Granular Stochastic Assessment of Renewable Integration: Identifying Critical Transmission Bottlenecks and Voltage Control Asymmetries

This paper presents a comprehensive stochastic assessment of renewable energy integration in the IEEE 30bus power system using a Monte Carlo simulation framework with 200 scenarios. By modeling the simultaneous injection of 45 MW solar and 80 MW wind generation with detailed temporal profiles, the study captures the operational impacts of renewable variability on grid performance. The results reveal that increased renewable penetration leads to substantial thermal generator displacement (10.1% to 42.6%) and the emergence of critical localized congestion, particularly in line 6-7 which experiences maximum flows of 53.586 MW. Voltage analysis highlights significant asymmetries between bus types, with PQ buses exhibiting up to 0.04 p.u. standard deviation compared to PV buses, underscoring the inadequacy of uniform voltage regulation strategies. Economic evaluation indicates that while operational costs generally decrease with renewables, cost variability and system losses may increase due to power flow redistribution. The analysis reveals dynamic curtailment patterns influenced by costprioritization mechanisms, with preferential wind curtailment due to higher marginal costs. The granular framework identifies transmission vulnerabilities masked by aggregate metrics, providing practical guidance for grid operators and planners working toward reliable and efficient renewable integration.