Abstract 

 

Over the last decade, renewable generation, mostly wind and solar, has displaced coal-based generation as the cheapest source of electricity in generation cost terms. Renewables are also an attractive option given their lower local and global environmental footprint. Given this, and the strong policy push, the share of renewables in the Indian electricity grid has been increasing rapidly in the recent years, with installed capacity of renewable power generation crossing 100GW.

 

Battery storage costs have seen huge reductions in recent years and they are expected to continue to drop. The modular nature of battery storage, makes it an attractive option to manage diurnal variability and reduce curtailment of renewable generation. In addition, there are various initiatives such as the agriculture solar feeder scheme to shift load to times when generation cost is the lowest. There is increasing electrification of energy demand, such as with transport, industry and cooking. With the advent of smart meters and ICT infrastructure, demand side management options such as time-of-day tariffs and demand response measures are becoming more feasible. Demand side measures such as energy efficiency and demand response require a better understanding of energy demand and how it is likely to change going forward. Disaggregated demand assessment can also provide a better window into energy access and demand inequities.

 

Policies, planning and system operation need to consider all these aspects of the energy transition to ensure an equitable, cost-effective and reliable energy system that meets the country's developmental and environmental goals.  Modelling plays an important role in making this happen, and hence decision makers are increasingly looking to models to help inform the path forward in the context of these complex dynamics.

 

We will present two open source modelling platforms using case studies of models developed for the Indian energy system using these platforms. The first is a power sector modelling platform named GridPath based on which a model was developed for the Maharashtra power system. The second is an energy systems modelling framework named Rumi based on which a model named PIER was developed for the Indian energy system. More details can be found at https://www.prayaspune.org/peg/publications/item/510 and https://www.prayaspune.org/peg/publications/item/512 respectively. We hope that these open source models would be of interest for ongoing research at IIT Bombay.

 

 

Srihari Dukkipati worked in embedded software development in the wireless communications sector for 14 years before joining Prayas in 2011. At Prayas, he focuses on energy data and modelling related activities. He has been part of various committees set up with central government energy data agencies to improve energy data management in the country. He works on power sector and energy systems modelling activities to inform power sector planning and wider energy policy. Srihari has Bachelor’s and Master’s degrees in Computer Science and Engineering.