In this paper, a nonlinear adaptive disturbance rejection control (NADRC) strategy is designed to overcome the limitations of the traditional virtual synchronous generator (VSG) control method in photovoltaic (PV) grid-connected energy storage systems. This strategy utilizes exact feedback linearization and linear optimal control theory to establish a nonlinear adaptive disturbance rejection control law based on the virtual synchronous generator. It achieves zero static error control and noise adaptive stabilization of the AC link in a multiple-input multiple-output system. Compared with the simulation results of the grid-connected inverter voltage and current double closed-loop (VACDCL) strategy, the nonlinear adaptive disturbance rejection control effectively mitigates the fluctuations in load current caused by the photovoltaic energy storage module. It ensures power tracking under variable power conditions and outperforms traditional PI dual-loop control in terms of dynamic and static regulation performance as well as grid-connected current quality. Furthermore, this strategy’s anti-disturbance adaptive link can quickly respond to system disturbances like frequency drift, voltage oscillations, and load current variations, thereby improving system performance.

Aiming at the occurrence of long-term and ultra-low frequency oscillations in the hydropower network system, this paper derives the generalized turbine transfer function speed control system model including the flow factor Tpq based on...

The joint operation of large cascade hydropower plants changes the natural hydrological regime of the river, thereby reducing the stability of the basin ecosystem. To coordinate the power generation of cascade hydropower plants' demand and ecological environment demand, this paper establishes an ecological multi-objective optimized scheduling model (EMOOSM) for cascade hydropower plants, aiming at the maximum power generation of cascade hydropower plants and the minimum inappropriate ecological water volume. To solve the complex EMOOSM, a marine predators algorithm was introduced, which was improved and extended to the multi-objective solution level. Multi-objective improved marine predators algorithm (MOIMPA) based on Cauchy variation preserves non-dominated solutions by adding an external archive set and maintaining them with a crowdedness-based fast sorting strategy. The optimal dispatching results of a cascade hydropower plant in China's Pearl River system show that MOIMPA can effectively deal with conflicting power generation and ecological goals. The recommended scheme determined according to the fuzzy set theory and the principle of maximum satisfaction can adapt to the change law of ecological demand and reasonably adjust the inappropriate ecological water volume in the stage according to the different ecological sensitivity in the dispatching period. The recommended scheme in the normal year reduces the inappropriate ecological water volume caused by the operation of the cascade reservoir by 1.7156 × 10⁵ m³ at the expense of only 1.12% of the power generation, effectively balancing the power generation and ecological benefits of the cascade hydropower plant operation. Compared with the results of other algorithms, the Pareto solution set obtained by MOIMPA has a better diversity metric (DM) indicator, maximum spread (MS) indicator, and hypervolume (HV) indicator. The research results provide a theoretical basis and reference for the ecological operation research of cascade hydropower plants.