Load Frequency Active Disturbance Rejection Control for Multi-Source Power System Based on Soft Actor-Critic

Abstract

To ensure the safe operation of an interconnected power system, it is necessary to maintain the stability of the frequency and the tie-line exchanged power. This is one of the hottest issues in the power system field and is usually called load frequency control. To overcome the influences of load disturbances on multi-source power systems containing thermal power plants, hydropower plants, and gas turbine plants, we design a linear active disturbance rejection control (LADRC) based on the tie-line bias control mode. For LADRC, the parameter selection of the controller directly affects the response performance of the entire system, and it is usually not feasible to manually adjust parameters. Therefore, to obtain the optimal controller parameters, we use the Soft Actor-Critic algorithm in reinforcement learning to obtain the controller parameters in real time, and we design the reward function according to the needs of the power system. We carry out simulation experiments to verify the effectiveness of the proposed method. Compared with the results of other proportional–integral–derivative control techniques using optimization algorithms and LADRC with constant parameters, the proposed method shows significant advantages in terms of overshoot, undershoot, and settling time. In addition, by adding different disturbances to different areas of the multi-source power system, we demonstrate the robustness of the proposed control strategy.

Multi-loop active disturbance rejection control and PID control strategy for poultry house based on GA, PSO and GWO algorithms

“…The controller uses the extended state observer (ESO) to treat and reject the internal and external disturbances as total disturbance and a feedback controller to compensate for this existing disturbance and generate the desired signal. The ADRC control has been successfully used with a variety of systems, including control of DC motor [ 13 ], wind and power systems [ [14] , [15] , [16] ], mechanics [ 17 ] and robotics [ 18 ]. However, to the authors' knowledge, no literature review work has employed ADRC control to regulate poultry environment building.…”

Tuning of Auto Disturbance Rejection Controller Parameters Based on Improved Grey Wolf Optimizer

“…When initializing the population, chaos mapping was introduced to increase population diversity, Levy flight strategy was introduced into the finder position update equation to improve the optimization performance of the algorithm, and evolutionary strategy was introduced into the guard position update equation to break away from the local extreme constraints, and the improved algorithms were applied to tune ADRC parameters and system identification. Zheng et al [17] used the soft actor-critical algorithm in reinforcement learning and designed a reward function based on the needs of the power system to obtain real-time linear auto disturbance rejection controller parameters to ensure load frequency control. Wu et al [18] proposed an adaptive hybrid algorithm based on biogeography and a differential evolution algorithm to tune ADRC parameters.…”