Magnetic field evaluation around 400 kv underground power cable under harmonics effects

Power lines or underground power cables generate electromagnetic interaction with other objects near to them. This study evaluates the magnetic field emitted by underground extra high voltage cables. The presented work aims to show a numerical simulation of the magnetic field of a buried 400 kV underground power line, which is used as a novel prototype in several countries at a short distance. The underground power cable study, in the presence of the current harmonics at different positions, with time variation by finite element resolution, using Comsol Multiphysics with Matlab software in two dimensions. The simulation results illustrate the magnetic flux density variation-in terms of amplitude and distribution as a function of different actual harmonics rates. The underground cable performance and magnetic field have affected by the harmonics effects. The maximum magnetic induction levels generated by significant harmonics are superior to the limits recommended by the international standard norms. In this paper, shielding has been used as an appropriate remedy to attenuate the magnetic field

Utilisation de la télédétection pour la cartographie de l’occupation du sol : cas des monts de Beni-Chougrane (Mascara-Algerie Nord Occidentale)

La cartographie rapide de l’occupation du sol permet d’appréhender la dynamique des formations végétales et contribuera à mieux aménager les espaces. La télédétection constitue un outil permettant de répondre à cette préoccupation. La carte d’occupation du sol obtenue par la méthodes universelle (Corine Land cover ) est répartie en unités et en classes d’occupation dans la zone étudiée. La classification supervisée a permis de regrouper et de classer les différents objets au sol en fonction des finalités que nous nous étions fixées au départ. Ainsi il a été obtenu 9 classes d’occupation du sol : eau, verger, matorral, pelouse, végétation clairsemée, sol nu, oléo-lentisque et forêts. Cette distribution permet de suivre la dynamique de ces entités et de cartographier leur évolution. La cartographie obtenue permettra de mettre en place par entité les principales recommandations d’aménagement. Une synthèse cartographique assistée par l’ordinateur constitue donc un outil permettant d’appréhender dans de meilleures conditions toute approche d’aménagement

Application of a new hybridization to solve economic dispatch problem on an Algerian power system without or with connection to a renewable energy

The most important contribution of this article is the use of four metaheuristic approaches to tackle the problem of economic dispatching, with the goal to study the influence of the injection of a renewable energy source on the electricity cost in the Algerian network, and minimizing the production cost of electrical energy while accounting for transmission losses. A Genetic Algorithm (GA) (a real coding) and Egyptian Vulture Optimization Algorithm (EVOA), as well as two hybridizations between the metaheuristics: Classic and Modern hybridization (C.H.GA-EVOA, M.H.GA-EVOA), are presented in this work. These techniques are used to address optimization difficulties of two Algerian electricity networks. The first has three system units, whereas the second has fifteen system units. The second electricity network is connected to a solar energy source. The findings obtained are compared with other techniques to validate the high performance of the suggested methods for addressing the economic dispatch issue. This study demonstrates that EVOA and C.H.GA-EVOA provide trustworthy results, and that M.H.GA-EVOA surpasses them

Application of a new hybridization to solve economic dispatch problem on an Algerian power system without or with connection to a renewable energy

The most important contribution of this article is the use of four metaheuristic approaches to tackle the problem of economic dispatching, with the goal to study the influence of the injection of a renewable energy source on the electricity cost in the Algerian network, and minimizing the production cost of electrical energy while accounting for transmission losses. A Genetic Algorithm (GA) (a real coding) and Egyptian Vulture Optimization Algorithm (EVOA), as well as two hybridizations between the metaheuristics: Classic and Modern hybridization (C.H.GA-EVOA, M.H.GA-EVOA), are presented in this work. These techniques are used to address optimization difficulties of two Algerian electricity networks. The first has three system units, whereas the second has fifteen system units. The second electricity network is connected to a solar energy source. The findings obtained are compared with other techniques to validate the high performance of the suggested methods for addressing the economic dispatch issue. This study demonstrates that EVOA and C.H.GA-EVOA provide trustworthy results, and that M.H.GA-EVOA surpasses them

Investigation on New Metaheuristic Algorithms for Solving Dynamic Combined Economic Environmental Dispatch Problems

In this paper, the dynamic combined economic environmental dispatch problems (DCEED) with variable real transmission losses are tackled using four metaheuristics techniques. Due to the consideration of the valve-point loading effects (VPE), DCEED have become a non-smooth and more complex optimization problem. The seagull optimization algorithm (SOA), crow search algorithm (CSA), tunicate swarm algorithm (TSA), and firefly algorithm (FFA), as both nature and biologic phenomena-based algorithms, are investigated to solve DCEED problems. Our proposed algorithms, SOA, TSA, and FFA, were evaluated and applied on the IEEE five-unit test system, and the effectiveness of the proposed CSA approach was applied on two-unit, five-unit, and ten-unit systems by considering VPE. We defined CSA for different objective functions, such as cost of production, emission, and CEED, by considering VPE. The obtained results reveal the efficiency and robustness of the CSA compared to SOA, TSA, FFA, and to other optimization algorithms reported recently in the literature. In addition, Matlab simulation results show the advantages of the proposed approaches for solving DCEED problems

Investigation on New Metaheuristic Algorithms for Solving Dynamic Combined Economic Environmental Dispatch Problems

In this paper, the dynamic combined economic environmental dispatch problems (DCEED) with variable real transmission losses are tackled using four metaheuristics techniques. Due to the consideration of the valve-point loading effects (VPE), DCEED have become a non-smooth and more complex optimization problem. The seagull optimization algorithm (SOA), crow search algorithm (CSA), tunicate swarm algorithm (TSA), and firefly algorithm (FFA), as both nature and biologic phenomena-based algorithms, are investigated to solve DCEED problems. Our proposed algorithms, SOA, TSA, and FFA, were evaluated and applied on the IEEE five-unit test system, and the effectiveness of the proposed CSA approach was applied on two-unit, five-unit, and ten-unit systems by considering VPE. We defined CSA for different objective functions, such as cost of production, emission, and CEED, by considering VPE. The obtained results reveal the efficiency and robustness of the CSA compared to SOA, TSA, FFA, and to other optimization algorithms reported recently in the literature. In addition, Matlab simulation results show the advantages of the proposed approaches for solving DCEED problems