Optimal Scheduling Of Short Range Fixed Head Hydro- Thermal Plants - Couverture souple

., Sarbjeet Kaur, Manbir Kaur

9781723862809: Optimal Scheduling Of Short Range Fixed Head Hydro- Thermal Plants

Couverture souple

ISBN 10 : 1723862800 ISBN 13 : 9781723862809

Editeur : Independently published, 2018

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Optimal generation dispatch seeks to allocate the real and reactive power throughout the power system obtaining an optimal operating state that reduces costs and improves overall system efficiency. This problem can be formulated and solved as two separate problems. One is the economic dispatch problem which reduces system cost by allocating the real power among the online generating units. Another problem is the reactive power dispatch which improves system voltage profile and reduces system losses by allocating the reactive power efficiently. Modeling in the generation dispatch problem is critical to achieve optimal results. In the economic dispatch problem, the classical formulation presents deficiencies due to the simplicity of the models. Here, the power system is modeled through the power balance equation and generators are modeled with smooth quadratic cost functions and generator output side constraints. In the reactive power problem, a common approach is to model transformers and capacitor banks as continuous variables instead of the discrete variables. To improve power systems studies, new models are continuously being developed that result in a more efficient system operation. Cost functions that consider valve point loadings fuel switching and prohibited operating zones as well as constraints that provide a more accurate representation of the system such as: emissions line flow.These improved models generally increase the level of complexity of the optimization problem due to the nonlinearity associated with them. Many different traditional optimization methods have been used to solve the classical economic dispatch and reactive power dispatch problems including: Steepest Descent, Newton, Interior Point Methods, Linear Programming, Quadratic Programming and Dynamic Programming. Some of these techniques are not capable of solving efficiently optimization problems with a non-convex, non-continuous and highly nonlinear solution space. Other techniques become inefficient since they require too many computational resources to provide accurate results for large scale systems such as electric power systems. Recent advances in computation and the search for better results of complex Optimization problems have formented the developments of the techniques using Artificial neural networks. Artificial Neural Networks (ANN) are gaining popularity in various fields of engineering including electrical power systems due to their high computational rates and robustness. One of the ANN models extensively used for power system applications is the multilayer perceptron model based on back propagation algorithm.

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