This paper describes the design of an adaptive controller based on model reference adaptive PID control (MRAPIDC) to stabilize a two-tank process when large variations of parameters and external disturbances affect the closed-loop system. To achieve that, an innovative structure of the adaptive PID controller is defined, an additional PI is designed to make sure that the reference model produces stable output signals and three adaptive gains are included to guarantee stability and robustness of the closed-loop system. Then, the performance of the model reference adaptive PID controller on the behaviour of the closed-loop system is compared to a PI controller designed on MATLAB when both closed-loop systems are under various conditions. The results demonstrate that the MRAPIDC performs significantly better than the conventional PI controller.
The integration of load shedding schemes with mainstream protection in power system networks is vital. The traditional power system network incorporates different protection schemes to protect its components. Once the power network reaches its maximum limits, and the load demand continue to increase the whole system will experience power system instability. The system frequency usually drops due to the loss of substantial generation creating imbalance. The best method to recover the system from instability is by introducing an under-frequency load shedding (UFLS) scheme in parallel with the protection schemes. This paper proposed a new UFLS scheme used in power systems and industry to maintain stability. Three case studies were implemented in this paper. Multi-stage decision-making algorithms load shedding in the environment of the DIgSILENT power factory platform is developed. The proposed algorithm speeds-up the operation of the UFLS scheme. The load shedding algorithm of the proposed scheme is implemented as a systematic process to achieve stability of the power network which is exposed to different operating conditions. The flexibility of the proposed scheme is validated with the modified IEEE 39-bus New England model. The application of the proposed novel UFLS schemes will contribute further to the development of new types of engineers.
<p><span>One of the most challenging aspects in the nonlinear control of a magnetic levitation (Maglev) system is to find an efficient control algorithm to achieve the stability and accuracy of the closed-loop system. The challenge is then to develop a linearizing control algorithm to maintain a steel ball at a desired position. In this paper, a novel linearizing control algorithm is proposed, which consists of the Lyapunov direct method (LDM) and the model reference control (MRC). The Lyapunov function is developed using the nonlinear equations of the magnetic levitation system, and the reference model is a linear second order system. Two control methods are developed to guarantee system robustness and output stability. Firstly, a new integral linear quadratic regulator (ILQR) is designed for the reference model. Then, an additional innovative proportional gain is combined with the linearizing controller to make the nonlinear control signal stronger. The simulation results indicate that the proposed linearizing controller has excellent set-point tracking, no time delay, fast rising and settling times, and achieves states stability.</span></p>
It is vital that the synchronous generator rotor angle be kept stable to avoid disastrous consequences such as the loss of synchronism amongst generators within a power system network. Once it is unstable, the time that is taken to remedy this is advised to be 5–10 s for smaller power systems and 15–20 s for larger ones. The instability that is caused by poorly damped Low-Frequency Electromechanical Oscillations (LFEOs) may result in inter-area oscillations, where a group of generators in one area oscillates against those in another area, thus affecting the stability of the entire network. This paper explores two control architectures, namely, a nonlinear Lyapunov-based trajectory tracking controller and a Model Reference Adaptive Controller (MRAC) as options to enhance the stability of the rotor angle. The performance of each of these controllers was assessed under steady-state conditions, and then, the synchronous generator was subjected to Gaussian noise and an impulse. While the first one is aimed at emulating small variations in the system loads that are responsible for inter-area oscillations, the latter one is an attempt to explore their performance for transient stability.
This paper presents an efficient design and real-time implementation of a controller for a large-scale grid-tied photovoltaic (PV) plant in a power system affected by disturbances. To direct the adequate amount of solar power, an Adaptive voltage and volt-ampere reactive (Volt-VAr) algorithm implemented in real-time using the Real Time Digital Simulator (RTDS) is proposed. An efficient and self-sufficient active and reactive P-Q power control scheme is proposed and implemented to transfer the generated power of the PV to the grid using a Voltage Source Converter (VSC). The proposed controller is implemented along with the PV system considered in RTDS to evaluate its effectiveness. By considering the impact of the disturbance caused by the load increase, the efficiency of the proposed power controller to transmit the generated power of the PV plant to the electrical grid system is investigated. It is observed that the hardware in the loop results verifies the advantage of the proposed method.
Being the primary cause of inter-area oscillations and due to the fact that they limit the generation’s output, Low-Frequency Electromechanical Oscillations (LFEOs) represent a real threat to power system networks. Mitigating their effects is therefore crucial as it may lead to system collapse if not properly damped. As rotor angle instability is the primary cause of LFEOs, this paper presents a novel Model-Reference Adaptive Control (MRAC) scheme that enhances its stability. The proposed scheme is tested using the Single-Machine Infinite Bus (SMIB) network. The results obtained validate the proposed decentralized control architecture. The robustness of this oscillation damping controller is verified through simulations in MATLAB/SIMULINK. With Gaussian noise added to the structure of the generator to emulate small load variations responsible for the rotor angle instability, the results of the simulations show that the rotor angle remains stable. Furthermore, when subjected to faults, the recovery time is less than 500 ms.
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