1 Introduction

The increased use of fossil fuels in the past decades has raised questions over the exhaustion of fossil resources in near future (Chandel et al. 2016). According to the prediction of the World energy forum, less than 10 years are available for the exhaustion of fossil-based fuels—Coal, Oil, and gas (Ritchie and Roser 2020). India ranks fourth in carbon emission production after, China, the USA, and the European Union, with the energy sector responsible for contributing nearly half of it in India (Chandel et al. 2016). In India, 74.456% of energy came from fossil fuels (Ritchie and Roser 2020). India’s average per capita consumption of energy is higher than that of developed countries and is anticipated to aggravate more due to rapid industrialization and expected economic growth (Sen et al. 2016). The population explosion in India has led to the scarcity of fossil fuels. Consequently, energy shortages will be faced by India due to the rise in energy prices and energy insecurity over the coming decades (Varun and Singal 2007). The depletion of natural resources and the rising demand for conventional sources of energy have forced policymakers to look for alternate, sustainable resources (Kumar et al. 2010). Thereby arises the need for the sustained high growth of the economy at the rate of 8–10% every year for the next 25 years (IEP 2006). To achieve this growth a very significant amount of diversification is required in the energy system, but unless some dynamic changes are made to the sector to become greener, it would be difficult to be sustainable in the long run (Bhattacharyya 2010).

The best alternative is renewable energy, the one which we have in abundance and is inexhaustible should be utilized in full capacity by the Energy sector. Renewable energy helps to reduce carbon emissions on our planet and move a step forward toward sustainable development (Kumar et al. 2010). Carbon emissions are the emissions that are stemming from burning of fossil fuels like coal, one of the main input in generating electricity as they include carbon dioxide, methane, sulphur dioxide and other harmful gases which are the major drivers of climate change due to global warming. Many sustainable policies have been framed to promote renewable energies both at the national and international levels (Varun and Singal 2007). However, there are many challenges that the energy sector needs to overcome to focus on green energy. Prior studies have discussed the barriers to sustainability in the energy sector based on major indicators. A study by Bhattacharyya (2010). Claimed that supply management, managing energy investment projects effectively, resource management, and environmental and social responsibility management reflect the major management challenges faced in the energy sector in implementing sustainable energy. An entrepreneur faces cost barriers, bureaucratic obstacles, unavailability of skilled labor, and technological challenges to run a sustainability-driven venture (Haldar 2021). Wing energy-based power-producing technologies face industrial and policy development challenges as reported by Sitharthan et al. (2018). High upfront investments, corruption, and lack of long-term planning are some of the barriers stated by Engelken et al. (2016) to sustainable business model barriers. Shifting to Solar PV technology includes international barriers with a high initial cost, Wind energy technology includes challenges like the expiration of the Generation Based Incentive scheme, inadequate grid infrastructure, Biofuel industry faces challenges in terms of, dependency on sugarcane molasses, kerosene subsidies, and shortage of ethanol supply are some of the barriers (Tagotra 2017). In reality, it is hard to determine a viewpoint and conclusion from quantitative information, as linguistic ambiguity leads to deviation in the understanding of linguistic preferences (Bui et al. 2020). From the above-stated research gap by Bui et al. (2020), the following research questions need attention from the decision-makers:

  1. (a)

    What are the prominent challenges that are hindering the sustainability performance of the Energy sector?

  2. (b)

    How these challenges can be shortlisted for a closer focus on enhancing the sector’s performance?

In this context, the current study examines the prominent challenges from literature. This study utilizes the Fuzzy Delphi method (FDM) to demystify the sustainable challenges in the energy sector. The rest of the study is divided as follows: Sect. 2 outlines the methods in detail. Section 3 describes the analysis of data. The results of the fuzzy set theory are discussed in Sect. 4. Lastly, the limitations and future scope of the study are presented in Sect. 5.

2 Review of literature

In an examination by Chu and Majumdar (2012), extensive literature review has been done to analyse the opportunities and challenges for a sustainable energy future. Making use of eco-friendly and efficient energy sources is a necessary component of ensuring the sustainability of energy to benefit both current and future generations. Streimikiene and Siksnelyte (2016) assessed which electricity market organization systems are the best using sustainability criteria as a guide where the sustainability of the power industry in various developed nations was found to benefit from the liberalization of the electricity market. The economic and technical viability of wind power systems was studied by Morea and Poggi (2017) and found that it can be achieved by the advantages of using Shari'ah-compliant Sukuk instruments and their applicability. Rösch et al (2017) studied the indicators required for political decision-making to effectively address sustainability aspects of the energy system and its transition. It also seeks to advance existing indicator systems, where using the indicator system in the right way can help with the development of resilient political strategies. An in-depth examination of the current state and prospects of Bangladesh's renewable energy sector was presented by Hil Baky et al (2017). Spanish energy policies and their implications for sustainable energy development were focused on by Gabaldón-Estevan et al. (2018). Lata-García et al (2018) aimed to discover and evaluate the degree of integration and performance of alternative clean ways of producing electricity into the country's energy system, the findings of this study demonstrate that the administration's actions over the past sixteen years have conformed with the principles outlined in the strategic planning for the decade from 2013 to 2022. A Renewable energy sustainability index designed by Cîrstea et al. (2018) revealed that by enhancing positive effect indicators and reducing negative impact indicators, the suggested index can offer strategies to boost a country's sustainability. Sitorus and Brito-Parada (2020) ranked the sustainability criteria of renewable energy technologies under uncertainty using a multi-criteria decision-making method. A Sustainable hybrid renewable system to reduce carbon emissions in Iran was investigated by Razmjoo et al (2021) where appropriate implementation of policies of new enabling technologies and investments in renewable energy resources were found to be useful indicators to reduce the emissions. A study by Ahmad et al. (2021), shows Artificial intelligence is the future magic tool in replacing the traditional methods and improving the operational energy efficiency.

Based on the findings, multiple sector-specific challenges were encountered in implementing sustainability. Anuar and Abdullah (2016) identified feedstock, environmental issues, waste glycerol glut problem, product commercialization, and acceptance by society as the major barriers to the biodiesel industry. Solar manufacturing challenges identified by Sahoo (2016) in India were reliance on imported wafers for the production of cells, high cost of capital and finance, competition with Taiwan and China, Low demand, and a lack of technical expertise, particularly in the upstream sector. Financial challenges were also identified as a key factor in the implementation of sustainable development goals in Africa by Schwerhoff and Sy (2017). The development of the alternative and renewable energy sector and the implementation of energy efficiency projects in Azerbaijan are impeded by visible hurdles such as institutional operation, expensive renewable energy plants, and other economic and policy barriers (Vidadili et al. 2017). Despite the significant problems associated with the use of coal, such as the emissions of greenhouse gases and air pollutants like sulfur dioxide (SO2) and carbon dioxide (CO2), coal has remained a very important commodity in South-East Asia as a whole as well as Malaysia's energy supply (Oh et al. 2018). Challenges identified by Ugwu et al. (2021) in Nigeria includes insufficient infrastructure, contradictory government regulations, and enormous metering gaps.

3 Research methodology

India alone negatively contributed, 1.8 metric tonnes of per capita carbon emissions in 2018 (World Bank 2018). The energy sector contributes the most to it, with India still producing 85% power from coal. Even though modernization and industrialization have catered to many businesses, it has also raised the opportunity cost of negative environmental impacts. With the growing population in India, and to keep pace with the global economy, the power demand is mounting (Pathak et al. 2016). So, it’s important to implement synchronous solutions that would be more sustainable.

This study helps to demystify the sustainability challenges that result in the negative performance of the Energy sector. To search relevant literature, we have explicitly typed the combination of words such as: ‘Sustainability + Energy sector’, ‘Sustainable energy + implementation challenges’, Sustainability + MCDM’,’ Sustainable energy + Fuzzy Delphi method’, and ‘ Energy sector + carbon emissions’ on Scopus, web of science and google scholar to get the required data. This session discusses the identification of challenges and addresses the proposed Fuzzy Delphi method.

3.1 Identification of challenges

The decision-makers include 10 experts, 2 academicians, and 8 experts from the energy sector. All the experts have extensive knowledge and experience in the Energy sector, in India. The details of the decision-makers are given in Table 1. Evaluation of linguistic terms for fuzzy set theory is given in Table 2

Table 1 Experts who participated in the decision-making process
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Table 2 Evaluation table for FDM
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Evaluation of linguistic terms for fuzzy set theory is given in Table 2

3.2 Fuzzy Delphi method (FDM)

Delphi is a method developed by Dalkey and Helmer (1963) where expert comments and feedback are taken after several discussions with them. A formal communication strategy or technique which was first imagined as a systematic, interactive predictive process based on an expert panel, is built on an expert opinion survey with three features: unnamed responses, monitored input iterations, and statistical responses by group (Mabrouk 2020). The method has been applied to several areas, including industrial quality evaluation, investment decisions, production prediction, etc. (Dong and Huo 2017). The judgments of the decision-maker are generally subjective, quantifying the same using crisp numbers is a tedious task, thereby paving the way for fuzzy set theory. A study by Wang et al. (2019), demonstrated that the Fuzzy Delphi process relies on an exchange of information to produce subjective determinations based on the objective judgments of various experts. Alternatively, the robustness of FDM lies in the fact that to achieve consensus, experts’ opinions are considered and integrated thereby reducing investigation times and decision-making costs (Kuo and Chen 2008; Lee et al. 2018; Padilla-Rivera et al. 2021). Therefore, the uncertainty of the survey process can be resolved by collective expert judgment when the fuzzy set theory is integrated into the conventional Delphi approach, which entails multiple survey rounds to obtain acceptable decisions. Additionally, it would be able to speed up the surveying procedure (Md Hashim et al. 2022).

The challenges proposed for measurement are presented in Table 3. According to expert p, attribute q has a significant value as stated by O = (\({l}_{pq}\);\({m}_{pq}\);\({n}_{pq}\)), where p = 1,2,3,…….,y; q = 1,2,3,…….,z; then weight \({O}_{q}\) of element q is \({O}_{q}\)= (\({l}_{q}{;m}_{q;}{n}_{q)}\), where \({l}_{q}\) = min(\({l}_{pq}\)), \({m}_{q}\)=\({(\prod_{1}^{y}{m}_{pq})}^{1/y}\), and \({n}_{q}\) = max(\({n}_{q}\)). Then, the fuzzy numbers and linguistic terms are converted into linguistic values. Convex combination \({G}_{q}\) is generated by the following equations and are created by adding a \(\beta\) cut to reach the result (Bui et al. 2020; Wu et al. 2016).

$$x_{q} = n_{q} - \beta (n_{q} - m_{q} ),{\mkern 1mu} {\mkern 1mu} w_{q} = l_{q} - \beta (m_{q} - m_{lq} ),\quad q = 1,2,3, \ldots ,z$$
(1)
Table 3 FDM Phase 1—screening out attributes
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Generally, \(\beta\) is denoted by 0.5. It ranges between 0 and 1 according to negative or positive expert opinions.

The exact value of \({G}_{q}\) can be generated using the following equation:

$$G_{q} = \int {(x_{q} ,w_{q} )} = \gamma \left[ {x_{q} + (1 - \gamma )w_{q} } \right]$$
(2)

where \(\gamma\) describes the positive opinion of the expert and helps in attaining an equilibrium among all the expert judgments.

Then \(\delta\) = \(\sum_{p}^{y}({G}_{q}/y)\) serves as the key to filtering out the required attributes. If \({G}_{q}\ge \delta\), then attribute q is accepted, else rejected.

3.3 Data analysis

This study is focused on 113 challenges i.e., the initial set of challenges proposed in Table 3 which was collected from literature reviews and decision-makers. Post evaluation, the scaling is done by the decision-makers based on linguistic terms and their corresponding fuzzy numbers given in Table 2. Further, these challenges are refined using FDM, which has been divided into two phases. In the first phase, accepted attributes have been screened out in Table 3 using Eqs. (1) and (2) with threshold \(\delta\) = 0.329.

Based on this result, a questionnaire is circulated for additional assessment and used as an input for FDM Phase 2. 47 challenges are accepted and renamed as Phase 1 set, Using the same equations, the barriers are further screened in Table 4 with threshold \(\delta\) = 0.436.

Table 4 List of FDM—Phase 2 Screening out Attributes
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Based on this result, a final set of challenges is prepared and renamed in Table 5.

Table 5 List of final challenges
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Five of the biggest challenges are ranked from most to least important according to their weights and are further studied for implications. The problems are Political Interference (FC14), High investments in transmission and distribution networks (FC3), Lack of flexible generation capacity (FC7), Interprets interventions effects and time lags differently (FC5), and Lack of grid expansion (FC10).

4 Results and discussion

The final result indicates that Political Interference (FC14), is the most important issue in implementing sustainability in the energy sector. Excess political interference has slowed down the implementation of many political reforms in the energy sector.

A study by Kwakwa et al. (2021) found that the effort to lessen the causes and effects of climate change, the political system of a nation has a considerable impact on the quality of its institutions, and concluded that there is a positive influence between political regime and access to clean fuelss reported by Bhattacharyya (2010) the reduced state funding and inadequate mobilization of private capital widened the gap between planned and actual capacity expansions, worsening the country's demand–supply imbalance. In India, electricity losses tend to spike right before state assembly elections, and agricultural price subsidies rise dramatically in the year leading up to an election (Verma et al. 2020). Also, private sector engagement in renewable energy projects is hampered by a lack of power and delays in clearances and allotments for private sector projects (Mirza et al. 2009). To achieve efficiency in the energy industry, stable, strict, long-lasting reforms and single window clearance systems must be introduced immediately. The High investments in Transmission and Distribution networks (FC3) have led to poor performance in the energy sector. Renewable energy developers may find themselves in a disadvantageous situation due to intermittent generation characteristics of renewable technologies and their site-specific nature in terms of power transmission contract structuring, the site-specific character of renewables is a disadvantage for some transmission pricing schemes that are based on distance (Mirza et al. 2009). As per, Mani and Dhingra (2013) Transmission infrastructure costs for offshore wind farms are very high, as sub-sea cabling requires superior engineering skills. So, the government should bear these expenses and recover the cost by a small increase in the tariff. The Lack of flexible generation capacity (FC7) generates similar concerns. Storage, connectivity, demand-side response, and fast-acting generators can all be used to increase operational flexibility (Das et al. 2020). The lack of incentives for flexible generation capacity makes securing energy supply at all times a major concern, especially when certain technologies are phased out at the same time (Papadis and Tsatsaronis 2020). Thus, the need for economically sustainable technologies arises. Interprets interventions effects and time lags differently (FC5) is another challenge in the implementation of sustainable energy. Time lags between treatments and their effects are underestimated, which leads people to mistakenly believe that there is a lack of response and so a need for stronger interventions, which leads to overcorrection that needs to be corrected (Seadon 2010). When implementing complex regulations, there is ambiguity, which makes it difficult to foster teamwork and leads to a pricey, drawn-out, and challenging governmental approval process. Therefore, superfluous law hinders symbiotic transfers and limits beneficial environmental activities.

Lack of grid expansion (FC10), where the supply needs to keep up with the growing energy demand. For a successful energy transition to take place, innovative sustainable technologies need to be adopted to increase the supply and overcome the challenge. It would also help to generate electricity cost-effectively in rural areas as well.

5 Limitations

Nevertheless, limitations exist. First, this study is in its preliminary stage and needs to be more elaborated to attain a holistic approach. The extension of which will be forwarded in future studies. Second, this study is reliable on the decision maker’s judgments, hence in further studies more Multi-criteria decision-making techniques will be adopted to attain more technical validity. Third, more number decision-makers could be contacted to get more reliable results.

6 Conclusion and recommendation

The overexploitation of fossil fuels by the energy sector has led to not only its exhaustion but also raised many environmental concerns. Hence, this study aims to demystify the challenges to sustainability in the energy sector. A set of 113 barriers are stated and analyzed using FDM. Fuzzy set theory helps to transform the quantitative data by experts into qualitative linguistic terms. This study identified political interference, high investments in transmission and distribution networks, lack of flexible generation capacity, Interprets intervention effects and time lags differently, and Lack of grid expansion as the most important challenges that hinder the performance of sustainability in the energy sector. Therefore, it is recommended that necessary policies to be taken by the government regarding technology, investments and administration for combating the challenges for the implementation of sustainable energy.