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Application of a New Meta-heuristic Algorithm using Egyptian Vulture Optimization for Economic DOI:10.15199/48.2019.06.11

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The industrialization and the growth of the population are the first factors for which the consumption of electrical energy increases regularly. As well, to have a balance between production and consumption, it is at first sight necessary to increase the number of power plants, lines, transformers etc[1], which implies an increase of the cost and a degradation of the natural environment. Accordingly, it is important today to have of mesh networks and work close to the limits of stability [2]-[5]. The exploitation of electrical networks requires to improve the management of energy by introducing the costs of production and minimizing the transmission losses. Scientific research is oriented toward the best form of economic distribution of electrical energy in order to minimize the costs of production [6]-[10]. For a good operation of the network, we need to solve the problems of a technical and economic, which requires the improvement of the management of electrical energy by reducing the cost of production and on the other hand by keeping the balance between production and consumption [11]. The current objective of an economic dispatch is the electrical production with a low cost of fuel. The general problem of the production and the optimal distribution of powers in a production system -Transport- consumption are therefore very complex. Several methods like PSO [12], bat algorithm [13], [14], Honey bee swarm [15]˗[18] league championship algorithm [19], [20], cuckoo search [21], simulated annealing [22], [23], krill herd optimization [24]-[29],Virus Optimization Algorithm [30]-[32], Magnetic Optimization Algorithms [21], [23], etc, have been developed to resolve this problem Here, a new meta-heuristic technique Egyptian Vulture Optimization [33], [34] is implemented to solve economic dispatch problems, and present its effectiveness using three, six, fifteen and forty generating units test systems. The result shows t[...]

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