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27
datasets available to search
ShareScore release 0.9.0
Dataset results
27 results for “Energy markets”
Dataset for Energy Resource Management Considering Participation in the Wholesale Day-Ahead Market
<p>This release is associated with a paper entitled "A Novel Framework for Day-Ahead Market Clearing Process Featuring a Hybrid Pricing Mechanism".</p> <p>In this document, we provide the mathematical manipulation employed to linearize an MPEC problem that models the market-clearing process considering the participation of generation companies and distribution operators in the day-ahead market. Additionally, we provide a numerical example of the pricing mechanism designed for solving the optimization problem. </p> <p>Finally, we include information regarding the transmission and distribution power systems adopted to present the results shown in the paper. These systems are modified versions of the IEEE <a href="https://icseg.iti.illinois.edu/ieee-14-bus-system/">14-bus</a> and the IEEE <a href="https://cmte.ieee.org/pes-testfeeders/resources/">34-bus</a>, respectively. Three renewable non-dispatchable generators were added to the original 14-bus system, while 5 dispatchable generators and 3 non-dispatchable generators were added to the distribution system. 13 load shapes were considered as well as 5 scenarios for each uncertain variable (wind velocity, solar irradiance, distribution load oscillation, and transmission load oscillation). The data regarding the costs and physical parameters of each of the power system's elements are provided in this document.</p>
Dataset for Energy Resource Management Considering Participation in the Wholesale Day-Ahead Market
<p>This release is associated with a paper entitled "A Novel Bilevel Programming Formulation for Optimizing the Interaction of Distribution System Operators and GENCOs in Day-Ahead Markets".</p> <p>In this document, we provide the mathematical manipulation employed to linearize an MPEC problem that models the market-clearing process considering the participation of generation companies and distribution operators in the day-ahead market. Additionally, we provide a numerical example of the pricing mechanism designed for solving the optimization problem. </p> <p>Finally, we include information regarding the transmission and distribution power systems adopted to present the results shown in the paper. These systems are modified versions of the IEEE <a href="https://icseg.iti.illinois.edu/ieee-14-bus-system/">14-bus</a> and the IEEE <a href="https://cmte.ieee.org/pes-testfeeders/resources/">34-bus</a>, respectively. Three renewable non-dispatchable generators were added to the original 14-bus system, while 5 dispatchable generators and 3 non-dispatchable generators were added to the distribution system. 13 load shapes were considered as well as 5 scenarios for each uncertain variable (wind velocity, solar irradiance, distribution load oscillation, and transmission load oscillation). The data regarding the costs and physical parameters of each of the power system's elements are provided in this document.</p>
Dataset for Energy Resource Management Considering Participation in the Wholesale Day-Ahead Market
<p>This release is associated with a paper entitled "A Novel Framework for the Day-Ahead Market Clearing Process Featuring the Participation of Distribution System Operators and a Hybrid Pricing Mechanism".</p> <p>In this document, we provide the mathematical manipulation employed to linearize an MPEC problem that models the market-clearing process considering the participation of generation companies and distribution operators in the day-ahead market. Additionally, we provide a numerical example of the pricing mechanism designed for solving the optimization problem. </p> <p>Finally, we include information regarding the transmission and distribution power systems adopted to present the results shown in the paper. These systems are modified versions of the IEEE <a href="https://icseg.iti.illinois.edu/ieee-14-bus-system/">14-bus</a> and the IEEE <a href="https://cmte.ieee.org/pes-testfeeders/resources/">34-bus</a>, respectively. Three renewable non-dispatchable generators were added to the original 14-bus system, while 5 dispatchable generators and 3 non-dispatchable generators were added to the distribution system. 13 load shapes were considered as well as 5 scenarios for each uncertain variable (wind velocity, solar irradiance, distribution load oscillation, and transmission load oscillation). The data regarding the costs and physical parameters of each of the power system's elements are provided in this document.</p>
Dataset for Energy Resource Management Considering Participation in the Wholesale Day-Ahead Market
<p>This release is associated with a paper entitled "A Novel Framework for the Day-Ahead Market Clearing Process Featuring the Participation of Distribution System Operators and a Hybrid Pricing Mechanism".</p> <p>In this document, we provide the mathematical manipulation employed to linearize an MPEC problem that models the market-clearing process considering the participation of generation companies and distribution operators in the day-ahead market. Additionally, we provide a numerical example of the pricing mechanism designed for solving the optimization problem. </p> <p>Finally, we include information regarding the transmission and distribution power systems adopted to present the results shown in the paper. These systems are modified versions of the IEEE <a href="https://icseg.iti.illinois.edu/ieee-14-bus-system/">14-bus</a> and the IEEE <a href="https://cmte.ieee.org/pes-testfeeders/resources/">34-bus</a>, respectively. Three renewable non-dispatchable generators were added to the original 14-bus system, while 5 dispatchable generators and 3 non-dispatchable generators were added to the distribution system. 13 load shapes were considered as well as 5 scenarios for each uncertain variable (wind velocity, solar irradiance, distribution load oscillation, and transmission load oscillation). The data regarding the costs and physical parameters of each of the power system's elements are provided in this document.</p>
Data for Assessing the renewable energy policy paradox: a scenario analysis for the Italian electricity market
<p>This page contains the datasets and codes used to generate the figures for the article Assessing the renewable energy policy paradox: a scenario analysis for the Italian electricity market.</p> <p>Below you will find two datasets (.dta) and four codes (.do) files. Please note that the .do files contain the original paths to where the datasets were saved, you should change them to where they are saved in your computer. </p> <ol> <li>The file <em>clustering_prer_ok.do</em> uses dataset <em>yearlyvars_raw.dta</em> to generate three additional datasets <em>clusters.dta</em>, <em>yearly_scenarios.dta</em> and <em>xwalk.dta</em> <ul> <li><em>clusters.dta</em> is used in <em>Figs_2-5-6_ok.do</em></li> <li><em>yearly_scenarios.dta</em> is used in <em>Figs_3_ok.do</em></li> </ul> </li> <li>Dataset <em>hprice_raw.dta</em> is used together with the generated <em>xwalk.dta</em> in <em>Fig_4_ok.do</em>.</li> </ol>
14-bus test system for peer-to-peer energy and reserve markets
<p>With the development of distributed energy resources the way to produce and consume electricity has changed dramatically over the past few years. To cope with these changes there is a need for a new paradigm in electricity markets, namely a consumer-centric market framework. Within this framework, peer-to-peer markets have gained substantial interest due to their decentralized nature and their structural flexibility. Usually solely applied on energy, these peer-to-peer energy markets are yet likely to involve agents with stochastic behaviors such as renewable generators. This test case proposes a modified version of the IEEE 14-bus test system which will allow to test these novel approaches peer-to-peer markets accounting both for energy and reserves. The data set is given in the form of a MATLAB .mat file following the Matpower file format.</p>
Supplementary material for the article entitled "Socioeconomic Analysis of the Proposed Opening of the Brazilian energy Market Through the Combination of Forecast Method with the Optimized Tariff Model"
<p>This supplementary material includes the input data used for the simulations conducted in the article.</p>
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
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