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Planning for variable renewable energy loads in India’s power system

Case Summary: 

The transformation of traditional power systems to encompass diverse renewable energy resources is critical in enabling low carbon climate resilient development. To support key climate and development objectives, the Government of India created an ambitious target of 175 GW of installed renewable energy by 2022. Understanding the impacts of scaled up renewable energy expansion on the grid is crucial and requires robust analysis to plan for potential operation and system changes. Within this context, GoI and other key partners, used advanced weather and power systems modeling to understand grid integration actions required to support these renewable energy targets. Listed below are actions and good practices supporting advanced modeling techniques for smart grid solutions in India, as profiled in the case study.

  • In-depth modeling was undertaken to support various analyses related to RE grid integration. These analyses shed light on key operational considerations such as:
    • Identification of power system operational methods for accommodating variable loads. It was demonstrated that balancing the maximum load of solar and wind was achievable with 15-minute operational time-scales with minimal renewable energy curtailment.
    • Understanding the consequences of reducing coal capacity. It was shown that the grid can withstand a 20% reduction (46 GW) in coal capacity
    • Actions to enable efficient and reliable grid operation by planning for future load flexibility, expanding geographical resource diversity, and expanding transmission infrastructure.
    • Actions to reduce operating costs of the power system.
  • Capacity building and training for local personnel to ensure modeling and analysis can be undertaken over the longer term as energy sector needs evolve.
Action Area 
Planning and Implementation Activity 
Analysis and Data Collection, Developing and Implementing Policies and Measures
Sectors and Themes 
Energy Efficiency, Renewable Energy
National Renewable Energy Laboratory (NREL)