Power and Energy

This dataset includes the system data and equivalent Distributed Energy Resource (DER) allocations for three test cases: a 10-bus system, the IEEE 69-bus radial test feeder, and an 873-bus radial test feeder. The IEEE 69-bus system data is based on the work of Baran and Wu ("Optimal capacitor placement on radial distribution systems," IEEE Trans. Power Deliv., vol. 4, no. 1, pp. 725-734, 1989).
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This paper presents a method for modeling and simulating three-phase grid-connected solid-oxide fuel cell systems in the Matlab/Simulink environment. The approach is utilized to analyze the interaction between solid-oxide fuel cells and the electrical power system, focusing on understanding the dynamics of the electrochemical reaction and its impact on the performance of grid-connected fuel cell systems. The results highlight the effectiveness of the proposed method in accurately modeling and operating three-phase grid-connected solid-oxide fuel cell systems.
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MatWPT is an innovative software to support designers during the analysis and development of Wireless Power Transfer (WPT) systems. The software, developed as a Matlab toolbox, receives the key system characteristics as inputs, such as compensation topology, operating frequency and desired output power. Then, using evolutionary optimization, provides potential design options for meeting the performance criteria defined by the designer, in terms of output power and efficiency.
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This dataset webpage contains datasets of exisiting and proposed models:
- centrifugalpump1.zip
- centrifugalpump2.zip
- centrifugalpump3.zip
B Model of Fault And Short-Circuit Analysis of Centrifugal Pump
presented in my last Speaker Presentation in Conference - 2025*.
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Accurately detecting power line defects under diverse weather conditions is crucial for ensuring power grid reliability and safety. Existing power line inspection datasets, while valuable, often lack the diversity needed for training robust machine learning models, particularly for adverse weather scenarios like fog, rain, and nighttime conditions. This paper addresses this limitation by introducing a novel framework for generating synthetic power line images under diverse weather conditions, thereby enhancing the diversity and robustness of power line inspection systems.
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