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The technology of Internet of Things (IoT) can be integrated with systems of electrical machines, for electric drives and wind and solar generation systems, and advance controlling and monitoring. This work presented recent research and progress of electrical drives with IoT technology, regarding design, operation, and trial of the control system for induction motors (ΙΜ). Also, the developed software code and hardware units for speed control were detailed and the results obtained from tests of performance of the ΙΜ integrated with IoT were described. With the IoT integration set-up, the operator can control the frequency values, obtain real-time feedback of the process, and monitor the system during varying loads in steady state. The operation of the ΙΜ system driven by inverter and its monitoring over IoT was proven to have high-accuracy speed control and increased efficiency at supersynchronous speeds. Thus, IoT establishes potentials to become a multipurpose tool in the industrial control of electric drives. This paper established one case study of an IoT set-up and control technique for IM, which is suitable for energy engineering experts in the field of IoT control of industrial equipment. [ABSTRACT FROM AUTHOR]

The available literature about Economic Dispatch ED problems is rich. In most of the cases the readers need specialized multidisciplinary knowledge of control systems, advanced optimization techniques, computers software and energy systems. Integration of ED problems in syllabus of economic management of energy systems requires knowledge of control engineering, and economics. There is a gap of knowledge between classical control theory most of graduates possess, and necessary advanced optimal control techniques for working in the field of ED problems. This article presents an educational generalized method EGM_ED for modeling, and solving the optimization of ED problems of thermal energy systems, using matrix mathematics, and matlab software. The solution is deducted mathematically, computed with matrices, and do not uses solvers from toolboxes. Can be applied in many different situations of energy systems with big numbers of generators. EGM_ED method is easier accessed by students, early carrier engineers, and practitioners. Using our matrix-based modelling for solving ED problems will offer access to students, and to other interested people to better learn, specialize and take critical managerial decisions in related energy industry jobs. [ABSTRACT FROM AUTHOR]