In microgrids, distributed generators that cannot be dispatched, such as a photovoltaic system, need to control their output power at the maximum power point. The fluctuation of their output power should be minimized with the support of the maximum power point tracking algorithm under the variation of ambient conditions. In this paper, a new maximum power point tracking method based on the parameters of power deviation ($\Delta P_{PV}$), voltage difference ($\Delta V_{PV}$), and duty cycle change ($\Delta D$) is proposed for photovoltaic systems. The presented algorithm achieves the following good results: (i) when the solar radiance is fixed, the output power is stable around the maximum power point; (ii) when the solar radiance is rapidly changing, the generated power is always in the vicinity of maximum power points; (iii) the effectiveness of energy conversion is comparable to that of intelligent algorithms. The proposed algorithm is presented and compared with traditional and intelligent maximum power point tracking algorithms on the simulation model by MATLAB/Simulink under different radiation scenarios to prove the effectiveness of the proposed method.

Currently, renewable energy sources (RESs) are gradually replacing traditional power sources that use fossil fuels. In some countries, such as Vietnam, RESs are developed on a massive scale and are concentrated in some key areas. This causes negative impacts on a power system when its transmission system is not deployed synchronously to release their capacity from these new renewable energy plants. An important challenge today is to ensure frequency stability in power systems with high uncertainty in RES output power. Additionally, the system requires solutions to prevent transmission line overloads during periods when RESs make a substantial contribution to the electricity generation capacity. Therefore, this paper builds an automatic generation control (AGC) system for a two-area power system with high penetration of RESs. This AGC system model aims to maintain system frequency stability amid unpredictable changes in RESs while also ensuring that tie-lines transmit the predetermined power levels to mitigate frequent congestion. By continuously monitoring and adjusting the system’s frequency, the challenges posed by the inherent variability of RESs can be effectively mitigated. The AGC model is simulated on DIgSILENT PowerFactory software and tested with a 106-bus system. The simulation results of this study show that the AGC system operates effectively, ensuring that the frequency returns to the rated value and maintaining the exchange capacity on the tie-lines after occurrences of RES power decrease events.

This study proposes an optimal control strategy for battery energy storage systems to support frequency regulation in power systems with high renewable energy penetration. The algorithm generates a sinusoidal reference signal for the pulse-width modulation scheme of the direct current/alternating current converter, adjusting it based on voltage magnitude and phase set points. The control system integrates multiple loops to manage frequency, voltage, active and reactive powers, charge, and current controllers on the d- and q-axes. It limits frequency deviations and improves the rate of change of frequency. An adaptive nonlinear droop control method, combined with state-of-charge (SOC) feedback, regulates active power-frequency control to enhance grid stability. The SOC feedback mechanism enables dynamic charge and discharge operations, ensuring that frequency remains within operational limits. Simulation results, validated using modified Vietnamese Tay Nguyen 500/220 kV and IEEE 39-bus systems with DIgSILENT/PowerFactory, show that the proposed method outperforms the conventional CBEST model in scenarios involving sudden generation outages or fluctuating renewable energy output. This method meets the frequency stability requirements set by the Circular No. 25/2016/TT-BCT of the Vietnamese Ministry of Industry and Trade, ensuring that the system operates within a stable frequency range of 49.5–50.5 Hz under 120 s and recovers to 49.8–50.2 Hz within 300 s.