The transition from marginal to dominant renewable energy systems in electricity generation globally has posed new challenges in terms of intermittency, variability, uncertainty and low-reliability. This situation has led to a significant supply-demand gap in terms of temporal mismatch (times of supply and demand) and quantity mismatch (high supply with low demand, and vice versa). These mismatches lead to several issues, including surplus or insufficient electricity generation, erratic grid operation, etc. Hence, the electricity planners have to match “dynamic supply with dynamic demand.”. In managing such a transitioning electricity system, the planning from the electricity supply side requires efficient management of existing electric power systems, on rationalizing generation portfolios. Therefore, to address these decisions, we have developed a generic linear programming-based optimisation model that dynamically balances supply and demand at least cost. In addition to achieving this objective of dynamic supply-demand balance, the model is designed to evaluate all the supply-side options and arrive at a least-cost generation portfolio. This would enable an RE dominated electricity taking in to account the inherent challenges associated with renewable energy integration. The model is validated using data from the electricity system of Karnataka, India where actual data was compared to modelled outputs for the calendar year 2019. Precision metrics, which measures standard error, were used to assess the model's accuracy. The results indicated that the standard error ranged from ±10%, which is within acceptable limits. This model can be effectively used for electricity transition planning and can provide critical inputs to policy makers.