Adaptive nonlinear control and energy management for grid-connected hybrid wind–PV systems using Vienna converters

This paper develops a comprehensive nonlinear control and energy management strategy for a grid-connected hybrid wind-photovoltaic ( P V ) energy conversion system equipped with a lithium-ion battery storage unit. The overall system configuration consists of a permanent magnet synchronous generator ( P M S G ) interfaced via a Vienna rectifier, a P V generator connected through a D C / D C boost converter, and a bidirectional Vienna converter for grid coupling. A unified nonlinear state-space modeling framework is developed to characterize the dynamic interactions among the wind, P V , battery, and grid subsystems. Multiple operating modes are considered to ensure flexible and safe system operation, including maximum power point tracking ( M P P T ), adaptive power point tracking ( A P P T ), constant current ( C C ), and constant voltage ( C V ) modes. These modes allow optimal renewable energy harvesting, controlled battery charging and discharging process, and protection against overcharge and deep discharge. A supervisory energy management system ( E M S ) based on frequency deviation Δ f and battery state of charge ( S O C ) is designed to coordinate power flows among renewable sources, the lithium-ion battery, and the utility grid. This strategy enables dynamic power sharing, enhances grid frequency stabilization, and enforces battery operational and safety constraints. Simulation results demonstrate the effectiveness and robustness of the proposed approach in terms of tracking accuracy, power regulation and battery protection under various operating scenarios. The obtained results confirm the suitability of the proposed framework for hybrid renewable energy systems operating under high levels of renewable energy integration. • Nonlinear control strategy for a hybrid wind–PV–battery energy system. • Unified state-space modeling of wind, PV, battery, and grid subsystems. • Vienna converter topology improves power conversion efficiency. • EMS based on frequency deviation and SOC for adaptive power sharing. • Robust tracking and battery protection under varying operating conditions.