Renewable generation expansion planning for Ecuador’s coastal region: a stochastic optimisation approach

Centralised energy planning frequently overlooks specific regional resource dynamics, magnifying the exposure to hydrological deficits in Ecuador’s high-demand zones. The present work formulates an optimal renewable expansion strategy for the coastal region to satisfy projected electricity demand over the 2025–2034 horizon. This analysis integrates viable solar, wind, and hydroelectric potentials into a stochastic dynamic programming model implemented in SimSEE. The model successfully determines the chronological dispatch hierarchy required to minimise operational deviations. Simulation results demonstrate that local resources can fully meet demand through a strict prioritisation of non-conventional sources. As a result, solar photovoltaic and wind power achieve 100% saturation of available capacity by 2031. Hydroelectric generation adjusts to cover residual requirements, reaching a 61.6% share by the end of the period. These quantitative outcomes call into question current centralised national planning assumptions. They prove that granular, region-specific modelling yields more robust solutions than aggregated approaches. Consequently, regulatory frameworks must evolve to facilitate regionalised auctions and the integration of battery energy storage systems. These changes are necessary to manage the high penetration of variable renewable energy.