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5 results for “Load demand”
Railbelt 2050 Load, Electrification, and Behind-the-Meter Solar Hourly Load Demand for Aggressive and Moderate Electrification Forecasts
<p>The data in this file is comprised of hourly load demand data for the year of 2050 for Alaska's Railbelt transmission system from the aggressive and moderate load, electrification adoption, and behind-the-meter solar forcasts generated by the ACEP Railbelt Decarbonization Study. </p>
Ndoro village load demand dataset
<p>Dataset of Ndoro village hourly-resolution load demand data computed from aggregated data collected during on-field campagns in 2019-2020. The village of Ndoro is located along the national street, in the Administrative Post of Ndoro, District of Caia, Sofala Province, Mozambique, at coordinates 34°56'35.6''E 18°6'59.5''S.</p> <p>The dataset, built in excel, is structured as follows:</p> <ul> <li>The "Baseload demand" sheet reports the parameters of the appliances of the 69 users under the 14 classes. The parameters are defined according to the <a href="https://github.com/RAMP-project/RAMP/releases/tag/v0.3.1 ">v0.3.1</a> of <a href="https://rampdemand.org/">RAMP</a>, an open-source software for the stochastic simulation of a user-driven energy demand time series, with existing applications in off-grid rural electrification.</li> <li>The "Baseload results" sheet reports the RAMP simulation results for the first year of the modelling period, differentiating between residential demand, productive activities and public services.</li> <li>Four scenarios of demand evolution and associated results are considered in the following sheets, accounting for evolutions estimated from the on-field data collected.The scenarios, showing a progressive upscaling of load demand along the years, introduce: <ul> <li>New appliances in Scenario 1</li> <li>New appliances and new classes of users in Scenario 2</li> <li>New appliances, new classes of users and new appliances associated to the new classes in Scenario 3</li> <li>New energy intensive appliances, new classes of users and new appliances associated to the new classes in Scenario 4</li> </ul> </li> </ul>
Hourly wind speed, solar radiation and load demand data
<p>Hourly data for wind velocity, solar radiation and load demand as time series of 10 years length, used within the simulation of a hybrid renewable energy system in the island of Sifnos, Greece. </p>
Photovoltaic Generation and Load Demand Datasets with 30 seconds resolution from an Actual Prosumer in Cyprus
<p>Real-life datasets regarding the photovoltaic generation (active and reactive power) and the load demand (active and reactive power) from an actual residential prosumer (consumer with a rooftop photovoltaic system) in Cyprus. </p> <p>The residential building, with two occupants and a 200 m<sup>2</sup> approximately indoor area, is located in Nicosia, Cyprus. The building is equipped with a rooftop photovoltaic system consist of a 5 kVA Solar Edge Inverter (SE5K), integrating 18 x REC310PE72 PV panels. The PV panels are installed with 3<sup>o</sup> inclination angle (almost flat) an 190<sup>o</sup> azimuth angle (almost south direction). The building is using split-unit air-conditioners to cover the cooling needs during the summer and a heat-pump underfloor heating system to cover the heating needs during winter. </p> <p>The datasets regarding the photovoltaic generation and the load consumption is captured through the WiseWire Energy Box (local hub) and WiseWire Cloud Platform (http://wisewiresolutions.com/) with a resolution of 30 seconds. It is noted that the photovoltaic generation is taken through the inverter's Modbus interface while the load consumption is obtained through the Modbus interface of Janitza UMG 604 fast reporting smart meter.</p> <p>A total of 24 daily profiles are provided (1 daily profile each month from October 2021 until September 2023, while the exact date is indicated by the ".csv" file name considering the following format yyyy-mm-dd). </p> <p>It should be noted that these profiles has been used for the integration of the Cyprus power system digital twin. In particular, an accurarate and high resolution simulation model of the Cyprus power system has been developed and executed in a real time simulator, where field data from various sources (e.g., PMUs, smart meters, SCADA) are fed in order to replicate the operating conditions of the actual system. Therefore, the datasets provided here, are examples of time-series profiles that have been used to replicate the photovoltaic generation and load consumption of a residential building emulated within the digital twin. More information about the digital twin can be found in Deliverable D8.3 of the OneNet project (<a href="https://onenet-project.eu/wp-content/uploads/2023/12/OneNet_D8.3_V1.0.pdf">OneNet_D8.3.pdf </a>). Moreover, these datasets have been used to develop realistic pre-piloting setups for the Smart5Grid project to preliminary examine pilot use cases in a digital twin based hardware in the loop environment in Deliverable D3.4 (<a href="https://smart5grid.eu/wp-content/uploads/2023/03/Smart5Grid_WP3__D3.4_PU_Smart5Grid-platform-integration-and-HIL-testing-activities_V1.0.pdf">Smart5Grid_D3.4.pdf</a>) of the corresponding project. </p> <p> </p> <p> </p>
SPARCS_WP4_Leipzig_Virtual_Modelled Residential Load for Community Demand Response
<p>modelled Residential Load for the 1000 households participating in the Community Demand Response. 900 are typical private 2-person households (RL1),100 are typical private 2-person households with heat pumps (RL2)</p>
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