Papers by Sahbi Marrouchi
2014 15th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA), 2014
ABSTRACT
2015 IEEE 15th International Conference on Environment and Electrical Engineering (EEEIC), 2015
This study deals with a newly-conceived control strategy for three-phase grid connected VSIs used... more This study deals with a newly-conceived control strategy for three-phase grid connected VSIs used for distributed generation (DG) system with renewable energy sources. This strategy has been called SCCA (Symmetrical Component Control Algorithm). The SCCA aims that DG power plants can avoid overcurrent while helping to mitigate the adverse effects of unbalanced voltage sags for continuous operation. For this, it accomplished simultaneously the control of the injected currents and active and reactive power flow. A simulation comparison among five published methods and SCCA is presented in terms of quality of the injected current and ripple of the injected powers. The extensive MATLAB/Simulink simulation studies of SCCA concept demonstrate that the proposed strategy outperforms the majority of already published strategies in terms of the above criteria.
2015 IEEE 15th International Conference on Environment and Electrical Engineering (EEEIC), 2015
This paper presents a new approach based on the combination of the Particle Swarm Optimization an... more This paper presents a new approach based on the combination of the Particle Swarm Optimization and the gradient method to solve the unit commitment (UC) problem. The proposed strategy optimizes the combination of production units operations and determines the appropriate operational scheduling of each production units to satisfy the expected consumption during a well specific duration. Each production unit is conducted to constraints that render this problem complex, combinatorial and nonlinear. The resolution of the UC Problem is conducted to several constraints that take into account the minimum up and minimum down time constraints, start-up cost and spinning reserve. The adopted approach was applied to an IEEE electrical network 14 buses containing 5 production units and the simulation results have clearly proven that the Gradient-PSO method was very competent in optimizing the UC problem in comparison to other existing methods.
Studies in Fuzziness and Soft Computing, 2014
ABSTRACT
Mathematical Problems in Engineering, 2014
Due to the continuous increase of the population and the perpetual progress of industry, the ener... more Due to the continuous increase of the population and the perpetual progress of industry, the energy management presents nowadays a relevant topic that concerns researchers in electrical engineering. Indeed, in order to establish a good exploitation of the electrical grid, it is necessary to solve technical and economic problems. This can only be done through the resolution of the Unit Commitment Problem. Unit Commitment Problem allows optimizing the combination of the production units’ states and determining their production planning, in order to satisfy the expected consumption with minimal cost during a specified period which varies usually from 24 hours to one week. However, each production unit has some constraints that make this problem complex, combinatorial, and nonlinear. This paper presents a comparative study between a strategy based on hybrid gradient-genetic algorithm method and two strategies based on metaheuristic methods, fuzzy logic, and genetic algorithm, in order t...
2013 International Conference on Electrical Engineering and Software Applications, 2013
The excessive increase in the number of subscribers in the electrical grid requires a flexible co... more The excessive increase in the number of subscribers in the electrical grid requires a flexible control of this electrical network and a better reliability of the offered power quality. Thus, several defense plans are omnipresent to ensure stability, continuity of service and to overcome some disturbances which can affect the electrical grid. In this context, we present in this paper the development of a new control strategy used a compensator UPFC based on fuzzy controllers. We simulated this strategy in the IEEE test 14 buses network and the results were promising.
2019 21st International Middle East Power Systems Conference (MEPCON), 2019
This paper proposes a combined analytical and metaheuristic optimization algorithm for optimal al... more This paper proposes a combined analytical and metaheuristic optimization algorithm for optimal allocation of multiple types of Distributed Generators (DGs) in radial distribution networks to minimize the total power losses. The analytical technique based on the exact loss formula is used to calculate the optimal size of the DG unit at a certain bus. However, the analytical technique may not be suitable to allocate multiple DGs types due to the mass of calculations, hence, Lightning Search Algorithm (LSA) is combined with the analytical technique to find the optimal locations. Like any random search-based optimization algorithm, LSA faces some issues such as low convergence rate and trapping in local solutions. So, to avoid these kinds of problems, a proposed Chaotic LSA (CLSA) based on Gauss/mouse map is established. The gauss/mouse map is used to change random LSA forking occurrence instead of using the random variable. The proposed Combined Analytical CLSA (CA-CLSA) is validated u...
Proceedings of the 1st International Conference on Smart Innovation, Ergonomics and Applied Human Factors (SEAHF), 2019
Solving the Unit Commitment problem (UCP) optimizes the combination of production units operation... more Solving the Unit Commitment problem (UCP) optimizes the combination of production units operations and determines the appropriate operational scheduling of production units to satisfy the expected consumption which varies from one day to one month. This paper represents a new strategy combining three optimization methods: Tabu search, Particle swarm optimization and Lagrangian relaxation methods in order to develop a proper unit commitment scheduling of the production units while reducing the production cost during a definite period. The proposed strategy has been implemented on a the IEEE 9 bus test system containing 3 production unit and the results were promising compared to strategies based on meta-heuristic and deterministic methods.
2017 International Conference on Advanced Systems and Electric Technologies (IC_ASET), 2017
This paper present a new and accurate scheme for fault classification of EHV transmission lines u... more This paper present a new and accurate scheme for fault classification of EHV transmission lines using fuzzy logic system. The fault classification scheme is developed by using only the post-fault magnitude of three phases current and its symmetrical components. The proposed fault classification technique is able to classify all faults type can be affect a transmission line such as the single-phase to ground faults, two-phases faults, two-phases to ground faults and three-phases faults with high accuracy under wide variety of fault conditions. The proposed scheme has a good performance in high fault conditions such as high fault resistances, high fault inception angles and high fault distances to fault from relaying point. Large numbers of test cases are generated to verify the performance of proposed scheme. The simulation studies have been carried out by using Matlab software and Matlab fuzzy-logic toolbox.
2017 International Conference on Advanced Systems and Electric Technologies (IC_ASET)
Unit Commitment Problem (UCP) is considered as a nonlinear mixed-integer combinatorial highly con... more Unit Commitment Problem (UCP) is considered as a nonlinear mixed-integer combinatorial highly constrained optimization problem divided on two sub problems: binary UC scheduling and economic dispatch (ED). UCP is used to determine the appropriate operational scheduling of the units' production to satisfy the expected consumption at every hour interval under different constraints. In the last decades, many algorithms have been developed to optimize the UCP, but energy managers are still working in this area to find new hybrid algorithms to make the problem more realistic. This paper represents a new strategy combining Particle swarm optimization and Tabu Search considered as meta-heuristic methods and Lagrangian relaxation considered as deterministic methods in order to develop a proper unit commitment scheduling of the production units while reducing the production cost during a definite period. The proposed strategy has been implemented on a the IEEE 9 bus test system containing 3 production unit and the results were promising compared to strategies based on meta-heuristic and deterministic methods.
2018 15th International Multi-Conference on Systems, Signals & Devices (SSD), 2018
The objective of this paper is the theoretical study and numerical simulation of a Series Active ... more The objective of this paper is the theoretical study and numerical simulation of a Series Active Filter using the modulated hysteresis controller to protect sensitive loads against voltage disturbances of the electrical network. The modulated hysteresis is retained because it simultaneously guarantees the robustness of the system and a fixed switching frequency. The identification of the reference voltages was carried out using the reference method linked to synchronism. The simulation results obtained show the efficiency of the proposed model which leads to better rejections of the voltage disturbances of the electrical network.
Under unbalanced grid conditions, the control of the instantaneous active and reactive power caus... more Under unbalanced grid conditions, the control of the instantaneous active and reactive power causes the injection of unbalanced currents into the utility grid. Especially, the power oscillating terms that appear due to the interaction between different sequences voltages and currents remains an important issue. This problematic requires the design of consistent arrangements to calculate the current references that should be exchanged with the grid by the grid side converter (GSC). This paper introduces a mechanism of negative-sequence injection based on the control of d-q currents coordinates. Besides, a comparison study of the design of current controllers, using a generic vector approach, to enhance unbalance-fault ride-through capability of dispersed generation has been proposed. The performance of entire control system is evaluated by time domain simulations with MATLAB/Simulink. The achieved results have helped to facilitate, according the preferential issue, the choice for fau...
2018 15th International Multi-Conference on Systems, Signals & Devices (SSD), 2018
Solving the Unit Commitment problem (UCP) optimizes the combination of production units operation... more Solving the Unit Commitment problem (UCP) optimizes the combination of production units operations and determines the appropriate operational scheduling of each production units to satisfy the expected consumption which varies from one day to one month. Besides, each production unit is conducted to constraints that render this problem complex, combinatorial and nonlinear. In this paper, we proposed a new strategy based on the combination of an improved the Particle Swarm Optimization method and the genetic algorithm applied to an IEEE electrical network 30 buses containing 6 production units to solve the Unit Commitment problem in one side and to find an optimized combination scheduling in the other side leading to minimize the total production cost. Our strategy differs from other evolutionary computing in enhancing the searching ability and helping to find more optimal solutions enabling a minimal production cost while considering a best unit commitment scheduling.
Advances in Science, Technology and Engineering Systems Journal
Solving the Unit Commitment problem (UCP) optimizes the combination of production units operation... more Solving the Unit Commitment problem (UCP) optimizes the combination of production units operations and determines the appropriate operational scheduling of each production units to satisfy the expected consumption which varies from one day to one month. Besides, each production unit is conducted to constraints that render this problem complex, combinatorial and nonlinear. In this paper, we proposed a new strategy based on the combination three optimization methods: Tabu search, Particle swarm optimization and Lagrangian relaxation methods in order to develop a proper unit commitment scheduling of the production units while reducing the production cost during a definite period. The proposed strategy has been implemented on a the IEEE 9 bus test system containing 3 production unit and the results were promising compared to strategies based on metaheuristic and deterministic methods.
TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES
This paper addresses the problem of estimating the time series of a gene expression using nonline... more This paper addresses the problem of estimating the time series of a gene expression using nonlinear Bayesian filtering algorithms. The response of gene regulatory networks (GRNs) to functional requirements in the cell and environmental conditions evolves over time. Dynamic biological processes such as cancer progression and treatment recovery depend on the collected genetic profiles. These processes are behind genetic interactions that rewire over the course of time. The GRN was formulated as a nonlinear and non-Gaussian dynamic system defined by the gene measurement model and the unknown state is an evolution of the gene model. However, the GRN has a high dimensional space where most of nonlinear Bayesian filtering algorithms are ineffective in high dimensional spaces. Therefore, many authors have introduced various techniques to overcome what has become known as the curse of dimensionality. This paper presents a comparative study between extended Kalman filter, unscented Kalman filter and derivatives of particle filters, in tracking the evolution of gene expression over time. Application of the nonlinear Bayesian filtering algorithms to estimate the evolution of gene expression from synthetic and real data, shows that the unscented particle filter (UKF-PF) provides promising and robust results compared to other filters. Furthermore, UKF-PF provides an alternative solution to the problem of modeling gene regulatory networks.
International Journal of Engineering & Technology
This paper presents a comparative study between a new strategy based on hybrid Gradient-Genetic ... more This paper presents a comparative study between a new strategy based on hybrid Gradient-Genetic Algorithm method and metaheuristic methods for solving Unit Commitment problem. Strategies have been applied on the IEEE electrical network 14 bus test system for a variable load profile during a discretized margin of time (24-hour time requirement). The right choice of the initial population and the best knowledge of the technical constraints specific to each generator (power balance constraints, Spinning reserve constraints, minimum up time, minimum down time ) suggests the possibility of obtaining improvements in the time execution. The adopted strategy has presented high performance both for minimizing the production cost and for the rapidity of convergence to optimal solutions and is promising compared to Genetic algorithm.
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Papers by Sahbi Marrouchi