Abdelhay A. Sallam

Bio: Abdelhay A. Sallam is an academic researcher from Port Said University. The author has contributed to research in topics: Electric power system & AC power. The author has an hindex of 16, co-authored 43 publications receiving 1433 citations. Previous affiliations of Abdelhay A. Sallam include Suez Canal University.

Damping controller design for power system oscillations using global signals

Abstract: This paper describes a new power system stabilizer (PSS) design for damping power system oscillations focusing on interarea modes. The input to the PSS consists of two signals. The first signal is mainly to damp the local mode in the area where PSS is located using the generator rotor speed as an input signal. The second is an additional global signal for damping interarea modes. Two global signals are suggested; the tie-line active power and speed difference signals. The choice of PSS location, input signals and tuning is based on modal analysis and frequency response information. These two signals can also be used to enhance damping of interarea modes using SVC located in the middle of the transmission circuit connecting the two oscillating groups. The effectiveness and robustness of the new design are tested on a 19-generator system having characteristics and structure similar to the Western North American grid.

An adaptive protection scheme for advanced series compensated (ASC) transmission lines

Abstract: This paper presents an adaptive protection scheme for advanced series compensated (ASC) transmission lines. The scheme is based on Kalman and adaptive Kalman filters. The adaptive scheme utilizes the differences in the transient current signals for faults encountering and not encountering the ASC to determine the fault location with respect to the ASC and the faulted phases. Equations to determine the line impedance to the fault on these lines are developed. The adaptive scheme is tested for faults along and outside the protected line using EMTP simulated data.

Enhancing the particle swarm optimizer via proper parameters selection

Abstract: Unlike many other computational intelligence techniques, the particle swarm optimizer (PSO) has few parameters to tune. However, properly chosen values for these parameters can positively affect the accuracy of the obtained results as well as the time consumed during the search process. Many parameters have been added to the originally developed PSO to modify or to improve the performance of the technique but yet, the swarm size, number of iterations and individuals flying velocities are still the most dominant parameters. The paper examines the PSO's parameters, describes their characteristics and provides guidelines for determining values for these parameters. A quick statistical experiment is used to fine-tune these parameters for the class of constrained optimization problem considered. The results show that the particle swarm optimizer is quite robust and provides good solution for reasonable choice of the values of the parameters within fairly wide range.

Electric Distribution Systems

Abstract: Preface. Acknowledgment. Part I. Fundamental Concepts. Chapter 1. Main Concepts of Electric Distribution Systems. Chapter 2. Load Demand Forecasting. Part II. Protection and Distribution Switchgears. Chapter 3. Earthing of Electric Distribution Systems. Chapter 4. Short Circuit Studies. Chapter 5. Protection of Electric Distribution Systems. Chapter 6. Distribution Switchgears. Part III. Power Quality. Chapter 7. Electric Power Quality. Chapter 8. Voltage Variations. Chapter 9. Power Factor Improvement. Chapter 10. Harmonics in Electric Distribution Systems. Chapter 11. Harmonics Effect Elimination. Part IV. Management and Monitoring. Chapter 12. Demand Side Management and Energy Efficiency. Chapter 13. SCADA Systems. Part V. Distributed Generation. Chapter 14. Distributed Generation. REFERENCES. INDEX. IEEE PRESS SERIES ON POWER ENGINEERING.

Particle Swarm Optimization: Basic Concepts, Variants and Applications in Power Systems

Abstract: Many areas in power systems require solving one or more nonlinear optimization problems. While analytical methods might suffer from slow convergence and the curse of dimensionality, heuristics-based swarm intelligence can be an efficient alternative. Particle swarm optimization (PSO), part of the swarm intelligence family, is known to effectively solve large-scale nonlinear optimization problems. This paper presents a detailed overview of the basic concepts of PSO and its variants. Also, it provides a comprehensive survey on the power system applications that have benefited from the powerful nature of PSO as an optimization technique. For each application, technical details that are required for applying PSO, such as its type, particle formulation (solution representation), and the most efficient fitness functions are also discussed.

Particle swarm optimization versus genetic algorithms for phased array synthesis

Abstract: Particle swarm optimization is a recently invented high-performance optimizer that is very easy to understand and implement. It is similar in some ways to genetic algorithms or evolutionary algorithms, but requires less computational bookkeeping and generally only a few lines of code. In this paper, a particle swarm optimizer is implemented and compared to a genetic algorithm for phased array synthesis of a far-field sidelobe notch, using amplitude-only, phase-only, and complex tapering. The results show that some optimization scenarios are better suited to one method versus the other (i.e., particle swarm optimization performs better in some cases while genetic algorithms perform better in others), which implies that the two methods traverse the problem hyperspace differently. The particle swarm optimizer shares the ability of the genetic algorithm to handle arbitrary nonlinear cost functions, but with a much simpler implementation it clearly demonstrates good possibilities for widespread use in electromagnetic optimization.

A Survey of Particle Swarm Optimization Applications in Electric Power Systems

Abstract: Particle swarm optimization (PSO) has received increased attention in many research fields recently. This paper presents a comprehensive coverage of different PSO applications in solving optimization problems in the area of electric power systems. It highlights the PSO key features and advantages over other various optimization algorithms. Furthermore, recent trends with regard to PSO development in this area are explored. This paper also discusses PSO possible future applications in the area of electric power systems and its potential theoretical studies.

Wide-area measurement based stabilizing control of large power systems-a decentralized/hierarchical approach

Abstract: The aim of this paper is to assess the capability of the emerging synchronized phasor measurement technology in improving the overall stability of the Hydro-Quebec transmission system through supplementary modulation of voltage regulators. Following a thorough singular value and eigenvalue analysis of the system dynamic interactions, five control sites consisting of four generators and one synchronous condenser are chosen to implement new power system stabilizers with a supplementary input from remote phasor measuring units, geographically spread over nine electrically coherent areas. Since the remote feedback loops are built on top of an existing decentralized control system, this design approach results in a decentralized/hierarchical control architecture with significant advantages in terms of reliability and operational flexibility. A systematic control and measurement pairing yielded four dominant natural loops, each associated with a significant open-loop inter-area oscillatory mode at 0.06, 0.4, 0.7 and 0.95 Hz respectively. These PSSs have a speed sensitive local loop operating in the usual way, and a wide-area measurement based global loop which involves a single differential frequency signal between two suitably selected areas. The tuning and coordination technique for these advanced multiple input signals PSSs is described. Their impacts on the system is assessed using both small-signal analysis and nonlinear simulations in a transient stability program. Wide-area stabilizing controllers have a significant potential in improving the dynamic performance of the Hydro-Quebec's existing power system.

Recent advances in particle swarm

Abstract: This paper reviews the development of the particle swarm optimization method in recent years. Included are brief discussions of various parameters. Modifications to adapt to different and complex environments are reviewed, and real world applications are listed.