![]() ![]() However, the need for a quick calculation of ATC poses a challenge. The system operators of the deregulated power system normally can obtain previously calculated ATC values through an open-access same-time information system. ATC is defined as the measure of the additional amount of power that may flow over and above the base case flows without jeopardizing power system security. The TTC of a power system is defined as the maximum amount of power that can be transferred over the interconnected transmission network in a reliable manner while meeting all of a specific set of defined pre- and post-contingency system conditions. Two quantities that require special attention in these computations are the total transfer capability (TTC) and the available transfer capability (ATC). Ever since the advent of the deregulated power system, the computation of transfer capability has been a priority. The first application of cubic splines is in finding the available transfer capability, which is an important parameter in power system operation. Determination of available transfer capability Other complicated methods of tackling the errors caused by noise are available, but the detailed and in-depth analysis of these methods falls beyond the scope of this chapter.Ģ. This ensures that the random noise gets canceled out on an average, and hence the integrity of the data is maintained. One of the possible solutions to the problems caused by noise is to take a large number of measurements. ![]() Especially in electrical measurements, such random noises may be caused by the magnetic field produced by the current, the presence of stray charges, heating caused by the flow of eddy currents, and so on. The measurements we take for analysis in everyday life are wrought with noise that may be caused by the surrounding environment. Cubic spline also has the desirable characteristics of continuous derivatives at data points which make the design of controllers around these regions possible, and its employment has been seconded by the high accuracy obtained. Among the various interpolation techniques available, the cubic spline method has been found to be a popular method. The challenges set the stage for interpolation techniques to play an active role in mitigating the problems prevailing in the current power system studies like load forecasting, power system reactive power planning, transmission network expansion, available transfer capability (ATC) determination and market power/clearing price forecasting. Regardless of the origin of this non-continuity of data, obtaining a continuous response is imperative because of the desired accuracy and the continuity of real-time operation. The unpredictability of these events entails the deployment of probabilistic-based load flow techniques, estimation of unknown variables and load models which includes uncertainties for their analysis.Īll the analysis and research aimed at providing solutions or mitigating the above-mentioned problems require vast amounts of data which is discrete in nature or the analysis techniques involve responses that are discrete in nature. ![]() This is met via several means most recently characterized by the penetration of renewable energy sources. The power system involves the continuous variation in connected loads and increases in power requirement which demands a corresponding increase in the generation. The realization of this necessity has manifested in extensive research in the field of power systems, which has brought to light the complexity of power system. With electricity becoming an inevitable part of all spheres of human life, it is imminent that the increasing demand for electricity be met. ![]()
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