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Short-Term Load Forecasting by Artificial Intelligent Technologies

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ISBN: 9783038975823 9783038975830 Year: Pages: 444 DOI: 10.3390/books978-3-03897-583-0 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Computer Science
Added to DOAB on : 2019-01-29 10:55:39
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In last few decades, short-term load forecasting (STLF) has been one of the most important research issues for achieving higher efficiency and reliability in power system operation, to facilitate the minimization of its operation cost by providing accurate input to day-ahead scheduling, contingency analysis, load flow analysis, planning, and maintenance of power systems. There are lots of forecasting models proposed for STLF, including traditional statistical models (such as ARIMA, SARIMA, ARMAX, multi-variate regression, Kalman filter, exponential smoothing, and so on) and artificial-intelligence-based models (such as artificial neural networks (ANNs), knowledge-based expert systems, fuzzy theory and fuzzy inference systems, evolutionary computation models, support vector regression, and so on). Recently, due to the great development of evolutionary algorithms (EA) and novel computing concepts (e.g., quantum computing concepts, chaotic mapping functions, and cloud mapping process, and so on), many advanced hybrids with those artificial-intelligence-based models are also proposed to achieve satisfactory forecasting accuracy levels. In addition, combining some superior mechanisms with an existing model could empower that model to solve problems it could not deal with before; for example, the seasonal mechanism from the ARIMA model is a good component to be combined with any forecasting models to help them to deal with seasonal problems.

Control of Multiphase Machines and Drives

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ISBN: 9783039281367 9783039281374 Year: Pages: 146 DOI: 10.3390/books978-3-03928-137-4 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2020-01-30 16:39:46
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With the growing interest in electrical machines in recent times, the multiphase machine field has developed into a fascinating research area. Their intrinsic features (power splitting, better fault tolerance, or lower torque ripple) make them an appealing competitor to conventional three-phase machines. Multiphase electric drives have been recently used in applications where fault tolerance and continuous operation of the drive are required. However, the difficulties in extending the three-phase conventional current regulation and control structure to multiphase systems still limit their broad applicability in industry solutions. The main objective of this book is to illustrate new advances, developments, and applications in the field of multiphase machines and drives, while exposing these advances, developments, and applications to the scientific community and industry.

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