Power and Energy
superjunction mosfets turn-off switching waveforms
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This dataset is used to design patent. The system is basic , as can be seen from figure.
As the boost converter, BMS is on existing designs.It is very simple for any graduate,degree holder or school students, so no paper is written for it.
There is related dataset-Data: Fifteen 255W Panels Connected Li-Ion
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Dynamic data for frequency control with continuous UFLS and LCFB1
This dataset is supplementary material to the draft 'Continuous Under-Frequency Load Shedding Scheme for Power System Adaptive Frequency Control' submitted to IEEE Transactions on Power Systems. Authors of the draft are: Changgang Li, Member, IEEE, Yue Wu, Yanli Sun, Hengxu Zhang, Member, IEEE, Yutian Liu, Senior Member, IEEE, Yilu Liu, Fellow, IEEE, and Vladimir Terzija, Fellow, IEEE
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Test systems are important tools and benchmark for power system research. Currently, there is a lack of standard test systems for modern transmission expansion planning (TEP) research, especially under high variable renewable energy (VRE) penetrations. This paper describes a 38-bus test system named the HRP-38 system dedicated to TEP. “HRP” stands for high renewable penetration. The objective of establishing such a system is to provide a consistent platform for different TEP methods to be tested and compared.
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This dataset contains data used for case studies in paper titled “Towards Flexible Risk-Limiting Operation of Multi-Terminal HVDC Grids with Vast Wind Generation” submitted to IEEE Transactions on Sustainable Energy.
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These two data sets are the generation and load profiles for a modified IEEE 123-node case and Nanji case.
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This dataset contains daily maximum load data with the average demand, customer count and PV capacity at two substations Arkana and Muchea, Western Australia used in the accepted IEEE Transactions on Power Systemspaper titled “The Use of Extreme Value Theory for Forecasting Long-Term Substation Maximum Electricity Demand” by Li and Jones (2019). The dataset spans from 01/01/2008 to 30/06/2022, part history (01/01/2008 to 16/09/2018) and part forecast (17/09/2018 to 30/06/2022). The dataset is beneficial to various research such as long-term load forecast.
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This dataset contains daily maximum load data with the average demand, customer count and PV capacity at two substations Arkana and Muchea, Western Australia used in the accepted IEEE Transactions on Power Systemspaper titled “The Use of Extreme Value Theory for Forecasting Long-Term Substation Maximum Electricity Demand” by Li and Jones (2019). The dataset spans from 01/01/2008 to 30/06/2022, part history (01/01/2008 to 16/09/2018) and part forecast (17/09/2018 to 30/06/2022). The dataset is beneficial to various research such as long-term load forecast.
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