Probabilistic Small-Signal Stability Analysis of a Wind–Solar–Thermal–Storage Hybrid Energy System

Against the backdrop of increasing global attention to energy transition and environmental protection, the development of green and clean energy faces significant challenges. A wind–solar–thermal–storage (WSTS) hybrid energy system is proposed in this paper to address the volatility, intermittency, and uncontrollability of wind and solar renewable energy, and probabilistic small-signal stability analysis is conducted for the system. First, to mitigate the impact of wind and solar energy characteristics, a probabilistic optimization strategy is developed by combining the Latin hypercube sampling (LHS) method and the simultaneous back-substitution elimination (SBSE) method. This ensures that the optimized wind and solar output scenarios better align with practical operating conditions and can safely operate within a complex and changeable system operating environment. Second, a hybrid energy system model integrating wind, solar, thermal power, and energy storage devices is established. The active power of the hybrid energy system circuit is taken as the input parameter of the flexible AC transmission system (FACTS) device, and a unified power flow controller-power oscillation damping (UPFC-POD) controller is designed by integrating a UPFC with POD. Based on Lyapunov stability theory, the local stability of the system under small perturbations is analyzed. The system is linearized to obtain the state matrix given multiple operating modes. Finally, considering the coupling characteristics between multiple controllers, the Nutcracker optimization algorithm (NOA) combined with the Levy flight strategy is employed to coordinate and optimize the parameters of the UPFC-POD and power system stabilizer (PSS) controllers. Simulation results for the IEEE 4-machine 2-area system and the IEEE 16-machine 5-area system demonstrate that the optimization algorithm combining NOA and Levy flight strategy exhibits faster convergence and superior optimization performance. The optimized WSTS improves the system damping ratio, effectively suppresses the impacts caused by low-frequency oscillations (LFO), and ensures the safe and stable operation of the system in harsh conditions.