The Sustainability Concept: A Review Focusing on Energy

Abstract

The concept of sustainability, with a focus on energy, has emerged as a central tenet in addressing the mounting global challenges of environmental degradation and resource depletion. Indicators of sustainability focusing on energy are crucial tools used to assess and monitor progress toward achieving a more sustainable energy system. These indicators provide valuable insights into the environmental, social, and economic dimensions of energy practices and their long-term impacts. By analyzing and understanding these indicators, policymakers, businesses, and communities can make informed decisions, formulate effective policies, and steer their efforts toward a more sustainable energy future. These indicators serve as navigational guides, steering the world toward energy practices that support both present needs and the well-being of future generations. In this paper, the concept of sustainability and measurement indexes used are reviewed, focusing on energy factors. The focus of the discussion presented here is related to an assessment of the possibilities for improving energy efficiency and evaluating the indicators that are used to measure whether the desired levels of sustainability are being achieved.

1. Introduction

It is increasingly important to include environmental, social, and governance considerations when evaluating results, especially in an industry as impacting as energy. Incorporating sustainability indicators assessments provides a more holistic evaluation of the long-term feasibility and harmony of deals with broader sustainable development objectives [1]. The sustainable principles serve as a unifying framework, promoting the responsible stewardship of resources, inclusivity, and intergenerational well-being. It further underscores how these principles provide a shared foundation for individuals, organizations, and societies to collaboratively contribute to a sustainable future [2].

A sustainability index implies providing information on the mechanisms and logic that operate in the area under analysis and quantifying the most important phenomena that occur in the system under study [3]. With this index, it is possible to understand how human activity affects the environment, alert people on the risks of survival, predict future situations, and offer sustainable alternatives in making better policy decisions [4].

Indicators make it possible to select the most relevant information, simplify complex phenomena, quantify qualitative information, and communicate information between collectors and users. They have applications for evaluating conditions and trends about objectives and goals, comparing results considering similar methodologies, and providing warning information to anticipate future conditions, among several other uses [5].

Sustainability is a balancing act between social, environmental, and economic dimensions [6]. The three dimensions of sustainability may imply conflicts due to the very concept of each part: environmental sustainability means the temporal maintenance of the fundamental characteristics of ecosystems under the use of their components and interactions; economic sustainability results in stable profitability over time; social sustainability associates the idea of systemic organization that must have cultural and ethical values of involved groups and society in a way that is acceptable to organizations over time [7].

These sustainability dimensions represent different aspects of human well-being and development that need to be balanced to ensure a sustainable and equitable future for both current and future generations [8]. These dimensions are interconnected and interdependent [9]. Achieving sustainability requires finding synergies and trade-offs among them, as actions in one dimension can have implications for the others [10].

The idea of the interconnections between sustainability dimensions is presented in Figure 1, especially focusing on energy; there are topics that are in more than one dimension, such as electricity access, which has social and economic importance. Each dimension of sustainability has indicators that measure whether the levels of sustainability are being satisfied, and the evaluation and discussion of these indicators are the focus of this paper.

Environmentally, indicators may include the share of renewable energy in the total energy mix, the reduction in greenhouse gas emissions, and improvements in energy efficiency. Social indicators might encompass access to affordable and reliable energy services for all, equitable distribution of energy resources, and the creation of green jobs in the renewable energy sector. On the economic front, indicators may assess the cost-effectiveness of sustainable energy solutions, investments in renewable energy infrastructure, and the overall resilience of energy systems to market fluctuations.

The social dimension focuses on the well-being and quality of life of people [11]. It includes aspects such as social equity, justice, human rights, health, education, cultural preservation, and community engagement [12]. In a sustainable society, social systems should ensure that all individuals have access to basic needs, opportunities, and a high quality of life without compromising the needs of future generations.

The environmental dimension relates to the health and resilience of ecosystems and the natural environment. It involves maintaining biodiversity, conserving resources, reducing pollution, addressing climate change, and promoting sustainable land use and resource management [13]. A sustainable approach considers the Earth’s finite resources and aims to minimize negative impacts on the environment.

The economic dimension concerns the long-term viability of economic systems. It involves promoting economic growth and development while ensuring that it does not come at the expense of social well-being or environmental health [14]. Sustainable economies strive to balance prosperity with the responsible use of resources, ethical practices, and consideration of the impacts of economic activities on society and the environment [15].

In recent years, discussions around sustainability have expanded to include additional dimensions such as cultural [16], political [17], and technological aspects [18], recognizing the complexity of achieving a truly sustainable future. In this case, energy is related to the technological aspect of sustainability, where there is a goal to provide energy with a lower environmental impact by improving the infrastructure of the system to make it reliable and efficient [19]. In this paper, the technological aspects are the focus, and the sustainability based on the energy is going to be covered.

The energy supply system consists of the physical infrastructure that defines the system configuration for resource input [20] and its expected response [21]. Resource inputs include primary energy inputs, such as crude oil, coal, natural gas, hydropower hydroelectric [22], nuclear [23], or renewable energy. The combination of resources and the configuration of infrastructure defines the production capacity of the energy system and, therefore, its ability to meet society’s needs at any given time [24].

1.1. Challenges

Renewable energies play a key role in reducing greenhouse gases as they do not come from burning fossil fuels, thus promoting energy sustainability and reducing pollutants. Achieving energy sustainability is a complex and multifaceted goal that involves addressing a range of challenges and barriers at both policy and technology levels. Here are some key challenges and potential strategies to overcome them (regarding policy and technology levels):

• Dependency on Fossil Fuels. Policy Level: Implement policies that incentivize the transition to renewable energy sources through subsidies, carbon pricing, and phasing out fossil fuel subsidies. Technology Level: Invest in research and development to improve the efficiency and cost-effectiveness of renewable energy technologies [25].

• Infrastructure and Investment. Policy Level: Develop financial mechanisms like tax incentives, grants, and public–private partnerships to attract investments in sustainable energy infrastructure. Technology Level: Focus on innovation and modular designs to lower the upfront costs of renewable energy installations and grid modernization [26].

• Intermittency and Reliability of Renewable Energy. Policy Level: Encourage energy storage development through policies promoting the research, development, and deployment of energy storage technologies. Technology Level: Invest in advancements in energy storage technologies like batteries, pumped hydro, and grid integration solutions to mitigate the intermittency issue.

• Lack of Energy Access. Policy Level: Prioritize policies that promote decentralized energy systems and microgrids, especially in underserved areas, to improve energy access. Technology Level: Develop affordable and scalable off-grid renewable energy solutions, such as solar home systems and mini-grids, and improving the electrical power system [20].

• Environmental Impact. Policy Level: Enforce strict environmental regulations and carbon pricing to incentivize cleaner technologies and penalize high-emission energy sources. Technology Level: Invest in clean technologies like carbon capture and utilization and promote circular economy practices in energy production.

• Technological and Knowledge Gaps. Policy Level: Invest in education and skill development programs to build a knowledgeable workforce capable of working with emerging clean technologies. Technology Level: Foster collaborations between academia, research institutions, and industry to bridge technological gaps and accelerate innovation.

• Political and Socioeconomic Challenges. Policy Level: Engage in international cooperation and agreements to foster a global commitment to energy sustainability, encouraging countries to share knowledge and resources. Technology Level: Develop diplomatic relationships to facilitate the transfer of sustainable energy technologies between nations, especially to those in need.

1.2. Objectives

Considering the challenges presented here, this work has the following objectives:

• Contextualize the concept of sustainability related to energy, based on the three classic dimensions (social, economic, and environmental), and propose a rereading with the insertion of two new dimensions (technical and institutional).

• Review and propose energy sustainability indicators based on the five dimensions of sustainable development (environmental, economic, social, technical, and institutional).

• Qualify the importance of energy sustainability for regional energy planning in line with public policies for sustainable development.

Addressing energy sustainability necessitates a holistic approach that combines policy interventions with technological advancements. Collaboration between governments, industries, research institutions, and communities is vital to overcoming the challenges and achieving a sustainable energy future [27]. Additionally, public awareness and engagement are crucial to garner support for sustainable energy initiatives and drive meaningful change. Given these challenges, the hypotheses/question arises:

Can harnessing renewable energy sources, implementing sustainable energy policies, and integrating energy efficiency measures lead to long-term viability and alignment with sustainable development goals in the energy sector?

Several researchers have presented reviews regarding sustainability, and some of these related works are discussed in Section 2. In Section 3, an evaluation of the methods available to save energy and improvements in power supply are presented. In Section 4, the indexes and indicators of sustainable development are explained, and finally, in Section 5, a conclusion is discussed.

2. Sustainability Reviews

Feil et al. [28], through a literature review with 24 papers, in a historical series from 1998 to 2018, found that 31.4 sustainability indicators are used on average in industrial organizations. The frequency of factors in the environmental, social, and economic spheres was evaluated. In the environmental context, it was verified that the volume of atmospheric gases, electricity, and water consumption are the main indicators evaluated. Within the social context, the engagement with the community, health, safety, and ethical behavior stand out. And concerning the economic indicators, the gross resale value, net profit, and investment capital have the greatest relevance.

Muniz et al. [29] present a comprehensive examination of tools utilized for measuring energy sustainability, offering a comparative analysis of their features, methodologies, and applicability. This research investigates the diverse range of assessment tools available in energy sustainability, encompassing both quantitative and qualitative approaches. By critically evaluating the strengths and limitations of each tool, they aim to provide a nuanced understanding of their respective contributions to evaluating energy systems’ ecological, societal, and economic dimensions.

Brulé [30], employing qualitative analysis, proposed alternatives to the measurements of already-existing indexes. Their results show an interconnection capacity with other indexes and political relevance. Therefore, it is necessary to evaluate the quality and improvement in the adaptation of indexes that are already consolidated, bringing more effective and cognitive measures to the level of social interaction and the evaluated community.

When verifying the global development indexes, Guo et al. [31] proposed to determine the capacity for the development of green technologies and sustainability. They evaluated the carbon dioxide emissions, verifying that due to the capacity of larger countries to extract natural resources and have a larger industrial complex, they pollute more. Therefore, there is a need to introduce environmental taxes so that “green” technologies are adopted and prohibit subsidies that are harmful to the environment, to increase public investment in this sector, to monitor whether the indicators and action programs are effective in regulating environmental protection, and to reduce the risks of adherence of new technologies on the market that have the potential to reduce environmental impacts.

Wang et al. [32] made an assessment of the power system in the European community concerning sustainable development commitments. With the need to increase external commercialization and expand consumption by more than 60 percent in the continent’s energy matrix, there is a need to seek to minimize greenhouse gas emissions and maximize the energy efficiency of electricity generation. The improvement in generation efficiency can be in large power plants or even in microgeneration [33]. According to Yumashev et al. [34], researchers verified that besides being an important factor in the development of life expectancy and standard of human welfare, the volume and quality of energy consumed interfere with the improvement in sustainability in a country and the levels of socioeconomic development.

The volume and quality of energy consumed concerning human development in carbon dioxide emissions had its influence studied by Yumashev et al. [34], in which the researchers found that in addition to being an important factor in the development of life expectancy and standard of human well-being, it interferes in the improvement in sustainability in a country and the levels of socioeconomic development. Since energy is a parameter that can be evaluated by its efficiency, intensity of use, and sustainability, combined as a trilemma, Baloch et al. [35] found that in the BRICS block, Brazil and Russia are the countries that have achieved the best environmental performance index in these three aspects respectively among the five countries in a data collection that took place from 2011 to 2016.

Flores et al. [36] focused on determining the most vital indicators related to sustainability in bioenergy from natural resources, prioritizing the use of non-native biomass within the Amazon as an energy source in this region within the literature, determining the critical points of advancement, and individualizing each area whether, they are social, economic and/or environmental, in conjunction with the determination of correlated indicators in sampling about seven attributes of sustainability (AOS) of the Spanish framework of natural resource management, which are resilience, adaptability, productivity, equity, self-confidence, reliability, and stability, finding 29 relevant indicators including 11 environmental indicators, 11 social indicators, and 7 economic indicators, through 27 critical points in these seven AOSs of the applied framework.

The standardization of indicators that have greater use in different indices is determined by internal and external policies adopted by the leaders of the organization or country and also by the internal conjugations that can be subdivided by their capacity as sub-indices and in the relationship of the performance output according to the desired value metric together with the impact achieved and the importance of each sub-index in the process. Huovila et al. [37] presented a methodology in the context of international standards within the concept of smart cities and their impact according to sub-indices such as transport, economy, water and waste, education, culture, innovation, governance, and citizen engagement, among other parameters, allowing other researchers to have a synthesized content in the evaluation of various standards and determine which ones are best adapted concerning the focus that will be given in the development of indices.

In the management of sub-indices, the number of indicators of them in the composition of the intervals and linguistic rules should be evaluated in addition to their aggregation within the final index. Gunnarsdontir et al.’s [38] review evaluated several energy sustainability indicators from the literature, one of which was the metric developed by Sovacool and Mukherjee [39], which had 372 indicators among all. The transparency in this paper was evaluated through the selection and application of all the indicators analyzed in more than 50 indexes developed by world bodies such as the World Energy Council, the World Bank, and the World Economic Forum, which complement the obtainment of stakeholders and their engagement; provide verification with 320 simple and 52 complex indicators in energy security; contribute in new future studies synthesizing the criteria of quality, quantity, and context; andcontribute in the performance evaluation of policies that adopt metrics and suppress the obtainment of an index that can present if there are threats in the context of access to electricity in the analyzed area

Achieving energy sustainability depends on the implementation of tools and applications that increase energy efficiency in the electricity system, and globalized financing can allow the improvement in environmental impact reduction rates. Murshed et al. [40] verified the increase in this economic aspect and its importance in sub-Saharan African countries, in which a 1 percent increase in energy efficiency rates within the entire context of the electricity system contributes to up to 11 percent in the improvement in sustainability indexes in the seven global sustainable development goals and promotes the improvement in internal development policies in reducing barriers to foreign investments with partnerships of local companies and state support by reducing taxes in these financing models by countries with a high income concentration that could benefit from social advertisements and the capture of natural resources with an adequate percentage to the benefited countries and external countries.

Within these goals of improving the reduction in environmental impacts in the energy sector, regulation and energy policies are critical points in the densification of the application of renewable energies crucial in encouraging and accelerating business involving potentially more sustainable energy resources and greater financial risk, as seen by Drago and Gatto [41], who made an indicator composed of four factors: the access to transparency and monitoring standards of renewable energy utilities, the legalization structure of these, counterpart risks, and energy building codes showing that some countries have high performance, thus benefiting both internal and external investments, while other countries have limitations in accessing these data, reducing the scale of investments.

The interrelation of the parameters of regulation, sustainability, and energy policies when evaluating the relationship of electricity from renewable sources with the index of economic complexity to achieve carbon emission neutrality was reviewed by Li et al. [42], in which the researchers found that the greater use of renewable energy is linked to this reduction in air pollution. However, it must be in line with the reduction in imports of fossil fuels, headed by investments in the export of more sustainable technologies, and increased resources in innovations that improve energy efficiency in general, reducing the need for greater capture of natural resources.

When evaluating the context of a country or region with a large area, there is a high probability of the occurrence of energy poverty, which is the lack of access to current energy services and which can reduce the level of sustainability because there is usually the adherence to fossil fuels. When applying this index, which can occur in both developed countries and developing regions, its concepts and metrics must be evaluated so that there is equity in measurement and there are no unequivocal measurements; in this way, Sy and Mokaddem [43] noted that the scarcity of data is still an impediment in the comparison between regions and further increases the delay in the adoption of energy policies that achieve sustainability in conjunction with the wide access to electricity due to lower population and income in remote regions.

The review presented by Chenari, Carrilho, and da Silva [44] investigates the mastery of sustainable, energy-efficient, and health-conscious ventilation strategies in the context of building environments. The critical importance of ventilation in maintaining indoor air quality, thermal comfort, and overall occupant well-being is widely acknowledged. In the face of escalating energy demands and environmental concerns, the need for innovative approaches to ventilation becomes paramount. The analysis encompasses their respective advantages, drawbacks, and performance metrics in terms of energy consumption, indoor air quality enhancement, and potential health impacts. The intricate interplay between ventilation strategies, building designs, and local climate conditions is examined in depth.

Pacheco, Ordóñez, and Martínez [45] presented a study about energy-efficient building design, exploring its pivotal role in mitigating energy consumption and environmental impact within the construction sector. With escalating energy demands and heightened awareness of climate change, the imperative to revolutionize building design strategies has gained paramount importance. Their paper scrutinizes a spectrum of energy-efficient design principles and strategies, ranging from passive design techniques to cutting-edge technological innovations. It delves into their respective merits, limitations, and quantifiable outcomes in terms of energy conservation, reduced operational costs, and decreased carbon footprint.

As the global community grapples with escalating environmental concerns and the imperative to transition from fossil fuels becomes ever more pressing, policy frameworks aimed at advancing renewable energy sources have gained prominence. Lu et al. [27] examine a spectrum of sustainable energy policies implemented worldwide, analyzing their design, implementation, and outcomes. Through their research, they assess the multifaceted impacts of policy interventions on renewable energy adoption. By considering various dimensions such as economic viability, technological innovation, environmental impact, and social acceptability, this review provides a comprehensive assessment of the strengths and limitations of different policy approaches.

As concerns over resource depletion and climate change intensify, businesses are increasingly pressured to adopt strategies that minimize environmental impacts while maintaining efficient supply chain operations. Centobelli, Cerchione, and Esposito [46] examined the evolving landscape of research trends in this domain and proposed guidelines for effectively integrating environmental sustainability and energy efficiency within supply chain practices. They explored the intricate relationships between supply chain design, operations, transportation, and distribution in the context of reducing ecological footprints and optimizing energy usage.

Meng et al. [47] assessed the multifaceted impacts of incorporating smart technologies into factory environments. Their work scrutinizes various dimensions, including process optimization, resource utilization, waste reduction, and carbon footprint mitigation, to comprehensively evaluate how smart factories contribute to sustainable production. The review delves into the intricate web of technologies underpinning smart factories. Considering that there is a major effort to improve the efficiency and reliability of power systems, the next section presents a discussion about this topic based on other authors’ applications.

3. Technology and Efficiency Improvement

Hydrogen fuel cell buses represent a promising avenue for sustainable urban transportation, but their energy efficiency is contingent on the effective management of power distribution and consumption. The study presented by Shen et al. [48] delves into the utilization of deep reinforcement learning algorithms to enhance the energy efficiency of hydrogen fuel cell buses by dynamically adjusting their velocity profiles. As well evaluated nowadays, the energy supply has become more efficient with the use of time series forecasting [49] using hybrid models [50], classification (computer vision [51], convolutional neural networks [52], deep neural networks [53], multilayer perceptron, and k-nearest neighbors [54]), and Internet of Things (IoT) using embedded systems [55].

Measuring energy sustainability using fuzzy logic can be performed with biological inputs, which can have a highly polluting character when released inappropriately into the environment. Parameters are first defined in governance in order to reduce this impact as quickly as possible so that these two processes, being carried out by specialized teams, are later assigned importance in each social, economic, technical and environmental indicator in the form of numerical scores according to the scenario and location analyzed formulating technological priorities seeking planning and decisions that are more appropriate [56].

These strategies can be carried out from a small site to reach entire countries, and they can become more complex and assist energy policies by categorizing the selection of energy plant sites, structural decisions assessing global costs, and productivity gains due to increased exports by raising the renewable matrix with trading partners and the risks associated with this energy stance with existing and expected marketing possibilities [57,58,59].

Although artificial intelligence (AI) algorithms are complex and their combination with other statistical tools is required by technical criteria [60], at the end of the operation, the results must be easy to understand for legislators and decision-makers in the area of energy policy, clearly dealing with the recognition of qualitative and quantitative indicators and having robustness, that is, guaranteeing the conclusions obtained, and there is a need to minimize the consumption of time and financial resources compared to human choices experts presenting strategies that improve the investment environment and reduce risks in operational energy planning both micro and macro population environments [61].

Within the electricity sector, generation, transmission, and distribution systems are encompassed by specific protocols. It can be evaluated from the literature that these established standards facilitate the adoption of a certain method that will have greater adaptability in the iteration of the data that will be inserted in the proposed model and obtain an energy sustainability index [62], determining the degree of influence for each related indicator [63]. Focused on improving energy access, researchers have evaluated advanced methods to analyze the transmission lines’ performance, using models to determine how the leakage current, electric field, and partial discharges are affecting the power system supply. According to Klaar et al. [64] and Ribeiro et al. [65], in addition to the system performance analysis, the energy price is necessary to evaluate as a measure of social access.

Among the methodologies for creating and developing these indices in line with the objectives of sustainable development within the electricity sector, three methods stand out that are related to AI algorithms: multicriteria decision analysis, aggregate normalization in minimum and maximum discrepancies, and hierarchical analytical process. These are related in the three dimensions most evaluated in the literature: environmental, economic and social. In addition, the cultural, institutional, and technical aspects can also be added, depending on the complexity and need foreseen, as well as the size of each project [66,67,68]. Nowadays, AI-based models are applied considering their capacity to deal with nonlinear data [69,70,71].

To classify technologies that are similar in technical characteristics, fuzzy logic can be an excellent alternative for reducing the costs and time required for investor decisions, by establishing criteria and weights for the needs envisaged by this group using the technique of the order of preference using similarity in an ideal system solution (TOPSIS) [72], improving the consistency of comparisons by matrices and sub-criteria, and it is used more significantly and with less sensitivity in the classification of nuclear plants; however, it is not limited to this type of plant and can be applied to other energy transformation plants.

Through the vision of a hierarchical analytical process (AHP), weight criteria are determined, and the relative importance values of different parameters are calculated; when embedded in logic such as fuzzy logic, the consistency of data from human uncertainty can be improved [73]. This allows decisions to be made that are more sensitive, realistic, and concrete among the particularities from the perspectives of energy policy alternatives with conflicting criteria, both in the AHP tool and in the analytical network process (ANP), which is the most widely used technique in the approximate comparison of pairs within the context of multi-criteria decision methods; both complement each other, since the AHP methodology makes it more consistent and reduces the redundancy of the ANP, which has the disadvantage of disregarding mutual relationships between criteria, which the ANP tool adjusts for. However, these two tools are not recommended for high-dimensional multivariate data, also known as big data [74].

Formulating the sustainability index prior to and before applying the AHP and ANP tools, the authors in the literature carry out a SWOT analysis, which consists of assessing the strengths, weaknesses, opportunities, and threats in a matrix to which a project may be subjected at all stages from conception to operation [75]. Thus, by carrying out this characterization prior to execution, the aim is to strengthen the aspects that are most susceptible to external and internal interference and reduce the associated risks that could make the process unfeasible so that one or more AI techniques can then be configured and ranking can be applied, such as TOPSIS, according to the type of data and intended analysis [76].

Smart electric railway networks play a pivotal role in modernizing and optimizing public transportation systems while minimizing their environmental footprint. The research presented by [77] examines the methodologies utilized to design and implement energy-management systems in these networks to ensure efficient energy usage and reduced operational costs. Their study emphasizes the need for a holistic approach that integrates these technologies seamlessly into energy management systems.

Tung et al. [78] investigate the application of waste heat recovery technologies in the context of fishmeal production plants, focusing on their potential to enhance energy efficiency and mitigate environmental impacts. The case study demonstrates the significant energy efficiency improvements achieved through the adoption of waste heat recovery technologies. By capturing and reusing waste heat, the fishmeal production plants can reduce their overall energy consumption, leading to operational cost savings and decreased reliance on conventional energy sources.

Microgrids, which are localized energy systems that incorporate distributed energy resources, have gained prominence as a means to enhance energy resilience and reduce environmental impact. However, the dynamic and decentralized nature of microgrids poses complexities in managing energy supply and demand. To address these challenges, Hamidi, Raihani, and Bouattane [79] proposed a multi-agent system as an intelligent solution that enables autonomous decision making within the microgrid ecosystem. By utilizing the proposed system, the microgrid can optimize energy allocation, storage, and distribution in real time. This contributes to efficient load balancing, peak demand reduction, and integration of renewable energy sources.

Power Grid Reliability

Focusing on reducing losses in electrical energy transmission, Klaar et al. [80] propose a hybrid machine learning approach to identify faults in insulators of power grids and alert the electric utility company about possible faults. This evaluation is based on the time series of leakage current, which is an indicator that a fault may occur [81]. In [82], the time series of ultrasound is evaluated, and in [83] the number of faults is evaluated, with the same goal.

According to Stefenon et al. [84], there is a major effort to identify faults in power grids before shutdowns happen since the maintenance becomes more costly and satisfaction levels are reduced with the lack of energy. Other strategies to keep the electricity running and reduce losses caused by shutdowns are visual inspection [85], the analysis of the contamination [86,87], the estimation of weather variation [88], and the optimization of the design of the equipment such as grid spacers [89] or insulators.

Accurate forecasting of renewable energy generation is essential for effective energy management and grid integration [90]. Zhou et al. [91] propose a novel forecasting model that combines the strengths of the dynamic accumulation method and grey seasonal model to enhance prediction accuracy. Their model showcases its efficacy in accurately predicting generation patterns of renewable energy across different time horizons, thus aiding in optimal energy resource allocation and grid stability.

Sauer et al. [92] presented research using historical energy-consumption data from residential buildings, considering variables such as weather conditions, occupancy patterns, and appliance usage. The XGBoost model, known for its robust predictive capabilities, is integrated to capture intricate relationships and patterns within the data. By effectively forecasting energy consumption in residential buildings, the proposed approach empowers homeowners, energy managers, and policymakers to make informed decisions regarding energy usage, demand response strategies, and overall energy efficiency improvements.

By amalgamating historical load data, meteorological conditions, and other pertinent variables, the cooperative ensemble model proposed by Ribeiro et al. [93] effectively optimizes the combination of individual forecasts. This model holds promise for facilitating improved energy-management strategies, bolstering grid stability, and enabling better-informed decision making in the field of electric power systems.

In the work of Silva et al. [94], an equivalent approach is proposed to multi-step short-term wind speed forecasting, holding promise for optimizing the integration of wind energy into power systems, facilitating energy resource allocation, and supporting informed decision making in the renewable energy sector. To determine whether sustainability is achievable, some indicators are used; these topics are discussed in the next section.

4. Discussions: Sustainable Development Index and Indicators

The objectives of sustainable development are interconnected and have as one of their fundamental requirements the elaboration of energy policies that enable the generation of sustainable electricity and that can be ranked from the formulation of national and/or international indexes generated from a series of data and indicators [95]. This can be carried out through operations with the statistical analysis and aggregation of an index composed of different indicators previously chosen [96].

There is a relationship between the dimensions of sustainability and their resources. In Figure 2, the environmental (ENV), economic (ECO), social (SOC), technical (TEC), and institutional (INS) dimensions are placed with their source, and the interconnection between the dimensions is presented in gray. For each of the dimensions, there are indicators that will be further discussed in this section.

Sustainability Indicators

The indicators have scores characterized by relevance, contextual sensitivity, and robustness, where they can combine and produce distinct indices at the municipal, state, or country scale concerning the quality of electricity, low carbon financing, and social effects such as job creation and acceptability of technology by society [97]. There are several indicators that are used to evaluate the levels of sustainability; some variables and indicators are shown in Table 1.

Regarding the relationship between consumption and quality of energy produced, the factor of the human development index (HDI) is considered an indispensable precedent and significantly related to the volume of energy consumption per person and is a determinant in the strategies that can be adopted according to socioeconomic development associated with government regulation; traditionally, in higher income countries, these strategies are the established investments and promotion of a safer and environmentally friendly energy market [103].

When the HDI is incorporated into the joint assessment of the management of the electricity matrix, equity in energy access, environmental sustainability, and energy security, the formation of the scope contained in the energy sustainability index provided by the World Energy Council of the analyzed region is obtained [103].

Considering the environmental, economic, social, technical, and institutional dimensions and giving the description of indicators to measure sustainability, the significance of each indicator is presented in Table 2.

These indicators are used to evaluate the level of sustainability for the considered dimensions. These indicators are calculated as follows:

(1)$TEC1=\frac{TNR}{TFC},TEC2=\frac{TRE}{TPES},$

(2)$ECO1=\frac{TPES}{GDP},ECO2=\frac{GDP}{Pop},$

(3)$SOC1=\frac{REC}{Pop},SOC2=GINI,$

(4)$ENV1=\frac{ARH}{TFC},ENV2=\frac{TC{O}_2}{TPES},$

(5)$INS1=\frac{TPES}{TFC},INS2=\frac{GDP}{TFC}.$

To apply the indicators, it is necessary to normalize them to have a standard parameter for comparisons. There are some indicators that have used by the same authors, which is because there is a relationship between indicators. In Table 3, a matrix of these relationships is presented.

Any index of a regional, national, or international nature requires interpretation prior to its application in order to establish a reliable characterization, verifying that additional indicators can be included and that it meets the prerequisites designated by the targets previously established in governance plans. Subsidies and guarantees are critical factors within developing countries and can be considered as additional indicators to measure their importance quantitatively and qualitatively [113].

Besides all indicators having a relation to the indicators of the same dimension, some of them have an additional relationship with other dimensions, which highlights the statement previously discussed in the introduction section regarding the interconnection between the sustainability dimensions. A complete discussion about the relevance of each indicator and the ones that are related is presented in Table 4.

Following the evaluation, in Table 5, some limitations and possible solutions for each of the indicators are discussed. These limitations highlight how important it is to evaluate sustainability based on more indicators to have a wider view of how dimensions are needed to have sustainability.

The determination of the weights of each indicator, especially when there is a large number of them, becomes one of the biggest problems in the aggregation of multiple-criteria decision analysis, so it is recommended to use the criteria of the local energy policy within computational resources in the literature, such as statistical tools, data envelopment analysis, the method of organizing, and the ranking of preferences in order to carry out the enrichment of evaluations, which can collaborate in reducing the difficulty or subjectivity proposed in the creation and methodological development of an environmental performance index of the energy generated in each project. In addition, this computational and human analysis should be established in different scenarios proposed preliminarily, and sensitivity analyses will be designed after obtaining data [174].

When structuring different variables in the analysis of indices, one can seek to evaluate the correlation and dependence of two series via a cross-validation model that collaborates in the understanding of the established conditionals and in the analysis of the generated curves determining what the dependent and independent variables are [175]. By verifying different biomass electricity-generation technologies using this tool, aided by green total productivity factors through a hierarchical analytical process, it is possible to verify which of the alternatives are the most and least cost-effective in the economy, as well as which have the greatest and lowest emission of greenhouse gases or pollution at the local level and whether the technological innovation that has less polluting character is justified and what maximum investment limit must be met [176].

Next, we draw conclusions about which is the best technological alternative according to the local justification, if there is a need for environmental improvements to the technology with the best cost-effectiveness, or if the necessary burden of investment and fiscal benefit of technological innovation has the best benefit in the short, medium, and long term, so that both achieve the same relationship between the economy and the environment from different energy sustainability indexes. In addition, we establish the barriers that must be overcome and the reasons for the cost difference between the technical aspects that increase the cost of the innovation produced and analyze the cost-effective performance of each technological solution in different countries analyzed and different policy regiments [177].

5. Conclusions

The sustainability concept focusing on energy is a critical and multifaceted approach that recognizes the importance of preserving and efficiently utilizing our planet’s finite resources. As we continue to witness the escalating challenges posed by climate change and resource depletion, it has become increasingly evident that our current energy practices are not sustainable in the long term.

By shifting toward renewable and clean energy sources, such as solar, wind, hydro, geothermal, and bioenergy, we can significantly reduce greenhouse gas emissions and curb the detrimental impact of fossil fuels on our environment. Embracing sustainable energy solutions not only mitigates the effects of climate change but also fosters energy independence and resilience, as these sources are naturally replenished and less susceptible to geopolitical tensions.

Integrating sustainable energy practices into our daily lives and industries promotes economic growth and job creation. The transition to clean energy technologies and infrastructures opens up new avenues for innovation and investment, stimulating green industries and green-collar employment opportunities. Energy efficiency used as a daily practice, for instance, reducing the consumption of air conditioning, has an impact on the preservation of natural resources and a reduction in the emissions of pollutants. From a national perspective, this results in lower fuel prices (combined with public policies) and improved air quality. From an international perspective, energy sustainability reduces a country’s energy dependency and improves its ability to manage the value passed on to public or legal entities.

Based on the text and the research question presented in this paper, it can be concluded that the use of renewable energy sources, the application of sustainable energy policies, and the integration of energy efficiency measures are crucial factors in achieving long-term viability and alignment with sustainable development goals in the energy sector. This article highlights the importance of transitioning to renewable and clean energy sources, reducing environmental impacts, and promoting energy efficiency to create a more sustainable energy future. The indices and indicators presented serve as a basis for learning about society, the economy, the environment, institutions, technologies, and the interactions between these areas. When carefully chosen and communicated effectively, they can provide information in a politically neutral way and contribute to engaging government and citizens in a shared debate about the meaning of sustainability and energy, with the ultimate aim of developing public policies in favor of sustainable development.

The concept of sustainability in energy also entails energy efficiency, which involves optimizing our energy consumption across various sectors. Implementing energy-efficient technologies and practices, such as smart grids, energy-efficient buildings, and industrial processes, can significantly reduce energy wastage and enhance overall system performance. However, achieving a sustainable energy future requires collaborative efforts on a global scale. Governments, businesses, communities, and individuals must work together to prioritize and implement sustainable energy policies, promote research and development about innovative technologies, and engage in responsible energy consumption habits.

Embracing the sustainability concept focusing on energy is not merely an option but an imperative for the well-being of current and future generations. By committing to sustainable energy practices, we can create a cleaner, healthier, and more prosperous world while safeguarding the planet’s natural resources for the benefit of all life forms. It is a collective responsibility and a beacon of hope for a brighter and more sustainable future.

Author Contributions

Writing—Original Draft Preparation, R.N.M. and W.G.B.; Writing—Review and Editing, Supervision, C.T.d.C.J., A.N. and G.V.G. All authors have read and agreed to the published version of the manuscript.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

In special thanks to the researchers Da Rocha, B.R.P.; De Sá, J.A.S. and Stefenon, S.F. for their fundamental contribution throughout the research, which had an assertive influence on the progress of the work.

Conflicts of Interest

The authors declare no conflict of interest.

Footnotes

Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Figures and Tables

Figure 1. Interconnection of sustainability dimensions.

Figure 2. Dimensions and indicators of sustainability.

Table 1

Variables and indicators used to assess sustainability.

Data	Acronym	Unit	Source
Area of reservoir of hydroelectric plants	ARH	km${}^2$	[98]
Distribution of income across a population	GINI	-	[99]
Gross domestic product	GDP	Currency	[99]
Population	Pop	Inhabitants	[99]
Residential energy consumption	REC	GWh	[100]
Total CO${}_2$ equivalent emission	TCO${}_2$	tCO${}_2$eq	[101]
Total final consumption of energy	TFC	GWh	[102]
Total non renewable energy generation	TNR	GWh	[100]
Total primary energy sources	TPES	GWh	[100]
Total renewable energy generation	TRE	GWh	[100]

Table 2

Indicators purposes and your references.

Indicator	Significance	Purpose	References
TEC1	Dependence on fossil fuels	Measures the rate of consumption of sources in relation to total final consumption.	[104].
TEC2	Renewable generation	Measures the rate of renewable generation to total primary generation.	[105,106].
ECO1	Energy intensity	Measures the use of primary energy needed to generate one unit of GDP.	[107,108].
ECO2	Economic productivity	Measures productivity per inhabitant.	[104,108].
SOC1	Social use of energy	Measures residential energy consumption per inhabitant.	[107,109,110].
SOC2	Social inequality	Considerated GINI Income Inequality Index.	[107,111,112].
ENV1	Energy deforestation	Measures deforestation due to energy generation generation.	[104,107].
ENV2	Carbon intensity	Measures carbon emissions from generation and waste disposal.	[107].
INS1	Energy security	Measures the rate of dependence on the import/export of energy.	[105].
INS2	Energy productivity	Measures the rate of energy consumption to produce one unit of GDP.	[104].

Table 3

Relationship matrix between indicators.

Indicator	TEC1	TEC2	ECO1	ECO2	SOC1	SOC2	ENV1	ENV2	INS1	INS2
TEC1		x	x			x	x	x	x
TEC2	x			x	x					x
ECO1	x	x		x	x			x		x
ECO2			x			x	x	x		x
SOC1		x	x	x		x	x	x		x
SOC2			x	x	x					x
ENV1	x	x		x	x			x	x
ENV2	x		x		x		x			x
INS1	x	x	x	x		x	x			x
INS2		x	x	x	x			x	x

Table 4

Relevance to the sustainability of indicators.

Indicator	Relevance to Sustainability	Related Indicators	Ref.
TEC1	The greater the dependence on fossil fuels for energy generation and consumption, the lower the region’s degree of sustainability, because the burning of fossil fuels has a direct impact on atmospheric greenhouse gas emissions.	ENV1, ENV2, INS1, TEC2, ECO1, SOC2	[114,115].
TEC2	Having a large share of renewable energy sources in its energy matrix points to greater sustainability due to the advantages of using renewables, promoting a lower carbon intensity in energy generation. There is greater institutional energy security if the renewable source is hydroelectric (a non-intermittent source) and lower energy intensity in final energy consumption.	ENV1, ENV2, INS1, TEC1, ECO2, SOC2	[116,117,118].
ECO1	Increasing energy efficiency in the economy, via the reduction in intensity, results in an increase in the useful life of energy resources with the promotion of the profitability of productive sectors. It becomes possible to produce more resources with the same amount of GDP. This makes a given region/state more productive and consequently more energy-sustainable, which can result in a postponement of investments to expand the energy supply.	ECO2, ENV2, TEC1, TEC2, SOC1, INS2	[119,120,121].
ECO2	Increases in the production of goods and services are a basic indicator of an economy’s behavior correlated with sustainable development. The economic productivity of a nation, region, or state has a direct influence on energy generation since an increase in production requires an increase in the availability of energy. Extracting natural resources to transform them into consumer goods involves intensive use of energy, which is why it has a direct connection with energy intensity.	ENV1, ENV2, ECO1, SOC1, SOC2, INS2	[122,123,124,125].
SOC1	Energy consumption per inhabitant is associated with a country’s level of economic and social development of a region. A higher per capita consumption generates more social development. However, this puts greater pressure on the environment with natural resources due to the extraction of raw materials. On the other hand, limiting the use of energy causes a major institutional risk, especially in developing countries, which need to increase energy consumption to elevate social productivity.	ENV1, ENV2, ECO1, ECO2, INS2, TEC2	[126,127,128,129,130].
SOC2	This is an important indicator for policies to combat and reduce social inequalities, and it measures the differentiated appropriation of income by individuals and social groups. It is also used to monitor the social acceptance of access to energy as electricity is lacking in societies with low development and standard of living.	SOC1, ECO2, ECO1, INS2	[131,132,133,134,135].
ENV1	Any damage to the forest certainly compromises its environmental sustainability. In the case of hydroelectric power generation, which is a renewable source, it nonetheless causes a socio-environmental impact at the time of installation and start-up. On the other hand, it has the advantage of not causing further plant extraction over the years of its operation, which is equivalent to a fixed deforestation rate.	ENV2, ECO2, SOC1, INS1, TEC1, TEC2	[136,137,138,139].
ENV2	This final disposal includes solid waste sent to sanitary landfills, controlled landfills, and open dumps. Basic sanitation in Brazil is still very precarious, with a large number of municipalities still operating open dumps, which contributes considerably to emissions of greenhouse gases such as methane. Methane has an impact of up to 28 times more carbon equivalent compared to carbon dioxide.	ENV1, ECO1, SOC1, INS2, TEC1	[140,141,142].
INS1	Increasing energy security implies diversifying energy sources and reducing dependence on energy imports. Regions with low energy self-sufficiency rely heavily on imports, which leads to low energy sustainability in the institutional dimension, as they are not able to guarantee the supply of energy demand.	INS2, TEC1, TEC2, ENV1, ECO1, ECO2, SOC2	[143,144,145,146].
INS2	The more productivity a region has, the more sustainability, as it will need to consume fewer natural and energy resources to produce the same amount of GDP units. The base indicator shows the efficiency of a given region’s primary energy-conversion technologies. Low conversion efficiency means that more natural resources are needed to meet the same level of useful energy demand, which is required for high efficiency.	INS1, ENV2, ECO1, ECO2, SOC1, TEC2	[147,148,149,150,151,152].

Table 5

Indicators, limitations, and solutions found.

Indicator	Limitations	Solutions Found	Ref.
TEC1	Localities have low consumption of fossils at the same time that they do not have renewable generation, due to the fact that they are importing states’ power.	The energy security indicator, which measures dependence on energy import/export, was used together.	[153,154].
TEC2	Increase in the rate of deforestation due to hydroelectric reservoirs. Institutional energy insecurity in the case of renewable generation, having a large share of intermittent sources such as solar and wind.	No solution was found for these limitations.	[155,156,157].
ECO1	Affected by economic cycles, production structure, and energy-intensive economic activities such as aluminum production. This would lead to an increase in the indicator, even with improvements in energy consumption in each sector.	No solution was found for these limitations.	[158].
ECO2	Even if it has a good application to measure the development level of a region, it is insufficient to express the degree of social well-being, particularly with regard to inequality in income distribution.	This indicator is used in association with the GINI index, correlated with energy consumption for GDP production (energy intensity) and the social use of energy.	[159,160].
SOC1	Commercial and industrial uses of energy are not included in the calculation of this indicator. The focus of its measurement is social energy consumption.	This indicator is integrated with the increase in energy productivity and promotes the use of renewable sources., reducing the pressure impact on ecosystems used for energy generation.	[161,162].
SOC2	As a measure of inequality calculated through a ratio, it has some limitations regarding interpretations of what is measured. When comparing poor or rich regions or states, it can both measure inequality in the material quality of life and the distribution of luxury beyond basic needs. It gives rise to different results.	Associated with this indicator is the social use of energy, measuring the energy consumption of the population of each state/region.	[163].
ENV1	One limitation is when thermal energy generation is for fossil resources, because this indicator calculates biomass deforestation for energy.	Results are associated with greenhouse gas emissions due to energy generation, which shows the equivalent carbon emissions from reservoirs and fossil thermal generation.	[104,164].
ENV2	Equivalent carbon intensity is limited to power generation and the disposal of solid waste. Emissions are not included in the calculation of the base indicator due to industrial, commercial, and other activities of the productive chain outside energy generation and solid waste disposal.	No solution was found for these limitations.	[165].
INS1	It does not consider other important factors such as the conservation of natural resources. This can cause a region, state, or nation that has high energy security but still has low sustainability.	This indicator needs to be integrated with others in order to minimize these limitations.	[166,167,168,169,170].
INS2	Energy productivity does not consider the quality of the product or service generated, nor what makes a region, state, or nation have a high energy productivity. Even if it produces low-quality consumer goods, it can lead to a long-term decrease in sustainability.	No solution was found for these limitations.	[171,172,173].

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