Electric Utility

We introduce a dataset concerning electric-power consumption-related features registed in seven main municipalities of Nariño, Colombia, from 2010 to 2016. The dataset consists of 4423 socio-demographic characteristics, and 6 power-consumption-referred measured values. Data were fully collected by the company Centrales Eléctricas de Nariño (CEDNEAR) according to the client consumption records.
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This work focuses on using the full potential of PV inverters in order to improve the efficiency of low voltage networks. More specifically, the independent per-phase control capability of PV three-phase four-wire inverters, which are able to inject different active and reactive powers in each phase, in order to reduce the system phase unbalance is considered. This new operational procedure is analyzed by raising an optimization problem which uses a very accurate modelling of European low voltage networks.
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This folder contains two csv files and one .py file. One csv file contains NIST ground PV plant data imported from https://pvdata.nist.gov/. This csv file has 902 days raw data consisting PV plant POA irradiance, ambient temperature, Inverter DC current, DC voltage, AC current and AC voltage. Second csv file contains user created data. The Python file imports two csv files. The Python program executes four proposed corrupt data detection methods to detect corrupt data in NIST ground PV plant data.
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This dataset is in support of my 3 research papers - 'Comparative SoC Analysis using Non-Linear Kalman Estimation in 8RC ECM of 72Ah LIB - Part I', ' Comparative SoC Analysis using Non-Linear Kalman Estimation in 8RC ECM of 72Ah LIB - Part II' , and 'Comparative SoC Analysis using Non-Linear Kalman Estimation in 8RC ECM of 72Ah LIB - Part III'.
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MILP instances (in LP format) of the paper
Alberto Borghetti
A Mixed-Integer Linear Programming Approach for the Computation of the Minimum-Losses Radial Configuration of Electrical Distribution Networks
IEEE Transactions on Power Systems (Issue: 3, Aug. 2012, pp. 1264-1273)
https://doi.org/10.1109/TPWRS.2012.2184306
previously available at http://www.lisep.ing.unibo.it/optree.zip
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This dataset is in support of my research paper 'Analysis of Power Generation And Turbine Characteristics of 2.2 kW Residential Wind Generators'.
Related Claim : Novel ß Wind Turbine Urban Residential Controller and Novel ß Wind Vibration Octa Axis Harvesting System in Patent 'Novel ß 10-Axis Grid Compatible Multi-Controller'
Preprint :
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This dataset is in support of my 2 research papers - 'Short Circuit Analysis of 72Ah Li-Ion BMC - Part I' and 'Short Circuit Analysis of 72Ah Li-Ion BMC - Part II'.
Faults and datasets can be copied to submit in fire cause investigation reports or thesis.
This dataset is a collection of data of battery and BMC faults.
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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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