and the latter is related to the source of the energy itself, but does not include the extracted power from renewable resources. Thus, the combination between these indicators could be called “Resource availability” (T21), which is more associated with measuring the generation potential for each renewable resource. “Grid compatibility” (T22) could also be essential as an indicator since renewable energy complicates the control and operation of the national electrical grid.

The “Social acceptance” indicator (S6) is changed to “Social adaptability” (S9) as it involves more than the acceptance of the technology, and relates instead to the willingness of customers to change their consumption habits to be more in line with renewable energy characteristics. In addition, two environmental dimension indicators could be combined: CO₂ emission (N9) and emission and pollution indicators (N12). They would come under “Impact on emission levels” (N14), which indicates the level of life-cycle emissions from each renewable application. It could be observed here that the numbers of social indicators in Table 2 and Table 3 are lower than that of other dimensions, which confirms Kumar’s argument that social dimensions do not have to be taken into account equally with environmental, economic and technical factors.

By following the flowchart for selecting the sustainable indicators in Figure 1, the selected indicators have to be subjected to the principles of selection in order to be suitable for our case study. Four of the chosen indicators are rejected, as shown in

Table 4. Results of screening indicators against selection.

Selection Principles	Data Availability	Broad Participation	Relevancy	Simplicity	Independency	Measurability	Sensitivity	Comparability	Consistency	Reliability
Deployment time	✓	✓	X	✓	✓	✓	✓	✓	✓	✓
Efficiency	✓	✓	✓	✓	✓	✓	✓	✓	✓	✓
Expert human resource	X	✓	✓	✓	X	✓	✓	✓	✓	✓
Reliability	✓	✓	✓	✓	✓	✓	✓	✓	✓	✓
Maturity	✓	✓	✓	✓	✓	✓	✓	✓	✓	✓
Resource availability	✓	✓	✓	✓	✓	✓	✓	✓	✓	✓
Grid compatibility	✓	✓	✓	✓	✓	✓	✓	✓	✓	✓
Capital cost	✓	✓	✓	✓	✓	✓	✓	✓	✓	✓
O&M cost	✓	✓	✓	✓	✓	✓	✓	✓	✓	✓
Electricity cost	✓	✓	✓	✓	✓	✓	✓	✓	✓	✓
Contribution to the economy	✓	✓	✓	✓	✓	✓	✓	✓	✓	✓
Return on investment	X	✓	✓	✓	X	✓	✓	✓	✓	✓
levelised costs	✓	✓	✓	✓	X	✓	✓	✓	✓	✓
Social acceptance	✓	✓	✓	✓	✓	✓	✓	✓	✓	✓
Job creation	✓	✓	✓	✓	✓	✓	✓	✓	✓	✓
Social benefits	✓	✓	✓	✓	✓	✓	✓	✓	✓	✓
Compliance with local conditions	✓	✓	✓	✓	✓	✓	✓	✓	✓	✓
Land requirement	✓	✓	✓	✓	✓	✓	✓	✓	✓	✓
Emission and Pollution	✓	✓	✓	✓	✓	✓	✓	✓	✓	✓

. In the technical dimension, the “Deployment time” indicator (T6) is not particularly significant since the country’s proposed share of renewable energy is relatively modest. Furthermore, most renewable technologies have a long deployment time, rendering this indicator almost without any considerable effect on the planning process. The “Expert human resource” (T9) indicator is rejected because there is no available data about the numbers of experts or the level of their expertise in the country. Another reason for not considering this indicator is related to its possible overlap with the “Job creation” indictor (S7), as the availability of expert human resources directly impacts the employment rate in the energy sector.

Two economic indicators are excluded from consideration: “Return on investment” (E7) and “Levelised costs” (E9). Both are not independent indicators because they depend on several factors such as the costs of capital, operation and maintenance, as well as electricity.

3.2. Final Selection of the Indicators

The chosen indicators are subjected to the experts, who have knowledge and involvement in Bahrain’s sustainable progress. Figure 5 presents the experts’ affiliation for covering the technical, economic, environmental and social dimensions. The expert panel comes from various energy sector stakeholders in the country, which include academic, industrial, governmental and commercial sectors. There are 60 total responses to the questionnaire and 56 individual participants. Due to the correlation between some of the participants’ field of expertise, some participants were asked to cover more than one dimension. For instance, one expert was assigned to cover the technical, economic and environmental indicators. The responses to the questionnaire are distributed as follows: fifteen individuals for each dimension.

The vast majority of the experts were satisfied with the selected indicators, and there was not any rejection of them.

Table 5. The final selected indicators.

Technical		Economic		Social		Environmental
T6	Deployment time	E2	Capital cost	S6	Social acceptance	N9	CO2 emission
T8	Efficiency	E4	O&M cost	S7	Job creation	N10	Compliance with local conditions
T9	Expert human resource	E5	Electricity cost	S8	Social benefits	N11	Land requirement
T12	Installed capacity	E6	Contribution to the economy			N12	Emission and Pollution
T13	Reliability	E7	Return on investment
T14	Resource Potential	E9	levelised costs
T17	Maturity

presents the final selected indicators for Bahrain’s sustainable planning of power generation. However, some experts suggested adding other indicators to be considered for the study. After reviewing the proposed indicators, they fall under the broad spectrum of the selected ones. In the following section, the selected indicators will be discussed based on how they are presented in the selected papers and the experts’ suggestions, and then they will be defined to be in line with the objectives of our study.

3.3. Definition of the Selected Indicators

It is essential to highlight here—prior to defining the selected indicators—that Bahrain’s government has taken several steps to incorporate renewable energy within its energy mix. A significant milestone was achieved in January 2017, when the Sustainable Energy Unit (SEU) launched the National Renewable Energy Action Plan (NREAP). This plan is a roadmap for identifying the most appropriate renewable resources and their optimal technologies. The action plan imposes a target of 255 MW deriving from renewable energy by 2025, with a generation of 480 GWh annually. It also sets another goal for 2035, which is to produce 700 MW—with 1460 GWh generated annually [34]. Consequently, identifying sustainable indicators for the country could assist in developing comprehensive strategies and national plans for additional sectors.

In the selected case studies, insufficient attention is paid to defining the indicators. Most of the researchers provide only the name of the indicators, which could be satisfactory, but in most cases, they are ambiguous. While a few of the papers suggested a structured framework for selecting the indicators, the most common approaches are from the literature or experts’ views. This lack of interest in defining and determining the indicators among several case studies shows how essential our proposed framework is. Defining the indicators adds more clarity and provides a solid basis for each subsequent stage of our research.

3.3.1. Technical Indicators

Efficiency

This indicator’s frequency is 55.7% in the selected case studies, which means it is widely considered in studying power planning. The vast majority of the papers define it as the useful amount of energy that can be captured from an energy source, and also as the ratio of the produced energy to the input energy. Mirjat et al. (2018) linked efficiency with the performance of the energy policy [35]. This does not seem appropriate as the study’s evaluation applies to the generation of the technologies themselves, not of the policies.

It essential to define efficiency indicators in terms of their relation to renewable energy planning. Bhandari et al. (2021) mentioned that a better efficiency performance of renewable technology could be achieved by improving the customers’ behavior or by the technology itself [36]. Even though customers’ habits in consuming electricity directly impact the efficiency of renewable technologies, the involvement of customers’ behavior should be considered in the social dimension; it is grouped under the “Social adaptability” indicator (S9) in our study. The chosen definition is in line with Al Garni et al. (2016)’s definition, which is an attempt to measure the efficiency level of renewable technology by converting its fundamental energy source into useful electricity [37]. Ideally, the most efficient technology is scored 100%; however, in practice, there is always a loss of energy for several reasons. The efficiency indicators for renewable technologies can be measured quantitatively, and for our research, they are obtained from the annual energy report of the US Energy Information Administration (EIA) (2012) and Stein (2013) (Table 6) [38,39].

Reliability

Reliability is considered in 41% of the case studies, and its definition is mainly about the electrical system’s capacity to perform as intended without interruption. Theoretically, reliability could be defined as the frequency or probability of failures, which depend on several factors such as equipment and maintenance quality. Some experts suggested adding the “stability” and “resilience” of the electrical network as indicators, since renewable energy could negatively affect the network. The network’s stability could be a critical factor if the share of renewables is relatively high, and thus, storage technologies have to be considered and evaluated. Our case study is based on Bahrain’s action plan for renewable energy, which suggested a modest goal for incorporating renewable energy. Resilience is not related to customer interruption, which is the case with the reliability indicator. It is related to the electrical system’s capability to respond to unexpected events and its recovery time from these events [40]. Thus, it is more appropriate to consider the concept of resilience and stability under the “Grid compatibility” indicator because it is aimed at evaluating the suitability of renewable technologies for the national grid.

The reliability indicator could be defined here as the level of continuous and secure supply as designed without interruption. In other words, some renewable technologies are more prone to interruption than others. For instance, photovoltaic panels cannot be used at night, and wind turbines do not operate when there is no wind or when wind speeds are too high. The reliability of renewable technologies could be evaluated qualitatively or quantitively [41]. In our research, the reliability is qualitatively assessed because there is no historical data to calculate the capacity factor required to quantify reliability (Table 6) [42].

Resource Availability

This indicator is a combination of the “Installed capacity” and “Potential resource” indicators. The former is mentioned in the case studies’ samples with a 34.4% frequency, and the latter 31.1%. The installed capacity is mainly defined as the ratio of the electrical power produced by a generating unit over a specific time [43,44], while “Potential resource” is defined as the availability of raw input resources to produce electricity [45,46]. The selected definition for “Resource availability” is about measuring each renewable resource’s actual power production per meter square for one year. The values of Bahrain’s resource availability are depicted in Table 6 [47,48,49].

Maturity

The frequency of this indicator in the selected studies is 37.7%. According to Amer and Daim (2011), a technology’s maturity is identified by its distribution both nationally and internationally [50]. This also includes the question of whether the technology has achieved its theoretical efficiency potential or if there is still an opportunity for enhancement. In contrast, Solangi et al. (2020) believe that technological maturity indicates that the technology is economically feasible and available commercially [51]. It is more convenient to look at technical maturity from the practical perspective, which is more associated with the testing and availability of the technology in the national or international market. Thus, it indicates the period that each technology is tested and then made available commercially and internationally. The evaluation of renewable technologies for Bahrain follows the common practice in the literature and can be found in Table 6 [52,53,54].

Table 6. Technical indicators for renewable technologies [39,40,43,48,49,50,53,54,55].

Technology	Efficiency [%]	Reliability	Resource Availability [kwh/m2/year]	Maturity	Grid Compatibility
PV	20	Qualitative Data	2160	Mature	Qualitative Data
CSP	21		2050	Least Mature
Wind Turbine	35		910	High mature
Biogas	25		266.6	Most Mature

Table 6. Technical indicators for renewable technologies [39,40,43,48,49,50,53,54,55].

Technology	Efficiency [%]	Reliability	Resource Availability [kwh/m2/year]	Maturity	Grid Compatibility
PV	20	Qualitative Data	2160	Mature	Qualitative Data
CSP	21		2050	Least Mature
Wind Turbine	35		910	High mature
Biogas	25		266.6	Most Mature

Grid Compatibility

This indicator is added as a result of the experts’ suggestions to include “stability” and “resilience” as indicators. The grid compatibility indicator can cover the suggested indicators and shed light on the complexity of integrating renewables into a national electrical grid. It is essential to highlight here that this indicator is about the impact of renewables on a grid, which requires technical expertise in both the technology and the grid under consideration. Incorporating renewable energy into an electrical system is not an impossible task, but it should be studied and planned to be consistent with the grid’s characteristics. The evaluation of the “Grid compatibility” indicator is conducted via experts’ views and judgments (Table 6).

3.3.2. Economic Indicators

Capital Cost

The highest frequency percentage is for the “Capital cost” indicator, at 72%. This indicator is essential in the planning stage as it shows the required liquidity to finance investment in renewable energy projects. The capital cost becomes more critical with renewables investments because their initial costs are higher than those of thermal power plants [55]. Its most common definition in the literature covers the total expenditure required to establish a plant with its equipment, labor, installation and commissioning costs. In other words, it includes all the costs of renewable energy technology just before being energised to the network [56,57]. The capital cost for each renewable technology is obtained from the literature as there is no national database for Bahrain (Table 7) [58].

O&M Cost

Operation and maintenance cost as an indicator has a 52.5% frequency in the selected case studies. This indicator consists of the plant running costs, costs of maintaining the electrical grid and the employees’ salaries [59,60]. It is not feasible to replace the electrical equipment before its expected life; hence, the electrical system has to be adequately maintained on a regular basis to secure the power supply’s reliability. The cost here comprises of two parts. Firstly, the costs associated with operating the electrical system, which include workers’ salaries, services and products. The second part is related to maintenance costs, which contribute to increasing the system’s lifespan and decreasing future failures and interruptions to the network [42]. The estimated costs of Bahrain’s renewable technology operation and maintenance costs are based on data from the US Energy Information Administration [58] (Table 7).

Table 7. Economic indicators for renewable technologies [58,61].

Technology	Investment Cost [£/kWh]	O&M Cost [£/kW—Year]	Electricity Cost [£/kWh]	Contribution to the Economy
PV	2993	19.13	0.1687	Qualitative Data
CSP	3922	52.12	0.2105
Wind Turbine	1709	30.65	0.0766
Biogas	6323	276	0.1881

Table 7. Economic indicators for renewable technologies [58,61].

Technology	Investment Cost [£/kWh]	O&M Cost [£/kW—Year]	Electricity Cost [£/kWh]	Contribution to the Economy
PV	2993	19.13	0.1687	Qualitative Data
CSP	3922	52.12	0.2105
Wind Turbine	1709	30.65	0.0766
Biogas	6323	276	0.1881

Electricity Cost

This indicator has a 32.8% frequency in the selected case studies. The method of generating electricity has a significant effect on its cost, which is considered at the point of connection between the power plant and the electrical grid [45]. It includes all costs of establishing, operating and maintaining the power plant over its lifetime. These costs are also affected by other factors such as the type of technology, efficiency and annual generation [37,42]. Electricity cost is a quantitative index obtained in our study from The International Renewable Energy Agency (IRENA) database [61] as depicted in Table 7.

Contribution to the Economy

This indicator’s frequency is 27.87%, and it directly relates to the job creation indicator. However, contribution to the economy as an indicator has more meaning than simply creating jobs, for example, developing investment and improving industrial fields. It measures to what extent the national economy could benefit from each renewable technology [41,62]. The indicator is evaluated qualitatively, and experts can assess the impact of each technology on Bahrain’s economy (Table 7).

3.3.3. Social Indicators

Job Creation

Even though this indicator could be assessed partially under the contribution to the economy, its high frequency, at 65.6%, requires considering it as a separate indicator. Furthermore, the indicator could be overlooked when it is mixed with other essential factors. According to Luthra, Mangla and Kharb (2015), employment creation is the most cited social indicator in electrical generation impact assessments [63].

There are three types of job creation associated with power generation. The first is direct job creation, representing newly created jobs for manufacturing, constructing, operating and maintaining the new power plant. Indirect jobs are the second type of employment creation, covering employment associated with the procurement of equipment, construction and services from third parties. The last type covers induced jobs, which are created as a result of improving the local economy and investment expansion [64]. The jobs creation indication in this study covers only the direct jobs, while the other parts are included in the “contribution to the economy” indicator. The estimated values for the jobs created within each renewable energy technology are obtained from a Wei, Patadia and Kammen (2010) study, based on historical data, and is used to forecast job creation from 2009 to 2030 (

Table 8. Social indicators for renewable technologies [65].

Technology	Employment Creation [job-Years/GWh]	Social Benefit	Social Adaptability
PV	0.87	Qualitative Data	Qualitative Data
CSP	0.23
Wind Turbine	0.17
Biogas	0.21

) [65].

Social Benefit

This indicator is repeated with a 21.3% frequency among other indicators in the selected case studies. Its definition is mainly related to measuring society’s social progress and its influence on education, science and culture [50,66]. Social benefits are usually evaluated qualitatively as they cannot be assessed in absolute terms. However, proxy measures could be used in evaluating social benefits, for instance, local income and the number of jobs created [43]. In our study, the experts’ judgments are utilised to assess the indicator since the other associated aspects are covered by other indicators, either quantitatively or qualitatively (Table 8).

Social Adaptability

The “Social adaptability” indicator’s development is based on the social acceptability indicator, which has a 60% frequency in the case studies. This reflects how vital social adaptability is as it covers the public’s acceptance of various renewable technologies. It shows the community’s readiness in adapting to renewable energy. The indicator is crafted for our study and aims to measure customers’ willingness to change their consumption habits to be more in line with renewable energy characteristics. Social adaptability assessment is more consistent with the AHP method because it depends on the experts’ views, while social acceptability is more suited to other types of surveys (Table 8).

3.3.4. Environmental Indicators

Compliance with Local Conditions

This indicator has a 29.5% frequency among the other indicators, and it measures the suitability of renewable technology to the country’s ecosystems. The indicator evaluates each power plant’s impact on the environment and how it suits the local environmental conditions. For instance, wind turbine technology is a potential risk to some avian species [43,67]. In our study, a qualitative impact scale is used for assessing the indicator (Table 9).

Land Requirement

The required land for developing renewable energy power plants is crucial due to its impact on human activities and the environment. The frequency of this indicator is 55.7% in the selected case studies for our study. The indicator aims to determine the required land for power plant installation, which varies from one renewable application to another. The land requirement for renewable energy depends on resource availability and efficiency [36,68]. The effect of selecting land for power generation extends to the landscape and communities close to it. Land use affects the overall quality of life and social dynamics as the occupied land could be used for more beneficial purposes involving local communities [43]. The land requirement data is collected from the literature and from international reports [42,69,70] (Table 9).

Table 9. Environmental indicators for renewable technologies [41,59,70,71].

Technology	Compliance with Local Conditions	Land Requirement [m2/kw]	Impact on Emission Level [gCO2eq/kWhe]
PV	Qualitative Data	75	300
CSP		100	150
Wind Turbine		150	124
Biogas		30	550

Table 9. Environmental indicators for renewable technologies [41,59,70,71].

Technology	Compliance with Local Conditions	Land Requirement [m2/kw]	Impact on Emission Level [gCO2eq/kWhe]
PV	Qualitative Data	75	300
CSP		100	150
Wind Turbine		150	124
Biogas		30	550

Impact on Emission Level

This indicator is one of the most commonly used indicators when evaluating renewable energy sustainability [59]. In our study, the indicator has a 67.2% frequency, which is the second highest. The indicator aims to assess the level of life-cycle emissions from each renewable application, expressed in equivalent emission of CO₂ per energy unit produced (g CO₂eq/kWh). The selected emission level for renewable energy is collated from Amponsah et al. (2014), which is implemented in several studies, such as Troldborg, Heslop and Hough (2014) and Lee and Chang (2018) [41,59,71] (Table 9).

4. Conclusions

The sustainable indicators for Bahrain’s power generation are identified in this study. The selection process follows a particular framework, which is based on both the literature and on expert views. At each stage, the principles for selecting indicators are implemented. Seventy-three studies are selected based on the suggested protocol in Section 2.1. The vast majority of the studies are conducted for Asian countries, followed by European countries. The North and South America cluster has the third highest number of studies. Fifty-nine indicators are obtained from the studies and categorised into technical, economic, environmental and social dimensions. The most used indicator is “Capital cost”, which is repeated in 72% of the studies. The second highest indicator is “Impact on emission level”, with 67% frequency, followed by “Job creation” with 65%.

After experts had evaluated the derived indicators and applied the selection principles, 15 indicators were selected for Bahrain’s sustainable planning of power generation. The technical indicators are efficiency, reliability, maturity, resource availability and grid compatibility, while the economic indicators are capital cost, O&M cost, electricity cost and contribution to the economy. Job creation, social benefit and social adaptability are the social indicators. Finally, the environmental indicators are as follows: compliance with local conditions, land requirements and impact on emission level.

Despite the effectiveness of our approach in linking the themes of sustainability and power generation planning with renewables, there is a requirement for an in-depth investigation between sustainability (as a notion) and the considered sectors within the study: technical, economic, environmental and social. This is because our research has shed some light on the interconnection among the four sectors holistically. Thus, more attention could be paid to each sector individually in order to study its role in promoting sustainable themes for the country.

Further studies are required to understand and identify the sustainable indicators for GEP with renewables in Bahrain. Even though this research effort covered technical, economic, environmental and social indicators, other significant indicators were excluded, such as political and security aspects. The overlooked dimensions were not in the scope of this study. Furthermore, it could be more efficient—in future studies—to conduct focus groups and interviews with policy makers and experts to gain further knowledge concerning such essential sustainable indicators, together with their relationship to power generation planning. Due to the time limitation for this study, a questionnaire tool was implemented to engage with policy makers and experts in Bahrain.