This dataset contains the following simulated information of the IEEE 14 bus system: The 24-hour load profile of all the nodes of the IEE 14 bus circuit, voltages and currents measured by the PMUs placed at optimal locations which minimizes the variance on the estimated voltage states, voltages and currents measured by the PMUs placed at sub-optimal locations.

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The dataset contains an example of energy consumption, Functioning hours and Production KPI of different stages of the experimental open pit mine, mainly the destoning, the screening, and the train loading station. The Code is an example of the prediction algorithm, and the API can be used to apply the same algorithm used in this article.

In the proposed Dataset the energy consumption data for each station are collected from power meters and stored into a database that contains functioning hours and production.

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The database contains information about three test systems, including the network connected to Bus 5 of the Roy Billinton Test System and two netwroks with 93 and 135 load nodes.

 

 

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Power system state estimation (PSSE) plays a vital role in stable operation of modern smart grids, while it is vulnerable to cyber attacks. False data injection attacks (FDIA), one of the most common cyber attacks, can tamper with measurement data and bypass the bad data detection (BDD) mechanism, leading to incorrect PSSE results.

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The AMPds dataset has been release to help load disaggregation/NILM and eco-feedback researcher test their algorithms, models, systems, and prototypes. This dataset is intended to be multi-year capture of the consumption of my house. This dataset contains electricity, water, and natural gas measurements at one minute intervals. This dataset contains a total of 1,051,200 readings for 2 years of monitoring (from April/2012 to March/2014) per meter. There are a total of 21 power meters, 2 water meters (with additional appliance usage annotations), and 2 natural gas meters.

Instructions: 

You must cite the Scientific Data journal paper: Makonin, S. et al. Electricity, water, and natural gas consumption of a residential house in Canada from 2012 to 2014. Sci. Data 3:160037 doi: 10.1038/sdata.2016.37 (2016).

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This a supplementary material for the IEEE Conference Paper - A Dynamic Model of Realistic Nigerian 330 kV Transmission Network: A Catalyst to Realistic Grid Studies and Expansion Strategy.

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Distribution grids are experiencing a massive penetration of fluctuating distributed energy resources (DERs). As a result, the real-time efficient and secure operation of distribution grids becomes a paramount problem. While installing smart sensors and enhancing communication infrastructure improves grid observability, it is computationally impossible for the distribution system operator (DSO) to optimize setpoints of millions of DER units.

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The dataset is supplementary material for the research article 'Techno-economic assessment of grid-level battery energy storage supporting distributed photovoltaic power' published in IEEE Access in October 2021. The dataset corresponds to the annual timeseries at 1-minute resolution (525,600 steps) of the per-unit profiles used for the electric load and the per-unit power output of 8 PV systems.

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Clean energy resources, like wind, have a stochastic nature, which involves uncertainties in the power system. Introducing energy storage systems (ESS) to the network can compensate for the uncertainty in wind plant output and allow the plant to participate in ancillary service markets. Advance in compressed air energy storage system (CAES) technologies and their fast response make them suitable for ancillary services.

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These measurements were taken at the point of common coupling using the power quality analyzer PQ-Box 200, where about 30 EV chargers are installed and exploited by the utility. For this reason, this data set only considers the charging behavior of the vehicles employed by the enterprise, namely the Renault Kangoo ZE and Renault Zoe. The period under consideration starts on 5.11.2018 and ends on 07.01.2020. Because of the large amount of data, values with a time interval of 10mins are extracted and used in this data set.

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