Renewable Energy for Sustainable Growth Assessment. Группа авторов
government has also exempted the inter-state transmission charges for wind projects to be commissioned by March 2022.
2.2.4 Solar Power
India has emerged as a leader in promoting the set up of a solar-based economy worldwide and is ranked 5th in the installed capacity of solar PV at a global level. The potential of solar power in India is predicted to be 750 GW considering that 3% of wasteland land in the country is available [18]. India launched the Jawaharlal Nehru National Solar Mission (JNNSM) on 11th January 2010, and since then a large-scale boom has been observed in the solar PV sector. Concentrated solar power (CSP) is also an important technology. However, the high cost of CSP seems to be a significant hurdle in promoting CSP. Research is in progress to develop economic CSP technologies [21].
Further to bring down the tariff of grid-connected solar projects significantly, a competitive bidding process is used which involves reverse e-auction. CFA is also provided for the grid-connected rooftop solar program under JNNSM Phase II [22]. Like wind projects, the charges applicable for inter-state transmission have also been exempted by 2022 for solar projects.
2.2.5 Bioenergy
In an agriculture-based economy like India, bioenergy has a rich potential of about 25 GW [17, 23], which includes biomass power, bagasse cogeneration, and energy recovery from urban and industrial waste. Bioenergy is an important RE technology based on various by-products from the forest, agriculture, animals, and humans, e.g., firewood, bagasse, crops residue, animal dung, agriculture-based industries’ waste, and waste from various human activity [24]. The bioenergy technology ranges from mature and economical alternatives, like the combustion of forest and agricultural residues, to less mature and/or high-cost alternatives, like biomass gasification or municipal solid waste generators with stringent emissions controls. The adoption of biomass power and bagasse cogeneration-based methodologies in India has been encouraged through various programs and providing various subsidies and incentives [23, 25, 26].
2.3 Impact of COVID-19 on RE Sector in India
The year 2020 was an unprecedented period due to the COVID-19 pandemic that resulted in multiple challenges. The pandemic hit the world when sustainability had started to gain significance in the energy sector [27]. India is expected to be the largest contributor to the renewable uplifting in 2021, but like other sectors the COVID-19 pandemic has also affected the RE sector. During the pandemic several collateral damages took place to this booming RE sector. Sudden lockdown and closures of industries and railway transport led to a gap of about 40% in the energy demand within the nation. The sudden drop in the power demand was linked with the restrictions on generation, leaving renewables, with their often-fluctuating nature, at a disadvantage [28].
The supply of PV modules was affected as China, where the disease broke out, was the major supplier of these modules. The delay in delivery of products affects RE projects up to a range as high as 4 GW [29]. The wind energy which is a leading sector in India has also been greatly affected by the pandemic. Projects equivalent to 600 MW got delayed, which is expected to cross loss of 2.69 GW in coming years [28].
To improve the share of RE in market MNRE has made RE projects as “most run,” which makes it mandatory for the states to purchase power from these RE sources [30]. MNRE has also processed to relax the deadlines for the RE projects, to ensure that these projects do not get affected and also ordered immediate payment to all the dues of the renewable projects by the states [30].
At the same time the damage to India’s renewable power goals for 2022 cannot be ignored either. However, in the recent study done by Bodenheimer and Leidenberger it is claimed that this pandemic could provide a bright opportunity for the renewable and sustainable energy sector, but that can only be achieved through proper strategic planning and designed communications on behalf of the policymakers [31].
2.4 Sustainability Assessment of RE Technologies
Assessment of RE technologies based on sustainability indicators is a complex task as indicators are generally conflicting in nature. Several assessment studies have been done with respect to the sustainability of electricity generation technologies at a global level [32–40] and also specifically of RE technologies [41–45], while some researchers have focused explicitly on the national level assessment of RE technologies, for example, for Turkey [44, 47], Irish city [46], Scotland [48], India [14, 15], Island of Sardinia [49], UK [50], Island of Crete in Greece [51], North Korea [52].
MCDM methods are the most common methods for assessing the sustainability of generation technologies; for example, analytic hierarchy process (AHP) [14, 44, 45, 52], MAVT [35, 37, 38], the weighted sum method (WSM) [34], the preference ranking organization method for enrichment evaluation (PROMETHEE) [48, 51], the elimination and choice translating reality (ELECTRE) [49], TOPSIS [41], (MULTIMORA, MACKBETH, NAIADE, CORPAS) [32, 41, 44, 46, 50].
The advantage of MCDM methods is that it allows considering all the objectives and indicators at the same time while making decisions [48, 53]. In the case of qualitative approaches, the value of indicators is expressed in the form of linguistic terms (e.g., low, high, very high), and due to the possibility of vagueness in a human decision, uncertainty is always associated with the result. Fuzzy combined with the MCDM method has proven to be useful in handling qualitative indicators with associated uncertainties [53, 54]. The fuzzy combined with MCDM methods have found vast application in the assessment of the energy system’s sustainability [43, 44, 47, 48, 55], and electricity distribution planning considering uncertainties [56, 57].
As far as sustainability assessment studies at a national level for India are considered there are majorly two studies [14, 15] done using MCDM applications. The study [14] accessed only three RE technologies i.e., wind power, solar power, and biomass and, did not consider small hydropower and large hydropower during the assessment. The assessment applied the AHP based on the Delphi technique and evaluated wind power as the most favourable technology. In another study [15], wind power, solar power, small hydropower, biomass, and geothermal were accessed using fuzzy-AHP using a wide range of sustainability indicators. However, the study [15] did not consider any social indicators.
The above-discussed limitations reviewed in the previous studies are addressed in the present study. Thus, the present study assessed all the RE technologies contributing to Indian grid-connected power using a range of technical, economic, environmental, and social indicators. The study also addressed the uncertainties associated with input data using fuzzy-TOPSIS and MCS.
Sustainability assessment of RE technologies required the following steps:
2.4.1 RE Technologies Selection
The potential of various RE technologies has been recognized in India such as onshore and offshore wind power, solar PV, CSP, large hydropower, small hydropower, tidal power, wave energy, bioenergy and, geothermal. The RE technologies which are contributing to grid-connected generation are assessed in the present study, i.e., large hydropower, small hydropower, onshore wind power, solar PV and, bioenergy (Table 2.1).
2.4.2 Sustainability Indicators Selection and Their Weightage
The social, environmental, and economic indicators are the three basic pillars of sustainability, although some technological and operational indicators have also been reviewed in the literature [36, 48, 58, 59]. The selection of sustainability indicators for the present study has been made with reference to studies [48, 53, 58]. Table 2.2 presents a summary of the selected indicators. Ten indicators have been selected comprised of three technological, two economic, two environmental, and three social types. The optimization preferences are assigned as maximum (max-m) or minimum (min-m). The indicator values of selected technologies with the range given in the brackets are presented in Table