Optimal Load Frequency Control of Island Microgrids via a PID Controller in the Presence of Wind Turbine and PV

This article studied the load frequency control (LFC) of a multi-source microgrid with the presence of renewable energy sources. To maintain a sustainable power supply, the frequency of the system must be kept constant. A Proportional–Integral–Derivative (PID) controller is presented as a secondary controller to control the frequency of the microgrid in island mode, and the integral of squared time multiplied by error squared (ISTES) is used as a performance index. The use of the Craziness-Based Particle Swarm Optimization (CRPSO), which is an improved version of Particle Swarm Optimization (PSO), improves the convergence speed in optimizing the nonlinear problem of load and frequency controller design. The test microgrid is composed of the load and distributed generation units such as diesel generators, photovoltaics and wind turbines. The proposed controller provided the desired response to adjusting the microgrid frequency, achieving the final response after a short time and making it more stable and less oscillatory compared with the conventional system.

Optimal Frequency stability Control Strategy for a Grid-Connected Wind/PV/FC/BESS Coordinated with Hydroelectric Power Plant Storage Energy System Using Variable Structure Control

Because of the growing nonlinear and complexity nature of microgrid systems for example battery energy storage systems, wind-turbine fuel cell, photovoltaic, and micro hydro power plants (BESSs/FC/WT/PV/ Micro Hydro), load-frequency management has been a difficulty. The development of a load-frequency controller based on Proportional–Integral–Derivative (PID) for an autonomous microgrid (MG) with hydro, wind, and PV RES is shown in this article. The suggested LFC goal is to retain the frequency of the micro hydro power plant under variable load situations by controlling the sharing of output power constant generator between the dummy loads and consumer. Using an adaptive fuzzy logic controller to govern nearly the generating unit`s whole operation, the suggested control technique optimally chooses PID settings for each load value. The suggested fuzzy logic-based controller regulates the plant's frequency output despite fluctuating user loads and manages energy distribution by separating the micro network into separate departures connected in priority order. The suggested frequency controller uses a centralised LFC approach centred on a combination of smart load and Battery Energy Storage System to manage the MG frequency (BESS). It regulates MG frequency by providing active power balancing for a variety of events that such systems face in real-world settings, such as energy surplus generation and energy shortage. In Simulink/MATLAB, the suggested structure is simulated. The simulation results clearly demonstrate the proposed frequency controller's ability to dump extra power when the customer load varies while maintaining a consistent supply frequency.

Parameter identification for load frequency control using fuzzy FOPID in power system

Purpose This paper aims to suggest the parameter identification of load frequency controller in power system. Design/methodology/approach The suggested control approach is established using fuzzy logic to design a fractional order load frequency controller. A new suitable control law is developed using fuzzy logic, and based on this developed control law, the unknown parameters of the fractional order proportional integral derivative (FOPID) controller are derived using an optimization technique, which is being used by minimizing the integral square error. In addition, to confirm the effectiveness of the proposed control design approach, numerous simulation tests were carried out on an actual single-area power system. Findings The obtained results reveal the superiority of the suggested controller as compared to the recently developed controllers with regard to time response specifications and quantifiable indicators. Additionally, the potential of the suggested controller is also observed by improving the load disturbance rejections under plant parametric uncertainty. Originality/value To the best of the authors’ knowledge, the work is not published anywhere else.

Unmanned Aerial Vehicle Forensic Investigation Process : Dji Phantom 4 Drone as A Case Study

A drone, technological term Unmanned aerial vehicle (UAV), means any aircraft operating or designed to operate autonomously or to be piloted remotely without a pilot on board. Essentially, a drone is a flying robot that can be remotely controlled or fly autonomously through software-controlled flight plans in their embedded systems, working in conjunction with onboard sensors and GPS. The easy accessibility to everyone led to an increase in drone crime. Criminals are using drones in many malicious activities worldwide due to the drones’ ability to offer live-stream, real-time video, and image capture, along with the ability to fly and transport goods. Terrorist groups are using aerial drones to conduct and coordinate attacks. Forensic laboratories have been receiving Drone cases throughout India. The drone has been built that can be operated by a radio frequency controller and send live audio-visual feedback. This paper aims to provide a case study of Drone, DJI Phantom 4 and presents the acquisition, examination, analysis of important artifacts recorded flight data and discuss some possible data extractions from its flash memory, GPS (navigator) & SD card.