A Hankel Matrix Based Reduced Order Model for Stability Analysis of Hybrid Power System Using PSO-GSA Optimized Cascade PI-PD Controller for Automatic Load Frequency Control

This paper presents the automatic load frequency control (ALFC) of two-area multisource hybrid power system (HPS). The interconnected HPS model consists of conventional and renewable energy sources operating in disparate combinations to balance the generation and load demand of the system. In the proffered work, the stability analysis of nonlinear dynamic HPS model was analyzed using the Hankel method of model order reduction. Also, an attempt was made to apply cascade proportional integral - proportional derivative (PI-PD) control for HPS. The gains of the controller were optimized by minimizing the integral absolute error (IAE) of area control error using particle swarm optimization-gravitational search algorithm (PSO-GSA) optimization technique. The performance of cascade control was compared with other classical controllers and the efficiency of this approach was studied for various cases of HPS model. The result shows that the cascade control produced better transient and steady state performances than those of the other classical controllers. The robustness analysis also reveals that the system overshoots/undershoots in frequency response pertaining to random change in wind power generation and load perturbations were significantly reduced by the proposed cascade control. In addition, the sensitivity analysis of the system was performed, with the variation in step load perturbation (SLP) of 1% to 5%, system loading and inertia of the system by ±25% of nominal values to prove the efficiency of the controller. Furthermore, to prove the efficiency of PSO-GSA tuned cascade control, the results were compared with other artificial intelligence (AI) methods presented in the literature. Further, the stability of the system was analyzed in frequency domain for different operating cases

Frequency deviations stabilizations in restructured power systems using coordinative controllers

Modern restructured power system faces excessive frequency aberrations due to the intermittent renewable generations and persistently changing load demands. An efficient and robust control strategy is obligatory to minimise deviations in the system frequency and tie-line to avoid any possible blackout. Hence, in this research, to achieve this target, automatic generation control (AGC) is utilized as a secondary controller to alleviate the changes in interconnected restructured systems at uncertainties. The objective of AGC is to quickly stabilize the deviations in frequency and tie-line power following load fluctuations. This thesis addresses the performance of AGC in two-area restructured power systems with many sophisticated control strategies in the presence of renewable and traditional power plants. As per literature of research work, there are quite a few research studies on AGC of a restructured system using optimized coordinative controllers. Besides, investigations on advanced optimized-based coordinative controller approaches are also rare to find in the literature. So, various combinations of two degrees of freedom (2DOF) controllers are utilized as supplementary controllers to diminish the frequency deviations. Nevertheless, the interconnected tie-lines are typically congested in areas with huge penetration of renewable sources, which may reduce the tie -line capability. Therefore, distinct FACTS controllers and ultra-capacitor (UC) are integrated into two-area restructured systems for strengthening the tie-line power and frequency. Further, new optimization techniques such as cuckoo search (CS), bat algorithm (BA), moth-flame optimization (MFO) are utilized in this work for investigating the suggested 2DOF controllers and compared their performance in all contracts of restructured systems. As per the simulation outcomes, the amalgamation of DPFC and UC with MFObased 2DOF PID-FOPDN shows low fluctuation rate in frequency and tie-line power. Besides, the settling times (ST) of two areas are 9.5 S for ΔF1, 8.2 S for ΔF2, and 10.15 S for ΔPtie. The robustness of the suggested controller has been verified by ±25% variations in system parameters and loading conditions

Frequency stabilization in interconnected power system using bat and harmony search algorithm with coordinated controllers

Modern power system faces excessive frequency aberrations due to the intermittent renewable generations and persistently changing load demands. To avoid any possible blackout, an efficient and robust control strategy is obligatory to minimize deviations in the system frequency and tieline. Hence, to achieve this target, a new two-degree of freedom-tilted integral derivative with filter (2DOF–TIDN) controller is proposed in this work for a two-area wind-hydro-diesel power system. To enhance the outcome of the proposed 2DOF–TIDN controller, its gain parameters are optimized with the use of a newly designed hybrid bat algorithm-harmony search algorithm (hybrid BA–HSA) technique. The effectiveness and superiority of hybrid BA–HSA tuned 2DOF–TIDN is validated over various existing optimization techniques like cuckoo search (CS), particle swarm optimization (PSO),HSA, BA and teaching learning-based optimization (TLBO). To further refine the system outcome in the dynamic conditions, several flexible AC transmission systems (FACTS) and superconducting magnetic energy storage (SMES) units are adopted for enriching the frequency and tie-line responses. The FACTS controllers like static synchronous series compensator (SSSC), thyristor-controlled phase shifter (TCPS), unified power flow controller (UPFC) and interline power flow controller (IPFC) are employed with SMES simultaneously. The simulation results disclose that the hybrid BA–HSA based 2DOF–TIDN shows superior dynamic performance with IPFC–SMES than other studied approaches. A sensitivity analysis is examined to verify the robustness of proposed controller under ±25% changes in loading and system parameters

A novel algorithm for integrated control model using swarm robots for intruder detection and rescue schedules

Due to the development of computer controlled tools and expansion of integrated computing applications, more and more controller functions are turning to software implementations. A novel controlling algorithm is designed for continuous optimization tasks. However, they are used to thoroughly optimize and apply different areas. The most intelligent swarm algorithms have been designed for continuous optimization problems. However, they have been applied to discreet optimization and applications in different areas. This article gives experimental results on the control of swarm robots with the help of integrated control model (ICM), around its own axis. Such methodology is quite impressive in development of applications for surveillance, path planning, intruder and obstacle detection, model errors in communication to remove uncertainty. The ICM control design performance is based on comprehensive swarm robot model for the identification of actuators from testing data. The same ICM controllers are designed to be compared with the PID controllers in a variety of tests and collected feedback found 12.37%, 8.69% and 12.09% improved on the basis of thrust produced in the propellers for surveillance

Microstructure of Injection Moulding Machine Mould Clamping Mechanism: Design and Motion Simulation

With the advent of intelligence technologies, more and more machines and devices are involved in the creation of complex structures. In the intelligent manufacturing industries, mouldings including injection moulding, blow moulding, compression moulding, and others play critical roles in manufacturing highly precise parts required for building intelligent machines (such as computers, cell phones, robots etc.). The performance of the clamping mechanism directly affects the quality of the microstructure of injection products. The design of the injection moulding mould clamping mechanism is based on the microstructure characteristics of the trip of the toggle lever mechanism ratio, speed ratio, and force amplification ratio. These are used to study the main performance parameters, such as analysis, as well as for the establishment of the physical model of the clamping mechanism. The model is based on the microstructure of injection of hyperbolic elbow clamping mechanism kinematics simulation. Simulation results and theoretical calculation contrast analysis show that the maximum dynamic template speed is 215.34 mm/s. The dynamic templates and cross-head speed ratio is 2.15; therefore, the design of the injection moulding mould clamping mechanism for the microstructure provides favourable technical support. The method described here is important to build complicated moulds required to build highly precise parts to build intelligent machineries

Semi-automatic liquid filling system using NodeMCU as an integrated Iot Learning tool

Computer programming and IoT are the key skills required in Industrial Revolution 4.0 (IR4.0). The industry demand is very high and therefore related students in this field should grasp adequate knowledge and skill in college or university prior to employment. However, learning technology related subject without applying it to an actual hardware can pose difficulty to relate the theoretical knowledge to problems in real application. It is proven that learning through hands-on activities is more effective and promotes deeper understanding of the subject matter (He et al. in Integrating Internet of Things (IoT) into STEM undergraduate education: Case study of a modern technology infused courseware for embedded system course. Erie, PA, USA, pp 1–9 (2016)). Thus, to fulfill the learning requirement, an integrated learning tool that combines learning of computer programming and IoT control for an industrial liquid filling system model is developed and tested. The integrated learning tool uses NodeMCU, Blynk app and smartphone to enable the IoT application. The system set-up is pre-designed for semi-automation liquid filling process to enhance hands-on learning experience but can be easily programmed for full automation. Overall, it is a user and cost friendly learning tool that can be developed by academic staff to aid learning of IoT and computer programming in related education levels and field