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8 results for “Flexibility Markets”
Flexibility market results
<p>The SLO_ACTIVATION_DATA dataset includes data about requested activation energy, delivered activation energy and price of delivered energy (monthly aggregates). The data set in CIM XML contains flexibility market results of Slovenian pilot in OneNet project. It is intended to enable o<span><span>bserving effectiveness </span><span>of flexibility services activation and ratio between requested and activated flexibility.</span></span><span> </span></p> <p>More about the Slovenian demo in the One Net deliverable 10.4 (<a href="https://www.onenet-project.eu//wp-content/uploads/2023/10/OneNet_D10.4_V1.0.pdf">OneNet_D10.4_V1.0.pdf (onenet-project.eu)</a>)</p>
Dataset to Study TSO-DSO Coordination Market Models for Flexibility Procurement to Balancing and Congestion Management
<p>The dataset is composed by an interconnected system consisting of the IEEE 14-bus (TN) transmission network connected to three distribution networks: the Matpower systems 18-bus (DN_18), 69-bus (DN_69), and 141-bus (DN_141). All systems topology and some parameters are based on the corresponding cases in Matpower [1]. Base demand is adapted from the case, while base generation profiles are added to all nodes. All distribution systems are balanced, and the transmission system is imbalanced. Thermal limits of the lines are adapted in order to create congestion in the systems. Each distribution system is connected to the transmission system through one line, which has capacity of 1.0. The interconnected system is fully represented in "Network.xlsx", in which:</p> <ul> <li>System: transmission (TN) or distribution (DN_18, DN_69, DN_141);</li> <li>LineID: ID of the lines;</li> <li>BusNumber: number of the nodes within the systems. This parameter is used to define the lines (from/to);</li> <li>BaseDemand and BaseSupply: base active demand and generation of each node;</li> <li>ConnectedDN: distribution system to which the transmission system node is connected to. If blank, the node is not connected to any distribution system. Only for the transmission system;</li> <li>InterfaceCapacity: thermal limit of the interface between the transmission and distribution systems;</li> <li>ThermalLimit: thermal limit of the transmission/distribution systems lines. For distribution systems, a value of 10 indicates that the line has no limit; </li> <li>SFTN: shift factor matrix of the transmission system. Capture the change in the active power flow over a line due to a change in injection or offtake at a node;</li> <li>BaseReactiveDemand and BaseReactiveSupply: base reactive demand and generation at each node. Only for distribution systems;</li> <li>VoltageLB and VoltageUB: lower and upper limits for the magnitude squared of the voltage in each distribution system node. Only for distribution systems;</li> <li>ConnectedTN: identify if the distribution node is connected or not to the transmission system. Only for distribution systems;</li> <li>ResistanceR: resistence of the distribution system lines. Only for distribution systems;</li> <li>ReactanceX: reactance of the distribution system lines. Only for distribution systems.</li> </ul> <p>Flexibility bids are randomly generated in the different nodes. For downward flexibility bids, the prices are drawn from the uniform distribution in the range 10 to 15, and for upward flexibility bids, they are drawn from the range 45 to 50. The bids maximum quantities are generated according to the base demand or supply of the node from which they are connected. A minimum value for the quantity is imposed as 0.01. The generated orderbook is presented in "OrderbookTN" (transmission system) and "OrderbookDN" (distribution systems):</p> <ul> <li>OrderID: the ID of the order, to make each order unique;</li> <li>System: the system (TN, DN_18, DN_69, DN_141) from which the order is offered;</li> <li>BusNumber: the node from which the order is offered;</li> <li>FlexibilitySense: UPWARD for increase in generation or decrease in demand; DOWNWARD for increase in demand or decrease in generation;</li> <li>Price: the submitted order price;</li> <li>Quantity: the maximum quantities of the order.</li> </ul> <p>Source of the systems' topology:</p> <p>[1] R. D. Zimmerman, C. E. Murillo-Sanchez, and R. J. Thomas, “Mat-power: Steady-state operations, planning, and analysis tools for power systems research and education,” IEEE Transactions on power systems, vol. 26, no. 1, pp. 12–19, 2010.</p> <p>Please notice that this dataset does not replace the information provided by Matpower related to the aforementioned systems. It rather uses those systems topology and some of their parameters to build a case study to investigate TSO-DSO coordination market models for the procurement of flexibility. For the full description of these systems, please visit: <a href="https://matpower.org/">MATPOWER – Free, open-source tools for electric power system simulation and optimization</a>.</p>
Dataset to Study Grid-Secure Use of Distributed Flexibility in Sequential DSO-TSO Markets
<p>We publish the dataset used to study Grid-Secure Use of Distributed Flexibility in Sequential DSO-TSO Markets (as part of chapter 7 of deliverable D3.3 of the OneNet project).</p> <p>The dataset is composed by an interconnected system consisting of the IEEE 14-bus (TN) transmission network connected to two distribution networks: the Matpower systems 69-bus (DN_69), and 141-bus (DN_141). All systems topology and some parameters are based on the corresponding cases in Matpower [1]. Injections and loads of the nodes are adapted to create an anticipated imbalance in the interconnected system, resolved by flexibility. In addition, the lines’ upper limits are adjusted to create anticipated congestion in the networks. The interconnected system is fully represented in "Network_case_A_B_C.xlsx" (upward balancing need) and "Network_case_D.xlsx" (downward balancing need).<br>Upward and downward flexibility bids are randomly generated and allocated to the nodes. </p> <p>7 bids lists are available in this dataset. </p> <p>Source of the systems' topology:</p> <p>[1] R. D. Zimmerman, C. E. Murillo-Sanchez, and R. J. Thomas, “Mat-power: Steady-state operations, planning, and analysis tools for power systems research and education,” IEEE Transactions on power systems, vol. 26, no. 1, pp. 12–19, 2010.</p> <p>Please notice that this dataset does not replace the information provided by Matpower related to the aforementioned systems. It rather uses those systems topology and some of their parameters to build a case study to investigate Grid-Secure Use of Distributed Flexibility in Sequential DSO-TSO Markets. For the full description of these systems, please visit: <a href="https://matpower.org/">MATPOWER – Free, open-source tools for electric power system simulation and optimization</a>.</p>
Taxonomy of barriers that hinders Local Flexibility Market proliferation
<p>This dataset contains the results of the state of the art survey to retrieve the barriers that that hinders Local Flexibility Market proliferation. Scientific literature, interviews with different stakeholders, technical reports from the main energy agencies and the European and national legislation have been consulted to build the taxonomy. Three files are provided:</p> <ul> <li>a spreadsheet with the list of barriers and the document were it is found and</li> <li>a diagram with the end taxonomy of barriers</li> <li>a document with an explanation of the barriers included in each category of the taxonomy</li> </ul>
Prioritization of barriers that hinders Local Flexibility Market proliferation
<p>This dataset contains the prioritization provided by a panel of 15 experts to a set of 28 barriers categories for 8 different roles of the future energy system. A Delphi method was followed and the scores provided in the three rounds carried out are included. The dataset also contains the scripts used to assess the results and the output of this assessment. </p> <p>A list of the information contained in this file is:</p> <ul> <li> <p><strong>data folder</strong>: this folders includes the scores given by the 15 experts in the 3 rounds. Every round is in an individual folder. There is a file per expert that has the scores between -5 (not relevant at all) to 5 (completely relevant) per barrier (rows) and actor (columns). There is also a file with the description of the experts in terms of their position in the company, the type of company and the country.</p> </li> <li> <p><strong>fig folder</strong>: this folder includes the figures created to assess the information provided by the experts. For each round, the following figures are created (in each respective folder):</p> <ul> <li> <p>Boxplot with the distribution of scores per barriers and roles. </p> </li> <li> <p>Heatmap with the mean scores per barriers and roles.</p> </li> <li> <p>Boxplots with the comparison of the different distributions provided by the experts of each group (depending on the keywords) per barrier and role.</p> </li> <li> <p>Heatmap with the mean score per barrier weighted depeding on the importance of the role in each use case and the final prioritization.</p> </li> </ul> </li> </ul> <p>Finally, bar plots with the mean scores differences between rounds and boxplot with comparisons of the scores distributions are also provided.</p> <ul> <li> <p><strong>stat folder</strong>: this folder includes the files with the results of the different statistical assessment carried out. For each round, the following figures are created (in each respective folder):</p> <ul> <li> <p>The statistics used to assess the scores (Intraclass correlation coefficient, Inter-rater agreement, Inter-rater agreement p-value, Homogeneity of Variances, Average interquartile range, Standard Deviation of interquartile ranges, Friedman test p-value Average power post hoc) per barrier and per role.</p> </li> <li> <p>The results of the post hoc of the Friedman Test per berries and per roles.</p> </li> <li> <p>The average score per barrier and per role.</p> </li> <li> <p>The mean value of the scores provided by the experts grouped by the keywords per barrier and role. P-value of the comparison of these two values.</p> </li> <li> <p>The end prioritization of the barrier for the use case (averaging the scores or fuzzy merging of the critical sets)</p> </li> </ul> </li> </ul> <p>Finally, the differences between the mean and standard deviations of the scores between two consecutive rounds are provided.</p>
Intelligent Energy Systems Ontology: Local flexibility market and power system co-simulation demonstration
<p>The Intelligent Energy Systems Ontology (IESO) provides semantic interoperability within a society of multi-agent systems (MAS) developed in the scope of power and energy systems (PES). It leverages the knowledge from existing and publicly available semantic models developed for specific PES subdomains to accomplish a shared vocabulary among the agents of the MAS community, overcoming heterogeneity among the reused ontologies. IESO provides agents with semantic reasoning, constraints validation, and data uniformization. The use of IESO is demonstrated through the simulation of the management of a rural distribution network, considering the validation of the grid’s technical constraints. This dataset publishes files demonstrating: i) a snapshot of the initial semantic knowledge base (KB); ii) queries to the KB to get services inputs; iii) conversions between syntactic and semantic models; <br> iv) constraints validations; v) automatic conversion of units of measure.</p>
Dataset to Study Flexibility Service Providers' Gaming Potential and its Impact on TSO-DSO Coordinated Markets
<p>We publish the dataset and nomenclature table used to study the Flexibility Service Providers’ Gaming Potential and its Impact on TSO-DSO Coordinated Markets (paper published in the 2023 SEST conference).</p> <p>The dataset is composed by an interconnected system consisting of the IEEE 14-bus (TN) transmission network connected to two distribution networks: the Matpower systems 69-bus (DN_69), and 141-bus (DN_141). All systems topology and some parameters are based on the corresponding cases in Matpower [1]. Injections and loads of the nodes are adapted to create an anticipated negative imbalance (total load surpassing total generation) in the interconnected system, resolved by upward flexibility. In addition, the lines’ upper limits are adjusted to create anticipated congestion in the networks. The interconnected system is fully represented in "Network.xlsx".<br>Upward and downward flexibility bids are randomly generated and allocated to the nodes. Their quantities are aligned with the nodes’ base injection/load and their marginal values are in the range [10, 26] euro/MW for downward, and marginal costs in the range [30, 73] euro/MW for upward, totaling 536 bids. </p> <p>4 bids lists are available in this dataset, to allow the strategic behavior analysis with different levels of liquidity:</p> <p>- In the list of bids "case 0", all 536 bids are present.</p> <p>- In the list of bids "case 1", 40% of bids in the transmission list are deleted (distribution bids are the same as in case 0).</p> <p>- In the list of bids "case 2", 98% of the bids in the distribution bids are deleted (transmission bids are the same as in case 0).</p> <p>- In the list of bids "case 3", only bids needed to solve distribution systems congestions are kept (all the others are deleted) (transmission bids are the same as in case 0).</p> <p>Source of the systems' topology:</p> <p>[1] R. D. Zimmerman, C. E. Murillo-Sanchez, and R. J. Thomas, “Mat-power: Steady-state operations, planning, and analysis tools for power systems research and education,” IEEE Transactions on power systems, vol. 26, no. 1, pp. 12–19, 2010.</p> <p>Please notice that this dataset does not replace the information provided by Matpower related to the aforementioned systems. It rather uses those systems topology and some of their parameters to build a case study to investigate TSO-DSO coordination market models for the procurement of flexibility. For the full description of these systems, please visit: <a href="https://matpower.org/">MATPOWER – Free, open-source tools for electric power system simulation and optimization</a>.</p>
Policy Review Data and Outcomes on Local Flexibility Markets Operation
<p>This is a collaborative work with several researcher involved from the PARITY project.</p> <p>We conducted research on the different PARITY offerings, attempting to bring evidence-based recommendations arising from the whole PARITY project process. The conducted survey and workshop helped us to deliver the PARITY policy review data that could enable relevant stakeholders (including the EC and national regulatory authorities) to understand the complications and the actions needed to facilitate a wide, sustainable, fair and future proof uptake of local flexibility markets in Europe</p>
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