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Analysing the impact of the different pricing policies on PV-battery systems:A Dutch case study of a residential microgrid
Get PDFThis study investigates the techno-economic impacts of various pricing policies on a photovoltaic (PV) system combined with battery energy storage (BES) as a single integrated system within a Dutch residential building. With the increasing adoption of PV systems, managing reverse power flow and grid stability becomes crucial. The study evaluates different scenarios, including net metering, feed-in tariffs (FiT) with time-of-use (TOU), RTP pricing, and subsidised BES. Using a multi-objective genetic algorithm, the optimal size and charging/discharging patterns of the PV-BES system were determined. The optimisation simultaneously minimises the Net Present Cost (NPC) and maximises the Self-Consumption Rate (SCR), to determine the PV-BES size that achieves an optimal balance between economic and technical performance. Results indicate that RTP pricing significantly enhances SCR. While the levelised cost of electricity (LCOE) and payback periods (PBP) are initially higher in the RTP pricing scenario, subsidising BES can mitigate these disadvantages. Additionally, incorporating price limit control variables into the energy management system (EMS) optimises the charging/discharging cycles, extending BES lifetimes and potentially increasing future revenues. These findings provide insights for policymakers to balance economic benefits and grid technical requirements through effective PV-BES integration.</p
Energy Community Resilience:A Multi-Objective Approach with Shared Battery Storage Systems
No full textThe introduction of shared battery storage in the energy community (EC) grid provides a unique solution to grid congestion issues. This paper presents an energy management strategy for ECs, leveraging shared communal battery storage (CBS) integrated with community resources to optimize energy distribution. The proposed hierarchical optimization framework is used to minimize costs and CO2 emissions while maximizing self-consumption, using CBS as a modular Virtual Battery Storage (VBS) adapted to community needs. Each VBS module within the CBS is used to optimize different objective functions in the energy management framework. This study demonstrates how the VBS concept can be incorporated into community energy systems for sustainable management and grid stability. The proposed approach is tested on the Aardehuizen community model based on a real EC located in Olst, the Netherlands.</p
ARISE:A Dutch dataspace connecting nature and people
Get PDFBiodiversity is declining worldwide at an unprecedented rate. The densely populated country of the Netherlands is even one of the forerunners exhibiting this dramatic decline. In recent years, however, concern about the environment has moved decisively from niche to mainstream. In this chapter we introduce ARISE (Authoritative and Rapid Identification System for Essential biodiversity information), a government-funded research infrastructure that connects nature and people. The ambition of ARISE is to enable recognition of all natural species in order to monitor on a large scale end-to-end and near real-time biodiversity, thereby helping to 'bend the curve' of biodiversity decline. To do so, ARISE (i) provides an open data platform to collect field-captured samples and digital observations of all living organisms for species level recognition, and (ii) offers tools and services to challenge and engage researchers, policymakers and citizens to create the data to enable insights that help us to better understand biodiversity in relation to our environment and human activities. ARISE is linked to the Dutch national SURF infrastructure for data management and HPC capacity. Tools comprise: (i) an AI repository for species recognition models; (ii) smart annotation services for images and sound; (iii) dashboards, leaderboards and maps; and (iv) an array of sensors to capture multicellular species in their natural environment. As such, ARISE will be the 'one-stop-shop' or marketplace for species recognition services and non-invasive biodiversity monitoring.</p
Olfactory performance explains duality of antennal architectural designs in Lepidoptera
No full textMale attraction by females through sex pheromones is widespread among Lepidoptera, and antennae are key olfactory organs during male orientation. Broadly speaking, two designs of antennae coexist in Lepidoptera: complex (pectinate) or stick-like (filiform) ones. Pectinate antennae have attracted attention because of their multiscale geometry, assumed to outperform filiform. Yet, the filiform design is by far more common. We compare the olfactory performance of the two designs using modelling, particle image velocimetry on three-dimensional-printed scaled-up models and computational simulations. In terms of absolute odour capture, pectinate antennae perform better at nearly all flying speeds. However, when considering drag, filiform designs are more energy efficient than pectinate ones at low-flight speeds, while the reverse holds at high speeds. This is owing to the differential scaling of drag and molecule capture with flight speed. According to our results, small and slow moths would bear filiform antennae whereas big and fast moths would have pectinate ones, which is the general trend observed in nature. We discuss exceptions to this general pattern and how species could evolve from one design to the other by investigating the influence of the antennal structural elements.</p
Innovative Neonatal Therapy: Artificial Placenta (ArtPlac) Providing Combined Lung and Kidney Support
No full textLACeS: An Open, Fast, Responsible, and Efficient Longitudinal Anycast Census System
Get PDFIP anycast replicates an address at multiple locations to reduce latency and enhance resilience. Due to anycast's crucial role in the modern Internet, earlier research introduced tools to perform anycast censuses. The first, iGreedy, uses latency measurements from geographically dispersed locations to map anycast deployments. The second, MAnycast2, uses anycast to perform a census of other anycast networks. MAnycast2's advantage is speed and coverage but suffers from problems with accuracy, while iGreedy is highly accurate but slower using author-defined probing rates and costlier. In this paper we address the shortcomings of both systems and present LACeS (Longitudinal Anycast Census System). Taking MAnycast2 as a basis, we completely redesign its measurement pipeline, and add support for distributed probing, additional protocols (DNS over UDP, TCP SYN/ACK, and IPv6) and latency measurements similar to iGreedy. We validate LACeS on an anycast testbed with 32 globally distributed nodes, compare against an external anycast production deployment, extensive latency measurements with RIPE Atlas and cross-check over 60% of detected anycast using operator ground truth that shows LACeS achieves high accuracy. Finally, we provide a longitudinal analysis of anycast, covering 17+ months, showing LACeS achieves high precision. We make continual daily LACeS censuses available to the community and release the source code of the tool under a permissive open source license
A knowledge-based strategy for interpretation of SWIR hyperspectral images of rocks
Get PDFStrategies to interpret short-wave infrared hyperspectral images of rocks involve the application of analysis and classification steps that guide the extraction of geological and mineralogical information with the aim of creating mineral maps. Pre-existing strategies often rely on the use of statistical measures between reference and image spectra that are scene dependent. Therefore, classification thresholds based on statistical measures to create mineral maps are also scene dependent. This is problematic because thresholds must be adjusted between images to produce mineral maps of the same accuracy. We developed an innovative, knowledge-based strategy to perform mineralogical analyses and create classifications that overcome this problem by using physics-based wavelength positions of absorption features that are invariant between scenes as the main sources of mineral information. The strategy to interpret short-wave infrared hyperspectral images of rocks is implemented using the open source Hyperspectral Python package (HypPy) and demonstrated on a series of hyperspectral images of hydrothermally altered rock samples. The results show how expert knowledge can be embedded into a standardized processing chain to develop reproducible mineral maps without relying on statistical matching criteria
Evaluating Multi-Sensor Placement and Neural Network Architectures for Physical Activity Level Classification
Get PDFAccurate physical activity level (PAL) classification could be beneficial for osteoarthritis (OA) management. This study examines the impact of sensor placement and deep learning models on AL classification using the Metabolic Equivalent of Task values. The results show that the addition of anankle sensor (WA) significantly improves the classification of intensity activities compared to wrist-only configuration(53% to 86.2%). The CNN-LSTM model achieves the highest accuracy (95.09%). Statistical analysis confirms multi-sensor setups outperform single-sensor configurations (p < 0.05). The WA configuration offers a balance between usability and accuracy, making it a cost-effective solution for AL monitoring, particularly in OA management
Time-reversal symmetry breaking in microscopic single-crystal SrRuO devices
Get PDFTime-reversal symmetry breaking superconductivity is a quintessential unconventional quantum state. In Josephson junctions, time-reversal symmetry breaking manifests itself in the supercurrent interference pattern as the invariance of the critical current under the reversal of both transport and magnetic field directions, i.e., . So far, such systems have been realized in devices where superconductivity is injected into a deliberately constructed weak link medium, usually carefully tuned by external magnetic fields and electrostatic gating. In this work, we report time-reversal symmetry breaking in spontaneously emerging Josephson junctions without intentionally constructed weak links. This is realized in ultra-pure single-crystal microstructures of SrRuO, an unconventional superconductor with a multi-component order parameter. Here, the Josephson effect emerges intrinsically at the superconducting domain wall, where the degenerate states partially overlap. In addition to violating , we find a rich variety of exotic transport phenomena, including a supercurrent diode effect present in the entire interference pattern, two-channel critical current oscillations with a period that deviates from , fractional Shapiro steps, and current-switchable bistable states with highly asymmetric critical currents. Our findings provide direct evidence of TRSB in unstrained SrRuO and reveal the potential of domain wall Josephson junctions, which can emerge in any superconductor where the pairing symmetry is described by a multi-component order parameter
Limiting Kinetic Energy Through Control Barrier Functions:Analysis and Experimental Validation
No full textIn the context of safety-critical control, we propose and analyse the use of Control Barrier Functions (CBFs) to limit the kinetic energy of torque-controlled robots. The proposed scheme is able to modify a nominal control action in a minimally invasive manner to achieve the desired kinetic energy limit. We show how this safety condition is achieved by appropriately injecting damping in the underlying robot dynamics independently of the nominal controller structure. We present an extensive experimental validation of the approach on a 7-Degree of Freedom (DoF) Franka Emika Panda robot. The results demonstrate that this approach provides an effective, minimally invasive safety layer that is straightforward to implement and is robust in real experiments.</p