Power and Energy

The dataset includes the regulatory, utility and DGENCO data for distribution planning for a utility under regulated monopoly. The regulatory data includes benchmark EENSC values, and elasticity values. The utility data involves bus, and prospective branch data. The load data corresponds to increase in load with respect to planning stages. The branch data corresponds to all candidate branch locations of all types. The DGENCO data corresponds the candidate DG locations with maximum size of each Distributed Generation.

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The dataset includes active power measurements for a residential prosumer located in Mogosoaia, Romania, collected at 1 frame/second reporting rate over 12 consecutive months.

Always-on appliances include the refrigerator and the wireless router. Several other appliances are installed in the residential unit: washing machine, lighting fixtures, electrical iron, vacuum cleaner, various ICT charging devices, and air conditioning (seldom used).

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363 Views

A dataset characterizing the parameters of a stepped piezoelectric cantilever beam using various geometric specifications is introduced. The dataset also shows the electric potential generated at each layer when exposed to a specific excitation frequency. The primary application of the cantilever is in ambient vibration energy harvesting, where the piezoelectric cantilever beam plays a crucial role in converting mechanical vibrations into electrical energy.

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258 Views

This letter presents a new formulation for the loss-concerned dc power flow that is suitable for optimization-based power system operation and planning. The proposed approach equivalently recasts a previously reported model that explicitly represents the differences in the power flows at the receiving

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270 Views

Where one can find videos about the innovative algorithms and experimental procedures of this paper. The algorithm files contain both the MATLAB version and the Code Composer Studio (CCS) version. In the video, here is the permanent magnet synchronous motor control platform used in the study.

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112 Views

Ionic wind has shown promising applications in many fields, but it still encounters the challenges of low wind velocity and high discharge voltage. Here we propose a method of enhancing the velocity of ionic wind at given discharge voltages by Joule-heating the discharge electrode in a wire-grid corona discharge scheme.

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Dataset from UCI contains the  electricity consumption (in kWh) of 320 customers every 15 minutes from 2011 to 2014.     For  some customers, their electricity consumption data was recorded starting from a different time,  and the data before the first record was marked as 0.     As training model requires a starting point for the time series, and different customers  have different starting times, some features remain 0 before a certain time point.     Using all  the data for training would inevitably have a negative impact.     Therefore, the data  from 2011 is removed  and set the starti

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This dataset contains simulation results for the research article "Reserve Provision from Electric Vehicles: Aggregate Boundaries and Stochastic Model Predictive Control". Each CSV file corresponds to an experimental setup with a certain number of EVs included in the fleet and the risk-aversion determined by the risk-aversion factor Ω.

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The evolution of the power grid is progressively shifting towards a much more dynamic and complex system. Generation sources that are more decentralized and reliant on inverter-based technologies, plus increasing demand for electrification of new types of loads are introducing more challenges to grid stability. Grid operators must adapt, requiring more extensive, granular, and timely data to enable analytics for improved efficiency and development of proactive mitigation strategies.

 

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225 Views

This dataset was used for the capacity planing of ahybrid solar PV-small hydro power plant located in Buseruka, Hoima District in Uganda. The data consitss of four files namely:

 

1. 20240601_GenerationStatisticsQ1_2024-Kabalega-Hydromax: Represents power generation statistics from ERA for Kabalega/HYdromax HPP.

2. Hydrology from Buseruka HPP - 2015-2022: Represents the hydrology or river flow data in cumecs for the period 2015 to 2022 as provided by the plant operators.

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