arXiv subjects

Nicolas Wyrsch

Publications and source records attributed to Nicolas Wyrsch.

15 recordsLinked to original sources

arXiv2026

A Hydrogenated Amorphous Silicon Photodiode indirect flexible device for radiation flux measurements at low intensities

The objective of the Photo-HASPIDE experiment is the construction and test of an indirect a-Si:H (Hydrogenated Amorphous Silicon) photo-detector plus scintillator device on a flexible substrate for the detection and measurement of particles fluxes (X-rays, electrons and protons) and for dosimetric measurements. The idea behind this experimental project lies in the utilization of Hydrogenated Amorphous Silicon (a-Si:H) as photodiode material; owing to its notable attributes of radiation hardness, light detection capability and mechanical flexibility. After the implementation of the HASPIDE experiment, which explored direct radiation detection using a-Si:H devices on a polyimide (PI) substrate, we aim to delve into indirect detection by employing these devices in conjunction with flexible and rad-hard scintillators like polysiloxane. The indirect detector design holds promise for improved responsiveness to low radiation fluxes compared to direct detection methods. The indirect a-Si:H detector should be composed of arrays of small (about 5 x 5 mm2) scintillator crystals read by a-Si:H photodiodes. Through optimization of the scintillator and detector thicknesses, we expect to achieve a better performance for low minimum detectable fluxes compared to direct detection methodologies. This new detector will find application in in-vivo dosimetry during radiotherapy or hadron-therapy and also, due to its expected fast response, in FLASH therapy. Another important application will be also in Solar Physics using these devices to measure particle fluxes in solar energetic particle events.

physics.ins-det↗

arXiv2025

Techno-Economic Case Study of a Rural Local Electricity Community in Switzerland

Local Electricity Communities (communaut\'es \'electriques locales, CEL) will become operational in Switzerland in 2026, allowing prosumers, consumers, and storage operators within the same municipality and distribution system operator (DSO) area to exchange electricity over the public grid with reduced distribution tariffs. This report examines a rural Swiss case study to explore the techno-economic implications of CELs for both participants and the local DSO. The findings indicate that CELs can enhance the local use of renewable generation, particularly photovoltaics, and offer modest financial gains, with outcomes strongly shaped by community size, composition, and tariff design. Larger and more heterogeneous communities achieve better internal matching of supply and demand, though the overall incentive remains limited because the tariff reduction applies only to distribution charges. The study further shows that internal energy exchange is maximized when local PV generation covers roughly 1-2 times the community load. For DSOs, CELs reduce grid imports (27-46%), resulting in a substantial reduction in distribution tariff revenues (17-36%), necessitating regulatory adaptation. While centralized batteries provide economic value to members, their technical impact on the grid remains modest due to their small, economically optimized capacity. Larger centralized storage is shown to reduce transformer peak power, but risks increasing line loading, suggesting a need for careful sizing and placement.

eess.SY↗

arXiv2025

A modeling framework to support the electrification of private transport in African cities: a case study of Addis Ababa

The electrification of road transport, as the predominant mode of transportation in Africa, represents a great opportunity to reduce greenhouse gas emissions and dependence on costly fuel imports. However, it introduces major challenges for local energy infrastructures, including the deployment of charging stations and the impact on often fragile electricity grids. Despite its importance, research on electric mobility planning in Africa remains limited, while existing planning tools rely on detailed local mobility data that is often unavailable, especially for privately owned passenger vehicles. In this study, we introduce a novel framework designed to support private vehicle electrification in data-scarce regions and apply it to Addis Ababa, simulating the mobility patterns and charging needs of 100,000 electric vehicles. Our analysis indicate that these vehicles generate a daily charging demand of approximately 350 MWh and emphasize the significant influence of the charging location on the spatial and temporal distribution of this demand. Notably, charging at public places can help smooth the charging demand throughout the day, mitigating peak charging loads on the electricity grid. We also estimate charging station requirements, finding that workplace charging requires approximately one charging point per three electric vehicles, while public charging requires only one per thirty. Finally, we demonstrate that photovoltaic energy can cover a substantial share of the charging needs, emphasizing the potential for renewable energy integration. This study lays the groundwork for electric mobility planning in Addis Ababa while offering a transferable framework for other African cities.

eess.SY↗

arXiv2024

Assessing strategies to manage distributed photovoltaics in Swiss low-voltage networks: An analysis of curtailment, export tariffs, and resource sharing

The integration of photovoltaic systems poses several challenges for the distribution grid, mainly due to the infrastructure not being designed to handle the upstream flow and being dimensioned for consumption only, potentially leading to reliability and stability issues. This study investigates the use of capacity-based tariffs, export tariffs, and curtailment policies to reduce negative grid impacts without hampering PV deployment. We analyze the effect of such export tariffs on three typical Swiss low-voltage networks (rural, semi-urban, and urban), using power flow analysis to evaluate the power exchanges at the transformer station, as well as line overloading and voltage violations. Finally, a simple case of mutualization of resources is analyzed to assess its potential contribution to relieving network constraints and the economic costs of managing LV networks. We found that the tariff with capacity-based components on the export (CT export daily) severely penalizes PV penetration. This applies to other tariffs as well (e.g. IRR monthly, Curtailment 30, and DT variable) but to a lesser extent. However, the inclusion of curtailment at 50\% and 70\%, as well as mixed tariffs with capacity-based components at import and curtailment, allow for a high degree of PV installations in the three zones studied and help to mitigate the impact of PV on the distributed network.

eess.SY↗

arXiv2024

Reinforcement Learning for Efficient Design and Control Co-optimisation of Energy Systems

The ongoing energy transition drives the development of decentralised renewable energy sources, which are heterogeneous and weather-dependent, complicating their integration into energy systems. This study tackles this issue by introducing a novel reinforcement learning (RL) framework tailored for the co-optimisation of design and control in energy systems. Traditionally, the integration of renewable sources in the energy sector has relied on complex mathematical modelling and sequential processes. By leveraging RL's model-free capabilities, the framework eliminates the need for explicit system modelling. By optimising both control and design policies jointly, the framework enhances the integration of renewable sources and improves system efficiency. This contribution paves the way for advanced RL applications in energy management, leading to more efficient and effective use of renewable energy sources.

cs.LG↗

arXiv2024

Amorphous silicon detectors for proton beam monitoring in FLASH radiotherapy

Ultra-high dose rate radiation therapy (FLASH) based on proton irradiation is of major interest for cancer treatments but creates new challenges for dose monitoring. Amorphous hydrogenated silicon is known to be one of the most radiation-hard semiconductors. In this study, detectors based on this material are investigated at proton dose rates similar to or exceeding those required for FLASH therapy. Tested detectors comprise two different types of contacts, two different thicknesses deposited either on glass or on polyimide substrates. All detectors exhibit excellent linear behaviour as a function of dose rate up to a value of 20 kGy/s. Linearity is achieved independently of the depletion condition of the device and remarkably in passive (unbiased) conditions. The degradation of the performance as a function of the dose rate and its recovery are also discussed.

hep-ex↗

arXiv2023

A Hydrogenated amorphous silicon detector for Space Weather Applications

The characteristics of a hydrogenated amorphous silicon (a-Si:H) detector are presented here for monitoring in space solar flares and the evolution of large energetic proton events up to hundreds of MeV. The a-Si:H presents an excellent radiation hardness and finds application in harsh radiation environments for medical purposes, for particle beam characterization and in space weather science and applications. The critical flux detection threshold for solar X rays, soft gamma rays, electrons and protons is discussed in detail.

physics.ins-det↗

arXiv2023

Reinforcement Learning for Joint Design and Control of Battery-PV Systems

The decentralisation and unpredictability of new renewable energy sources require rethinking our energy system. Data-driven approaches, such as reinforcement learning (RL), have emerged as new control strategies for operating these systems, but they have not yet been applied to system design. This paper aims to bridge this gap by studying the use of an RL-based method for joint design and control of a real-world PV and battery system. The design problem is first formulated as a mixed-integer linear programming problem (MILP). The optimal MILP solution is then used to evaluate the performance of an RL agent trained in a surrogate environment designed for applying an existing data-driven algorithm. The main difference between the two models lies in their optimization approaches: while MILP finds a solution that minimizes the total costs for a one-year operation given the deterministic historical data, RL is a stochastic method that searches for an optimal strategy over one week of data on expectation over all weeks in the historical dataset. Both methods were applied on a toy example using one-week data and on a case study using one-year data. In both cases, models were found to converge to similar control solutions, but their investment decisions differed. Overall, these outcomes are an initial step illustrating benefits and challenges of using RL for the joint design and control of energy systems.

math.OC↗

arXiv2023

Balancing DSO interests and PV system economics with alternative tariffs

Distributed rooftop photovoltaics (PV) is one of the pillars of the energy transition. However, the massive integration of distributed PV systems challenges the existing grid, with high amounts of PV injection possibly leading to over-voltage and reverse power flow, with line and transformer overloading, among other issues. Moreover, the increase in PV self-consumption and consequently the reduction of imported electricity poses a problem in recovering Transmission System Operators (TSOs) and Distribution System Operators (DSOs) grid costs, that until now have been directly linked to the amount of electricity consumed due to the volumetric nature of traditional tariffs. To investigate whether alternative tariffs could mitigate PV impacts at the distribution level without hampering PV development, we assess five electricity tariffs that could help the DSOs to recover the costs of maintaining the distribution grid. Additionally, we evaluate how such tariffs may affect private investment in storage and their impact on three types of low-voltage networks (i.e., urban, semi-urban, and rural). We found that tariffs with a capacity-based component promote further adoption of PV and storage. At the same time, they allow the DSOs to recover the grid cost without incurring relevant economic differences for the customer. However, all assessed tariffs were found to have a limited role in mitigating PV impacts at the distribution level.

eess.SY↗

arXiv2021

Privacy-preserving methods for smart-meter-based network simulations

Smart-meters are a key component of energy transition. The large amount of data collected in near real-time allows grid operators to observe and simulate network states. However, privacy-preserving rules forbid the use of such data for any applications other than network operation and billing. Smart-meter measurements must be anonymised to transmit these sensitive data to a third party to perform network simulation and analysis. This work proposes two methods for data anonymisation that enable the use of raw active power measurements for network simulation and analysis. The first is based on an allocation of an externally sourced load database. The second consists of grouping smart-meter data with similar electric characteristics, then performing a random permutation of the network load-bus assignment. A benchmark of these two methods highlights that both provide similar results in bus-voltage magnitude estimation concerning ground-truth voltage.

cs.CR↗

arXiv2021

Distributed flexibility as a cost-effective alternative to grid reinforcement

The deployment of distributed photovoltaics (PV) in low-voltage networks may cause technical issues such as voltage rises, line ampacity violations, and transformer overloading for distribution system operators (DSOs). These problems may induce high grid reinforcement costs. In this work, we assume the DSO can control each prosumer's battery and PV system. Under such assumptions, we evaluate the cost of providing flexibility and compare it with grid reinforcement costs. Our results highlight that using distributed flexibility is more profitable than reinforcing a low-voltage network until the PV generation covers 145% of the network annual energy demand.

eess.SY↗

arXiv2020

Hydrogenated amorphous silicon detectors for particle detection, beam flux monitoring and dosimetry in high-dose radiation environment

Hydrogenated amorphous silicon (a-Si:H) has remarkable radiation resistance properties and can be deposited on a lot of different substrates. A-Si:H based particle detectors have been built since mid 1980s as planar p-i-n or Schottky diode structures; the thickness of these detectors ranged from 1 to 50 micron. However MIP detection using planar structures has always been problematic due to the poor S/N ratio related to the high leakage current at high depletion voltage and the low charge collection efficiency. The usage of 3D detector architecture can be beneficial for the possibility to reduce inter-electrode distance and increase the thickness of the detector for larger charge generation compared to planar structures. Such a detector can be used for future hadron colliders for its radiation resistance and also for X-ray imaging. Furthermore the possibility of a-Si:H deposition on flexible materials (like kapton) can be exploited to build flexible and thin beam flux measurement detectors and x-ray dosimeters.

physics.ins-det↗

arXiv2019

Mitigating the impact of distributed PV in a low-voltage grid using electricity tariffs

A high share of distributed photovoltaic (PV) generation in low-voltage networks may lead to over-voltage, and line/transformer overloading. To mitigate these issues, we investigate how advanced electricity tariffs could ensure safe grid operation hile enabling building owners to recover their investment in a PV and storage system. We show that dynamic volumetric electricity prices trigger economic opportunities for large investments in PV and battery capacity but lead to more pressure on the grid while capacity and block rate tariffs mitigate over-voltage and decrease line loading issues. However, block rate tariffs significantly decrease the optimal PV installation size.

eess.SY↗

arXiv2019

Unsupervised algorithm for disaggregating low-sampling-rate electricity consumption of households

Non-intrusive load monitoring (NILM) has been extensively researched over the last decade. The objective of NILM is to identify the power consumption of individual appliances and to detect when particular devices are on or off from measuring the power consumption of an entire house. This information allows households to receive customized advice on how to better manage their electrical consumption. In this paper, we present an alternative NILM method that breaks down the aggregated power signal into categories of appliances. The ultimate goal is to use this approach for demand-side management to estimate potential flexibility within the electricity consumption of households. Our method is implemented as an algorithm combining NILM and load profile simulation. This algorithm, based on a Markov model, allocates an activity chain to each inhabitant of the household, deduces from the whole-house power measurement and statistical data the appliance usage, generate the power profile accordingly and finally returns the share of energy consumed by each appliance category over time. To analyze its performance, the algorithm was benchmarked against several state-of-the-art NILM algorithms and tested on three public datasets. The proposed algorithm is unsupervised; hence it does not require any labeled data, which are expensive to acquire. Although better performance is shown for the supervised algorithms, our proposed unsupervised algorithm achieves a similar range of uncertainty while saving on the cost of acquiring labeled data. Additionally, our method requires lower computational power compared to most of the tested NILM algorithms. It was designed for low-sampling-rate power measurement (every 15 min), which corresponds to the frequency range of most common smart meters.

cs.LG↗

arXiv2019

Amorphous silicon-based microchannel plate detectors with high multiplication gain

With their fast response time and a spatial resolution in the range of a few microns, microchannel plates (MCPs) are a prominent choice for the development of detectors with highest resolution standards. Amorphous silicon-based microchannel plates (AMCPs) aim at overcoming the fabrication drawbacks of conventional MCPs and the long dead time of their individual channels. AMCPs are fabricated via plasma deposition and dry reactive ion etching. Using a state-of-the-art dry reactive ion etching process, the aspect ratio, so far limited to a value of 14, could be considerably enhanced with a potential for very high gain values. We show first fabricated AMCP devices and provide an outlook for gain values to be expected based on the fabrication results.

physics.ins-det↗