Noémie Jeannin
EPFL STI IEM PV-LAB
MC A2 208 (Bâtiment MC)
Rue de la Maladière 71b, CP 526
2002 Neuchâtel 2
Web site: Web site: https://pvlab.epfl.ch/
EPFL STI IEM PV-LAB
MC A2 208 (Bâtiment MC)
Rue de la Maladière 71b, CP 526
2002 Neuchâtel 2
+41 21 695 43 21
Office:
MC A2 208
EPFL
>
VPA-AVP-PGE
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AVP-PGE-EDOC
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EDEY-GE
Web site: Web site: https://go.epfl.ch/phd-edey
Publications
Infoscience publications
Mapping the Charging Demand for Electric Vehicles in 2050 from Mobility Habits
This paper proposes a method to spatially model and compare charging needs on the European scale considering local disparities in population density, distance to city centres, car ownership and mobility habits. Mobility habits are modelled across Europe in terms of distance and time frame, to elaborate scenarios of charging behaviour. The first step of the method is to calculate the density of electric vehicles with a resolution of 1 km2, according to the progressive electrification of the fleet each year between 2020 and 2050. The second step is to quantify the mobility of commuters using their driving distance to work areas and mobility statistics. The model is then applied in a case study in Switzerland to plan the public charging infrastructure required to satisfy the charging needs of the local population. The results show a stronger need for charging in cities despite lower motorisation rates and driving distances. With 50 % of commuters charging at work and 20 % at home during the workday, the demand in the evening can be reduced by 50 % in the suburban areas compared to the baseline scenario in which all commuters are charging at home in the evening. This model can be used to quantify the energy needs of commuters, plan the deployment of the charging infrastructure, or simulate the effect of policies.
Sustainable Energy, Grid and Network. 2023-10-17. DOI : 10.2139/ssrn.4604192.What drives electricity tariffs in Switzerland? Two-stage statistical and geospatial analysis of structural differences across 1913 municipalities
We present a two-staged statistical and geospatial analysis exploring the discrepancies of household electricity tariffs across 1,913 Swiss municipalities. First, we perform a multilinear regression analysis, considering structural, sociodemographic data and energy transition indicators together with the actual regulated electricity tariffs. Secondly, a geostatistical analysis was carried to investigate upon the spatial autocorrelation of electricity tariffs with selected model variables. Outcomes show that the strong variation in electricity tariffs cannot be fully explained by the chosen socio-demographic variables or the uptake from distributed energy resources in Swiss municipalities, calling for additional research on the currently unknown influencing factors at work that shape domestic electricity tariffs in Switzerland.
2023-08-02. IEEE ISGT Europe 2023, Grenoble, France, October 23-26, 2023.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 grid reinforcement costs, which are typically high. We establish a new methodology to price and reward flexibility within low-voltage networks, in the case DSOs are able to control distributed assets. Under such assumptions, we compare the cost of providing flexibility and the cost of grid reinforcement using the CIGRE low-voltage network as a case study. 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's annual energy demand.& COPY; 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Sustainable Energy Grids & Networks. 2023-06-01. DOI : 10.1016/j.segan.2023.101041.