An Extreme Learning Machine Based Adaptive VISMA for Stability Enhancement of Renewable Rich Power Systems

Abstract

Maintaining power system stability in renewable-rich power systems can be a challenging task. Generally, the renewable-rich power systems suffer from low and no inertia due to the integration of power electronics devices in renewable-based power plants. Power system oscillatory stability can also be affected due to the low and no inertia. To overcome this problem, additional devices that can emulate inertia without adding synchronous machines can be used. These devices are referred to as virtual synchronous machines (VISMA). In this paper, the enhancement of oscillatory stability of a realistic representative power system using VISMA is proposed. A battery energy storage system (BESS) is used as the VISMA by adding an additional controller to emulate the inertia. The VISMA is designed by using Fruit Fly Optimization. Moreover, to handle the uncertainty of renewable-based power plants, the VISMA parameters are designed to be adaptive using the extreme learning machine method. Java Indonesian Power Grid has been used as the test system to investigate the efficacy of the proposed method against the conventional POD method and VISMA tuning using other methods. The simulation results show that the proposed method can enhance the oscillatory stability of the power system under various operating conditions.

Adaptive Controller of Bidirectional DC-DC Converter Based on Extreme Learning Machine for Electric Vehicle

“…In addition, the output is predicted parameter of PI controller (Kp and Ki). The procedure of adaptive PI includes the following steps [28]:…”

“…If the MSE value is minimum, print out the results. Otherwise go to the step 1 until the minimum MSE are obtained [28].…”

Intelligent voltage controller based on firefly algorithm for DC-DC boost converter

“…In 2018, Abdulkhader et al [14], the application of particle swarm optimization (PSO) was observed for designing a multi-band power system stabilizer, with the adoption of FFO (fruit fly optimization) also used for developing virtual synchronous machine in [15]. Among all the numerous algorithms, FA (Firefly Algorithm) is still observed as the best model, regarding the simplicity and optimal results [16].…”

An Eagle Strategy Arithmetic Optimization Algorithm for Frequency Stability Enhancement Considering High Renewable Power Penetration and Time-Varying Load

“…Accordingly, the entities responsible for establishing new generation power plants are still intending to use renewable energy sources (RESs) instead of conventional power plants due to their good features (i.e., friendly to the environment, low cost, and abundant energy). However, with the rapid growth and use of RESs, the power system fluctuations increase due to the reduction of the system inertia [1,2]. Wherein, the power systems' operation and security will be affected according to those fluctuations.…”