There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Chapter 8 establishes the relationship between the input and output power spectral densities of a linear system. Limitations on results are carefully detailed and the case of oscillator noise is considered. The theory is extended to multiple input-multiple output systems.

Linear System Theory

Power systems are the most complex systems that have been created by men in history To operate such systems in a stable mode, several control loops are needed Voltage frequency plays a vital role in power systems which need to be properly controlled To this end, primary and secondary frequency control loops are used to control the frequency of the voltage in power systems Secondary frequency control, which is called Load Frequency Control (LFC), is responsible for maintaining the frequency in a desirable level after a disturbance Likewise, the power exchanges between different control areas are controlled by LFC approaches In recent decades, many control approaches have been suggested for LFC in power systems This paper presents a comprehensive literature survey on the topic of LFC In this survey, the used LFC models for diverse configurations of power systems are firstly investigated and classified for both conventional and future smart power systems Furthermore, the proposed control strategies for LFC are studied and categorized into different control groups The paper concludes with highlighting the research gaps and presenting some new research directions in the field of LFC

Challenges and Opportunities of Load Frequency Control in Conventional, Modern and Future Smart Power Systems: A Comprehensive Review

In this paper, a new load frequency control (LFC) for multi-area power systems is developed based on the direct–indirect adaptive fuzzy control technique. LFCs for each area are designed based on availability of frequency deviation of each area and tie-line power deviation between areas. The fuzzy logic system approximation capabilities are exploited to develop suitable adaptive control law and parameter update algorithms for unknown interconnected LFC areas. An ${H}_{\infty}$ tracking performance criterion is introduced to minimize the approximation errors and the external disturbance effects. The proposed controller guarantees stability of the overall closed-loop system. Simulation results for a real three-area power system prove the effectiveness of the proposed LFC and show its superiority over a classical PID controller and a type-2 fuzzy controller.

Load Frequency Control of a Multi-Area Power System: An Adaptive Fuzzy Logic Approach

Global energy challenges have driven the adoption of renewable energy sources. Usually, an intelligent energy and battery management system is deployed to harness the renewable energy sources efficiently, whilst maintaining the reliability and robustness of the power system. In recent years, the battery-supercapacitor based hybrid energy storage system (HESS) has been proposed to mitigate the impact of dynamic power exchanges on battery's lifespan. This study reviews and discusses the technological advancements and developments of battery-supercapacitor based HESS in standalone micro-grid system. The system topology and the energy management and control strategies are compared. The study also discusses the technical complexity and economic sustainability of a standalone micro-grid system. A case study of a standalone photovoltaic-based micro-grid with HESS is presented.

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Battery-supercapacitor hybrid energy storage system in standalone DC microgrids: areview

Adaptive fuzzy logic load frequency control of multi-area power system

This paper considers design and implementation of a computer-controlled sun tracking system to enhance the power output of photovoltaic (PV) solar panels. The tracking system is driven by two permanent magnet DC motors to provide motion of the PV panels in two axes. The control of the dual axis tracking system is not an easy task due to nonlinear dynamics and unavailability of the model parameters. Therefore, a PC-based fuzzy logic control algorithm utilizing the knowledge of the system behavior is designed in order to achieve the control objectives. The implementation of such a controller is realized by building an interfacing card consisting of sensor data acquisition, motor driving circuits, signal conditioning circuits and serial communication with the PC. A set of laboratory demonstrations shows the capability of the system to track the sun effectively.

Design and implementation of a fuzzy logic computer-controlled sun tracking system

This paper proposes an adaptive fuzzy logic control scheme for a class of strict-feedback nonlinear systems with unknown backlash-like hysteresis The proposed controller exploits the properties of the newly developed L1 adaptive control in conjunction with the approximation capability of fuzzy systems The developed controller is fast, the adaptation can be as fast as the CPU permits, and robust by virtue of the L1 adaptive control structure and the direct estimation of the system nonlinear functions via fuzzy logic systems As a result, the proposed L1 adaptive fuzzy controller has a simpler form and requires fewer adaptation parameters The inverted pendulum and Duffing forced oscillation systems are used in simulation studies to verify the effectiveness of the proposed L1 adaptive fuzzy control scheme

Hassan A. Yousef

Papers

Load Frequency Control of a Multi-Area Power System: An Adaptive Fuzzy Logic Approach

Adaptive fuzzy logic load frequency control of multi-area power system

Design and implementation of a fuzzy logic computer-controlled sun tracking system

L1 Adaptive fuzzy controller for a class of nonlinear systems with unknown backlash-like hysteresis

Brief paper: Adaptive fuzzy decentralized control for interconnected MIMO nonlinear subsystems