Lopez Quizhpi, Julio CesarPozo, David2019-07-262019-07-262018978-153864505-50000-0000https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85060254270&origin=inwardLa generación renovable está cambiando la generación convencional en microrredes. Por lo tanto, el funcionamiento de las microrredes se está volviendo más complejo y desafiante para garantizar la estabilidad y la fiabilidad. En este artículo, presentamos un enfoque de aversión al riesgo para el funcionamiento óptimo de las microrredes en presencia de generación renovable (RG) y sistema de almacenamiento de energía de batería (BESS).Renewable generation is shifting conventional generation in microgrids. Thus, the operation of microgrids is becoming more complex and challenging for ensuring stability and reliability. In this paper, we introduce a risk-averse approach for optimal operation of microgrids in the presence of renewable generation (RG) and Battery Energy Storage System (BESS). These sources are modeled and embedded into an AC optimal convex power flow equations. A Two-Stage Adaptive Robust Optimization mathematical framework is presented to address uncertainties in the load demand and renewable resources. Uncertainty is depicted with a polyhedron instead of probability distribution function. The resulting model is a three-level min-max-min problem. The robust model is formulated to minimize the total cost of energy purchased from the distribution substation and energy cost of distributed generation. Results of an illustrative example and a case study based on the 11-node test system show the effectiveness of the proposed approach.es-ESMicrogridsMathematical modelUncertaintyEnergy storageOptimizationLoad modelingStochastic processes