Search

Green hydrogen can be the transitional solution required to reduce anthropogenic emissions and enhance energy independency from fossil fuel. To improve green hydrogen adoption, a cluster-based infrastructure, called a hydrogen hub, is devised taking into account the demand-supply interplay coupled with transport ease. In this paper, we have identified sites across states that are conducive for hydrogen hubs. It involves a multicriteria decision-making (MCDM) framework deployed to assign priorities within competing set of criteria. A comprehensive analytical hierarchy process (AHP) is used to rank criteria that are connected to establish a functioning hydrogen hub. These criteria include, but not limited to, proximity to refineries, fertilizer plants, substations, chlor-alkali units, steel manufacturing plants, water availability, access to gas pipelines, railway line access, and finally distance to highways. Our analyses indicate that proximity to refineries and fertilizers scored higher (scores directly proportional to importance) while railway line access scored the least. These prioritised scores are used to spatially locate sites using geographical information system. In a total of thirteen states identified, Gujarat had the largest parcel of most suitable land for setting up hydrogen hub followed by Maharashtra and Andhra Pradesh. For India to set up a functioning hydrogen economy and achieve green hydrogen goals, it is important to identify states that can drive the agenda forward. This paper illustrates a way (amongst many available ways) to identify states based on their strength and capability to fulfil the national goal of 5 million tons of green hydrogen by 2030. • The paper addresses setting up of green hydrogen hubs in India based on a multi-criteria site selection framework. • Nine selection criteria covering aspects of hydrogen ecosystem proposed to identify site(s) suitable for hydrogen hubs. • Integration of AHP and GIS is used to ascertain land parcels where hydrogen economy can sustain across states in India. • Zones in 13 states were identified as potential hydrogen hubs. [ABSTRACT FROM AUTHOR]

[Display omitted] • Indian electricity demand reduced by 11 % vis-à-vis 2019 during the lockdown. • Sectoral demand reduction—73 % industrial, remaining 27 % commercial. • Pan India lights-off event—hydropower provides the bulk of the flexibility (60 %). • The plant load factor of coal dropped to a record low of 35 % during phase-1. • Power sector emissions reduced by 16 % (86 MtCO2) compared to 2019. This paper aims to understand the responsiveness of the power sector during the lockdown due to the COVID-19 pandemic beginning from March 25, 2020 and analyses its impact on the demand, operation and supply of electricity in the Indian power system. The role of the C&I load share in reducing the electricity demand of the different states in India has been examined using multi-sectoral regression analysis. The impact of the pan India lights-off event on the short-term operational flexibility response of the power system has also been analysed using high-temporal resolution data. The results indicate that there has been a reduction of nearly 70 TWh of electricity demand during the lockdown period, an 11 % reduction compared to 2019. The top three states recording the highest reduction were Maharashtra, Gujarat and Tamil Nadu at 11 TWh, 10.6 TWh and 8.4 TWh, respectively. Regression analysis revealed that out of the total drop in load demand — 73 % is owed to the industrial sector, while the remaining 27 % is to the commercial sector. This demand drop also impacted the upstream electricity supply mix where 96 % of the reduction in supply was borne by the coal generating units, recording its lowest national plant load factor at 35 % with a 16 % reduction in overall CO 2 emission compared to the same period in 2019. In conclusion, a case study of Maharashtra has been used to analyse the impact of this reduction in electricity demand on the supply mix, hourly load profile and cost of supply under the different lockdown phases. [ABSTRACT FROM AUTHOR]