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17 results for “Allocation cost”
Supporting Dataset for the Analysis on TSO-DSOs Cooperation and Stable Cost Allocation for the Joint Procurement of Flexibility (Network and Bid List)
<p>The data provides supporting material for the two case studies in Chapter 5 of CoordiNet D6.2 (the deliverable is available at <a href="https://coordinet-project.eu/publications/deliverables">https://coordinet-project.eu/publications/deliverables</a>) and the two case studies in paper on TSO-DSO cooperation (available at <a href="https://arxiv.org/abs/2111.12830">https://arxiv.org/abs/2111.12830</a>).</p> <p>The dataset is cooresponding to two case studies. In the first case study, the interconnected system consists 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). The interface flow limit is TPmax. In the second case study, the interconnected system consists of the IEEE 14-bus (TN) transmission network connected to three Matpower systems 18-bus distribution networks, who are named as DN_1, DN_2, DN_3. </p> <p>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. The interconnected system is fully represented in "Network_XXX.xlsx", in which:</p> <ul> <li>System: transmission (TN) or distribution (DN_XXX);</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 50 to 55. The bids maximum quantities are generated according to the base demand or supply of the node from which they are connected.. The generated orderbook is presented in "OrderbookTN_XXX.xlsx" (transmission system) and "OrderbookDN_XXX.xlsx" (distribution systems):</p> <ul> <li>OrderID: the ID of the order, to make each order unique;</li> <li>System: the system (TN, DN_XXX) 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>
Data from: Pleiotropy alleviates the fitness costs associated with resource allocation trade-offs in immune signaling networks
<p>Many genes and signaling pathways within plant and animal taxa drive the expression of multiple organismal traits. This form of genetic pleiotropy instigates trade-offs among life-history traits if a mutation in the pleiotropic gene improves the fitness contribution of one trait at the expense of another. Whether or not pleiotropy gives rise to conflict among traits, however, likely depends on the resource costs and timing of trait deployment during organismal development. To investigate factors that could influence the evolutionary maintenance of pleiotropy in gene networks, we developed an agent-based model of co-evolution between parasites and hosts. Hosts comprise signaling networks that must faithfully complete a developmental program while also defending against parasites, and trait signaling networks could be independent or share a pleiotropic component as they evolved to improve host fitness. We found that hosts with independent developmental and immune networks were significantly more fit than hosts with pleiotropic networks when traits were deployed asynchronously during development. When host genotypes directly competed against each other, however, pleiotropic hosts were victorious regardless of trait synchrony because the pleiotropic networks were more robust to parasite manipulation, potentially explaining the abundance of pleiotropy in immune systems despite its contribution to life history trade-offs.</p>
Heat Cost Allocator Dataset for the Reconcycle Project
<p>The dataset consists of images of the Kalo 1.5 heat cost allocator (HCA) and the Qundis HCA. The dataset has been created for the Reconcycle project. Find information at reconcycle.eu. The objects are positioned in different areas of the Reconcycle workcell, designed by JSI.</p> <p>The dataset has the following properties:</p> <ul> <li> <p>1577 images with resolution: 1450x1450 pixels (Basler camera )</p> </li> <li> <p>57 images with resolution: 848 x 480 pixels (Realsense D435 camera)</p> </li> <li> <p>The images have segmentation annotations labelled using the labelme software.</p> </li> <li> <p>The original labelme annotations are present and exported to COCO dataset format.</p> </li> <li> <p>The annotations are in the form of polygon segmentations.</p> </li> <li> <p>The included COCO train/test split is a 90/10 split.</p> </li> </ul> <p>The images have been annotated with the following labels:</p> <ul> <li> <p>hca_front</p> </li> <li> <p>hca_back</p> </li> <li> <p>hca_side1</p> </li> <li> <p>hca_side2</p> </li> <li> <p>battery</p> </li> <li> <p>pcb</p> </li> <li> <p>internals</p> </li> <li> <p>pcb_covered</p> </li> <li> <p>plastic_clip</p> </li> </ul>
Data from: Pleiotropy alleviates the fitness costs associated with resource allocation trade-offs in immune signaling networks
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Cost-effective portfolio allocation across quarantine, surveillance and eradication using info-gap theory
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C allocation to the fungus is not a cost to the plant in ectomycorrhizae (a meta-analysis)
Mycorrhizal benefit to plants is most frequently evaluated through growth differences between mycorrhizal (M) and non‐mycorrhizal (NM) plants. These growth differences are often considered to be due to differences in belowground carbon (C) expenditure, or in cost efficiency, i.e. amount of nutrients acquired per C expended. In order to understand whether growth differences between M and NM plants are dictated by differences in C availability, we searched published reports on for relations between plant growth and belowground C allocation, C use efficiency, or nutrient uptake, in ectomycorrhizal (ECM) versus non‐mycorrhizal plants. This search was done for carrying out a meta-analysis on the published literature. The list of studies used in this meta-analysis, along with relevant information from each study, can be found in this dataset.
Exploring the competitive dynamic enzyme allocation scheme through enzyme cost minimization
<p>The dataset is for the manuscript entitled "Exploring the competitive dynamic enzyme allocation scheme through enzyme cost minimization".</p>
Data from: A sex allocation cost to polyandry in a parasitoid wasp
The costs and benefits of polyandry are central to understanding the near-ubiquity of female multiple mating. Here, we present evidence of a novel cost of polyandry: disrupted sex allocation. In Nasonia vitripennis, a species that is monandrous in the wild but engages in polyandry under laboratory culture conditions, sexual harassment during oviposition results in increased production of sons under conditions that favour female-biased sex ratios. In addition, females more likely to re-mate under harassment produce the least female-biased sex ratios, and these females are unable to mitigate this cost by increasing offspring production. Our results therefore argue that polyandry does not serve to mitigate the costs of harassment (convenience polyandry) in Nasonia. Furthermore, because males benefit from female-biased offspring sex ratios, harassment of ovipositing females also creates a novel cost of that harassment for males.
Data from: Coevolutionary feedbacks between female mating interval and male allocation to competing sperm traits can drive evolution of costly polyandry
Complex coevolutionary feedbacks between female mating interval and male sperm traits have been hypothesized to explain the evolution and persistence of costly polyandry. Such feedbacks could potentially arise because polyandry creates sperm competition and consequent selection on male allocation to sperm traits, while the emerging sperm traits could create female sperm limitation and, hence, impose selection for increased polyandry. However, the hypothesis that costly polyandry could coevolve with male sperm dynamics has not been tested. We built a genetically explicit individual-based model to simulate simultaneous evolution of female mating interval and male allocation to sperm number versus longevity, where these two sperm traits trade off. We show that evolution of competing sperm traits under polyandry can indeed cause female sperm limitation and, hence, promote further evolution and persistence of costly polyandry, particularly when sperm are costly relative to the degree of female sperm limitation. These feedbacks were stronger, and greater polyandry evolved, when postcopulatory competition for paternity followed a loaded rather than fair raffle and when sperm traits had realistically low heritability. We therefore demonstrate that the evolution of allocation to sperm traits driven by sperm competition can prevent males from overcoming female sperm limitation, thereby driving ongoing evolution of costly polyandry.
Data from: Optimal allocation ratios: A square root relationship between the ratios of symbiotic costs and benefits
<p>All organisms struggle to make sense of environmental stimuli in order to maximize their fitness. For animals, single cells and superorganisms responses to stimuli are generally proportional to stimulus ratios – a phenomenon described by Weber's Law. However, Weber's Law has not yet been used to predict how plants respond to stimuli generated from their symbiotic partners. Here, we develop a model for quantitatively predicting the carbon (C) allocation ratios into symbionts that provide nutrients to their plant host. Consistent with Weber's Law, our model demonstrates the optimal ratio of resources allocated into a less- relative to the more-beneficial symbiont scale to the ratio of the growth benefits of the two strains. As C allocation into symbionts increases, the ratio of C allocation into two strains approaches the square root of the ratio of symbiotic growth benefits (e.g., a worse symbiont providing ¼ the benefits gets sqrt(¼) =1/2 the C of a better symbiont). We document a compelling correspondence between our square-root model prediction and a meta-analysis of experimental literature on C allocation. This type of preferential allocation can promote coexistence between more- and less-beneficial symbionts, offering a potential mechanism behind the high diversity of microbial symbionts observed in nature.</p>
Data from: Coevolutionary feedbacks between female mating interval and male allocation to competing sperm traits can drive evolution of costly polyandry
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Data from: A sex allocation cost to polyandry in a parasitoid wasp
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Data from: Optimal allocation ratios: A square root relationship between the ratios of symbiotic costs and benefits
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Online companion - A New Cooperative Framework for a Fair and Cost-Optimal Allocation of Resources within a Low Voltage Electricity Community
<p>Simulation parameters used for the article "A New Cooperative Framework for a Fair and Cost-Optimal Allocation of Resources within a Low Voltage Electricity Community" submitted for review in IEEE Transactions on Smart grid</p>
Data from: Sex allocation theory reveals a hidden cost of neonicotinoid exposure in a parasitoid wasp
Sex allocation theory has proved to be one the most successful theories in evolutionary ecology. However, its role in more applied aspects of ecology has been limited. Here we show how sex allocation theory helps uncover an otherwise hidden cost of neonicotinoid exposure in the parasitoid wasp Nasonia vitripennis. Female N. vitripennis allocate the sex of their offspring in line with Local Mate Competition (LMC) theory. Neonicotinoids are an economically important class of insecticides, but their deployment remains controversial, with evidence linking them to the decline of beneficial species. We demonstrate for the first time to our knowledge, that neonicotinoids disrupt the crucial reproductive behaviour of facultative sex allocation at sub-lethal, field-relevant doses in N. vitripennis. The quantitative predictions we can make from LMC theory show that females exposed to neonicotinoids are less able to allocate sex optimally and that this failure imposes a significant fitness cost. Our work highlights that understanding the ecological consequences of neonicotinoid deployment requires not just measures of mortality or even fecundity reduction among non-target species, but also measures that capture broader fitness costs, in this case offspring sex allocation. Our work also highlights new avenues for exploring how females obtain information when allocating sex under LMC.
Multicenter Study on Organ Acquisition Costs in the Post Re-Allocation Era: Liver Transplantation
ClinicalTrials.gov study NCT05087550. IPD Sharing: NO. Countries: 1. Publications: 0.
Data from: Sex allocation theory reveals a hidden cost of neonicotinoid exposure in a parasitoid wasp
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