Abstract: The events such as the increase of load demands constantly in power systems, the continuous growth of electricity networks, the use of new technologies and the controls have led to the emergence of system stability problems in different structures. For the design and operation of the power system in the optimum level, instabilities in different ways and their relations with each other should be revealed clearly. To prevent great economic losses in the system as a result of the possible instabilities, it is necessary to predict stability criteria and do the necessary regulatory works. In this study, critical values for the system voltage stability have been obtained with the Power System Analysis Toolbox (PSAT) program. By using obtained values, artificial neural network (ANN) and least squares support vector mechanism (LSSVM) algorithms have been determined with the voltage stability critical values. The achievements of ANN and LSSVM algorithms, trained with the help of power system vo

• Publication Date: 13-Mar-2016
• DOI: 10.15224/978-1-63248-087-3-56
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Abstract: There is increasing use of the public cloud by governments; however, this use is for non-critical systems and non-sensitive data. The potential that the public cloud has for government use lies not only in the well-known benefits of cost and scalability, but also as a more permanent solution for providing e-services to citizens and as a solution for an advanced form of digital continuity whereby in the case of a national crisis, the government can continue to function in the public cloud on an indefinite basis. To take advantage of the public cloud in this way it becomes necessary for governments to place sensitive data and critical systems in the public cloud, which they are reluctant to do because of security concerns. Towards a solution to this issue, this study examines the frameworks, standards and certification schemes (FSCs) that inform governments’ approach to adopting the public cloud. The study focuses on the extent to which they are suitable for the identification of issues

• Publication Date: 13-Mar-2016
• DOI: 10.15224/978-1-63248-087-3-57
• Views: 0
• Downloads: 0