Power sector decarbonization planning considering renewable resource variability and system operational constraints

Bottom-up long-term planning models generally consider low levels of spatial, temporal, and technical details to reduce associated computation. However, these details are required to capture spatial and temporal variability of Renewable Energy Sources (RESs) and perform harmonized dispatch of conventional generating units. In their absence, models may overestimate RESs uptake and underestimate the quantum of required flexible resources. This may create a false impression of sector decarbonization and the obtained capacity mix may result in frequent RES or load curtailment during real-time system operations. In this context, this study aims to improve upon the shortcomings of conventional planning approaches and develop a TIMES based planning model for the Indian power sector. The model adopts high spatial and temporal definitions of 5 regions and 288 sub-annual timeslices. RESs are categorized into sub-classes based on annual capacity factors to capture their intra-regional variations without further increasing the spatial resolution. Each month is represented by a day of chronological hourly resolution that facilitates the capture of RES temporal variations and incorporation of operational aspects of generating units such as minimum stable generation, ramp limits and partial load operation. The impact of these operational parameters on system planning is analysed to identify a trade-off between planning accuracy and computational complexity. The study is relevant for countries that are rigorously following their decarbonization plans with high penetration of variable RESs and have a similar trajectory as that of India. The results indicate that decarbonization levels can be better assessed if capacity mix and flexible resources are adequately valued by considering operational parameters at the planning stage for a power system dominated by low flexible generation.