Mohamed Boudour

Facts allocation for power systems voltage stability enhancement using MOPSO

Location of the static VAR compensator (SVC) and other types of FACTS devices is important for the enhancement of practical power systems voltage stability. In this paper, a Multi-objective particle swarm optimization (MOPSO) is used to solve a mixed continuous-discrete multi-objective optimization problem in order to find optimal location of FACTS. Various objectives are considered, namely voltage stability improvement, real power loss minimization and load voltage deviations minimization. Simulations are performed on IEEE 14 test system for optimal location and size of FACTS devices. Analysis of the initial conditions to determine the voltage stability margins and a contingency analysis to determine the critical outages with respect to the voltage stability margin are also examined in order to evaluate their effect on the location analysis. The obtained results show that with the allocation of FACTS devices with the proposed method, the voltage stability is considerably enhanced in both normal state and critical contingencies. The calculation of the load margin demonstrates the effectiveness of the proposed method.

Optimal placement of FACTS devices for multi-objective voltage stability problem

In this paper, a new method for optimal locating multi-type FACTS devices in order to optimize multi-objective voltage stability problem is presented. The proposed methodology is based on a new variant of Particle Swarm Optimization (PSO) specialized in multi-objective optimization problem known as Non-dominated Sorting Particle Swarm Optimization (NSPSO). The crowding distance technique is used to maintain the Pareto front size at the chosen limit, without destroying its characteristics. To aid the decision maker choosing the best compromise solution from the Pareto front, the fuzzy-based mechanism is employed for this task. NSPSO is used to find the optimal location and setting of two types of FACTS namely: Thyristor Controlled Series Compensator (TCSC) and Static Var Compensator (SVC) that maximize Static Voltage Stability Margin (SVSM), reduce Real Power Losses (RPL), and Load Voltage Deviation (LVD). The optimization is carried out on two and three objective functions for various FACTS combinations. The thermal limits of lines and voltage limits of load buses are considered as security constraints. The simulation results show the effectiveness of the proposed NSPSO to solve the multiobjective optimization problem considered and capture Pareto optimal solutions with satisfactory diversity characteristics.

New Evolutionary Technique for Optimization Shunt Capacitors in Distribution Networks

New Evolutionary Technique for Optimization Shunt Capacitors in Distribution Networks The paper presents a new evolutionary technique for optimizing on one part the numbers, the sizes and locations of shunt capacitors in radial distribution network in away to minimize the annual cost of active power losses with the improvement of voltage profiles of different buses. The technique is applied on 10 buses network and on IEEE 34 buses network test. The results are compared with ones of previous studies using heuristiques methods and the same network tests.

Optimal placement and parameter settings of unified power flow controller device using a perturbed particle swarm optimization

This paper presents the application of a perturbed particle swarm optimization (PPSO) technique to find optimal location and parameter setting of unified power flow controller (UPFC) for enhancing power system security under single line contingencies. A contingency analysis is first outlined to identify the most severe line outage contingencies, considering lines overload and bus voltage limit violations as a performance index. Then, the proposed algorithm is applied to find out the optimal location and parameter setting of UPFC under the determined contingency scenario. Simulations are performed on IEEE 14 bus system. The results indicate that PPSO is a powerful optimization technique and enhance the convergence of the standard PSO. Installing UPFC in the optimal location determined by the proposed approach can significantly enhance the security of power system by eliminating or minimizing the number of overloaded lines and the bus voltage limit violations.

Optimal load frequency control based on hybrid bacterial foraging and particle swarm optimization

This paper presents an application of a hybrid technique combining bacterial foraging with particle swarm optimization (BF-PSO) for determining the optimal values for the proportional-integral-derivation (PID) controller for a load frequency control (LFC) of two-area interconnected power system. This method is compared to the heuristic optimization method (PSO) and to bacterial foraging optimization (BFO) thereby to the traditional Ziegler-Nichols method. The results of PID-tuning are compared with the results of I, ID and PI controllers. The transient responses are shown due to step load disturbances in area-1. The main primary objective is to suppress all the fluctuations of the system frequency and tie line power flow.

FACTS placement multiobjective optimization for reactive power system compensation

One of the problems responsible of power generation and transmission is the maintaining of an appropriate voltage profile by installation of reactive power supplies. In this paper, we propose a new technique for the optimal location and design of two kinds of Flexible AC Transmission System Devices (FACTS) namely: Satitic Var Compensator (SVC) and Thyristor Controlled Series Compensator (TCSC) handling the minimization of transmission losses in electrical network. Using the proposed scheme, the type, the location and the rating of FACTS devices are optimized simultaneously. The problem to solve is multi criteria under constraints related to the load flow equations, the voltages, the transformer turn ratios, the active and reactive productions and the compensation devices. Its resolution requires the employ of the advanced algorithms. Thus, we propose an approach based on the evolutionary algorithms (EA) to solve this problem multi criterion. It is about the NSGA-II method (Ellitist Non Dominated Sorting Genetic Algorithm). The Pareto front is obtained for continuous, discrete and multiple of five MVArs of compensator devices for the IEEE 57-bus test system.

Load Frequency Control in multi-area power system based on Fuzzy Logic-PID Controller

In an interconnected multi-area power system, as a power load demand varies randomly, in the case of any small sudden load change in any of the areas, both area frequency and tie-line power flow interchange also vary. The main goals of Load Frequency Control (LFC) are, to hold the frequency and the desired power output in the interconnected power system at the scheduled values and to control the change in the tie-line power flow between control areas. The purpose of this paper is to present basically an application of Fuzzy Logic Controller (FLC) based load frequency control using PID controller in multi-area interconnected power system. The fuzzy logic is employed to search for optimal values for the PID controller parameters. The three-area 9-unit model system is used for the simulation, and the transient responses are shown due to step load disturbances in area-1, area-2 and area-3. The main primary objective is to suppress all the fluctuation of the system frequency and tie-line power flow. By comparison to the conventional Ziegler-Nichols technique (Z-N) and to the heuristic Particle Swarm Optimization method (PSO), the effectiveness of the proposed method is confirmed.

Optimal load frequency control in interconnected power system using PID controller based on particle swarm optimization

Today load frequency control is becoming more important and significant in interconnected power system design and operation due to the complexity of power systems, changing structure, and emerging renewable energy sources. This paper presents an application of particle swarm optimization (PSO) algorithm for determining the optimal values for the proportional-integral-derivation (PID) controller for a load frequency control (LFC) of two-area interconnected power system having diverse sources of power generation. This method is compared to the traditional Ziegler-Nichols method. In order to analyze the load frequency control we propose to use a new method based on the implicit integration Trapezoidal rule and the iterative Newton-Raphson method. The two area power system is simulated for different load disturbances. The main primary objective is to suppress all the fluctuation of the system frequency and tie line power flow and the proposed method has proven to be very efficient.

New reactive power sources dispatch applied to the IEEE 57 nodes

Purpose – The purpose of this paper is to deal with a new dispatching and optimization of reactive power sources in power systems.Design/methodology/approach – The methodology is first based on an optimal movement of existing reactive sources as a first phase, then an optimal investment in a second phase and finally a combination of the two previous phases as the third one. The methodology showed also the advantage of a two‐levels procedure, considering an initial minimal compensation before minimizing the active losses. The solution of the global non‐linear problem is performed using the projected and augmented Lagrange method associated with the reduced gradient and the DFP methods.Findings – In waiting for new investment programs which are planned for limited periods, the study presents an alternative of optimizing the reactive power compensation by a movement of the power sources or some of them, satisfying all system constraints and minimizing also the active power losses.Originality/value – The plan...

Robust Power System Stabilizers Design Using Multi-objective Genetic Algorithm

Optimal locations and design of robust multimachine power system stabilizers (PSSs) using heuristic algorithms is presented in this paper. The tuning of PSS via a non-dominated sorting genetic algorithm (NSGA-II) is performed to obtain a set of compromise speed-damping solutions. The stabilizers are tuned to simultaneously shift the lightly damped and undamped electromechanical modes of all plants to a prescribed zone in the s-plane. A multiobjective problem is formulated to optimize a composite set of objective functions comprising the damping factor, and the damping ratio of the lightly damped electromechanical modes. The problem of robustly tuning of the power system stabilizers is solved by a nondominated sorting genetic algorithm (NSGA-II) with the eigenvalue-based multiobjective function. The efficacy of this technique in damping local and inter-area modes of oscillations in multimachine power systems is confirmed through nonlinear simulation results and eigenvalues analysis.