This paper presents a three-area system tied together with tie lines. During the intervals of power mismatch, the system frequency deviates beyond the nominal value with an oscillatory response and the system may go t...
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This paper presents a three-area system tied together with tie lines. During the intervals of power mismatch, the system frequency deviates beyond the nominal value with an oscillatory response and the system may go to instability mode. The main purpose of the control strategy is optimizing the frequency fluctuations of the three areas and the deviations in the three tie line powers. This is achieved by three controllers as follows: the Tilt-Integral-Derivative (TID) controller, the Fractional Order Proportional-Integral-Derivative (FOPID), and the Proportional-Integral-Derivative (PID) controller. The three controllers are optimized by a new metaheuristic optimization algorithm based on the jellyfish behaviour in the ocean called the Jellyfish Search (JS) Optimizer. To prove the algorithm validity, it is compared with previous optimization techniques that have been applied to the study field such as Grey Wolf Optimization (GWO) algorithm and Genetic algorithm (GA). Furthermore, renewable energy sources are implemented in the system such as wind energy and photovoltaic based on real data. Finally, energy storage devices (ESDs) like superconducting magnetic energy storage (SMES), capacitor energy storage (CES), and battery energy storage (BES) are implemented to improve the system behaviour due to the intermittent behaviour in the renewable sources.
Artificial Intelligence has become ubiquitous in many application sectors nowadays. One field, machine learning, has proved to be promising for industries as it can solve complex problems thanks to various methods and...
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ISBN:
(纸本)9781538667866
Artificial Intelligence has become ubiquitous in many application sectors nowadays. One field, machine learning, has proved to be promising for industries as it can solve complex problems thanks to various methods and algorithms. The present article is an example of machine learning with EBM, a recent additive manufacturing technology. Several algorithms are tested onto the manufacturing of a part in order to check which results can extrapolate at the best the deformation risks vs the quality of the part to build. In this example, a few parameters of support structures are identified and are varied to observe the algorithms validity.
The theory for validating computerized business simulators proposed in this article is based on several premises derived from the research literature. Unique to the theory is the use of a hypothesis test and a methodo...
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The theory for validating computerized business simulators proposed in this article is based on several premises derived from the research literature. Unique to the theory is the use of a hypothesis test and a methodology to describe the behavior of a simulator from the perspective of the student. THE EXECUTIVE GAME is validated to demonstrate the methodology of the theory. THE EXECUTIVE GAME is shown to be unstable, but it is suitable for the development of forecasting skills using exponential smoothing models. It is also shown that the proposed validation methodology reveals much more about the behavior of a simulator than existing validation methods. The theory should help simulation users choose simulators that closely match the learning goals of the courses in which computerized business simulators are used.
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