This study evaluated a potential transition of India’s power sector to 100% wind and solar energy sources. Applying a macro-energy IDEEA (Indian Zero Carbon Energy Pathways) model to 32 regions and 114 locations of potential installation of wind energy and 60 locations of solar energy, we evaluated a 100% renewable power system in India as a concept. We considered 153 scenarios with varying sets of generating and balancing technologies to evaluate each intermittent energy source separately and their complementarity. Our analysis confirms the potential technical feasibility and long-term reliability of a 100% renewable system for India, even with solar and wind energy only. Such a dual energy source system can potentially deliver fivefold the annual demand of 2019. The robust, reliable supply can be achieved in the long term, as verified by 41 years of weather data. The required expansion of energy storage and the grid will depend on the wind and solar energy structure and the types of generating technologies. Solar energy mostly requires intraday balancing that can be achieved through storage or demand-side flexibility. Wind energy is more seasonal and spatially scattered, and benefits from the long-distance grid expansion for balancing. The complementarity of the two resources on a spatial scale reduces requirements for energy storage. The demand-side flexibility is the key in developing low-cost supply with minimum curtailments. This can be potentially achieved with the proposed two-level electricity market where electricity prices reflect variability of the supply. A modelled experiment with price signals demonstrates how balancing capacity depends on the price levels of guaranteed and flexible types of loads, and therefore, can be defined by the market.

Globally, electricity systems are transitioning from marginal to dominant renewable energy systems in terms of installed capacity and electricity generation shares. This transition has led to the situation of matching dynamic supply with dynamic demand. For effective management, electricity system planners and operators must have a clear understanding of the dynamics of the supply sources. Knowing these would enable them to identify periods of constrained supply and manage resources optimally. Studying 365 supply profiles for a year is a cumbersome exercise and it is impossible to observe the supply peculiarities from such a huge volume of data. Therefore, there needs to be a mechanism in place to capture these patterns along with magnitude, span, temporal effects and influential factors of supply-side variabilities. In this research, we propose a methodology for characterizing variations in supply profiles of solar and wind energy technologies by deploying a simulation-based approach. First, a logical clustering method is employed to form a smaller groups of supply profiles. Next, probability distribution-based Monte Carlo simulation is adopted to refine these groups of supply curves and arrive at a representative supply curve, which is called Representative Supply Profile (RSP). This approach is validated using data from Karnataka (a state in India) electricity system, and technology specific RSPs are developed. With this, we could represent the 365 days' hourly generation into 10 RSPs for solar and 14 RSPs for wind. The results show that solar and wind supply profiles represent different seasonal cycles.