Agent-Based Modelling of Charging Behaviour of Electric Vehicle Drivers

The combination of electric vehicles (EVs) and intermittent renewable energy sources has received increasing attention over the last few years. Not only does charging electric vehicles with renewable energy realize their true potential as a clean mode of transport, charging electric vehicles at times of peaks in renewable energy production can help large scale integration of renewable energy in the existing energy infrastructure. We present an agent-based model that investigates the potential contribution of this combination. More specifically, we investigate the potential effects of different kinds of policy interventions on aggregate EV charging patterns. The policy interventions include financial incentives, automated smart charging, information campaigns and social charging. We investigate how well the resulting charging patterns are aligned with renewable energy production and how much they affect user satisfaction of EV drivers. Where possible, we integrate empirical data in our model, to ensure realistic scenarios. We use recent theory from environmental psychology to determine agent behaviour, contrary to earlier simulation models, which have focused only on technical and financial considerations. Based on our simulation results, we articulate some policy recommendations. Furthermore, we point to future research directions for environmental psychology scholars and modelers who want to use theory to inform simulation models of energy systems

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Mobility in the smart grid: roaming protocols for EV charging

While most smart grids approaches assume that the user consumes services in a fixed location, the case of charging Battery Electric Vehicles (BEVs) adds an interesting mobility dimension. Drivers increasingly need to rely on public charging facilities, and given local grid conditions, such facilities often cannot offer their services without smart charging and tight integration in the smart grid. In analogy with mobile telecommunications, stakeholders in the field of EV charging have developed EV roaming protocols to allow for a mobility dimension, and, for some, add smart grid integration. However, this development is still in its early phase, and in Europe, there are at least four different, mutually incompatible protocols in use. In this paper, we investigate the history of these protocols, their characteristics – especially in relation to the smart grid – and investigate their openness and neutrality. We then explore scenarios for future development towards a single standard, also taking the regulatory dimension into consideration. We end with a reflection on the development of standards for the smart grid

L'isola magica. Haiti

Traduzione e cura dell'edizione italiana. Note al testo, apparato critico e bibliografia. Interazione con l'autrice/curatrice durante la stesura del testo

Multiple roads ahead: How charging behavior can guide charging infrastructure roll-out policy

A key challenge for the roll-out of public charging infrastructure is that electric vehicles are needed to function both as a clean mode of transportation and as part of a sustainable electricity system, while being cost-effective. Translating these high-level policy goals to a coherent roll-out strategy is not trivial. We address this by analyzing local charging behavior and linking behavior indicators to specific policy measures through a decision tree. We analyze how policy measures for: (1) increasing the number of charge points, (2) reducing hogging, (3) vehicle-to-grid, (4) overnight charging, and (5) solar charging align with overall goals and characteristics of specific neighborhoods. More specifically, we analyze a dataset containing one million charging sessions in the Netherlands, and (1) link this data to neighborhood characteristics and (2) evaluate the coherency of policy mixes. Our analysis shows great spatial variation in charging behavior and consequently in the suitable policy mixes

Multiple roads ahead: How charging behavior can guide charging infrastructure roll-out policy

A key challenge for the roll-out of public charging infrastructure is that electric vehicles are needed to function both as a clean mode of transportation and as part of a sustainable electricity system, while being cost-effective. Translating these high-level policy goals to a coherent roll-out strategy is not trivial. We address this by analyzing local charging behavior and linking behavior indicators to specific policy measures through a decision tree. We analyze how policy measures for: (1) increasing the number of charge points, (2) reducing hogging, (3) vehicle-to-grid, (4) overnight charging, and (5) solar charging align with overall goals and characteristics of specific neighborhoods. More specifically, we analyze a dataset containing one million charging sessions in the Netherlands, and (1) link this data to neighborhood characteristics and (2) evaluate the coherency of policy mixes. Our analysis shows great spatial variation in charging behavior and consequently in the suitable policy mixes

Conceptualization of a vehicle-to-grid assisted nation-wide renewable energy system – A case study with spain

This study explores the potential of Vehicle-to-Grid (V2G) technology in utilizing Electric Vehicle (EV) batteries for energy storage, aiming to fulfil Spain's 2030 and 2050 energy goals. The validated Simulink model uses 3.15 million EVs in 2030 and 22.7 million EVs in 2050 as primary energy storage. The results show that Spain can achieve its 2030 target of 42 % renewable energy by utilizing 800 GW of PV + Wind, or 220 GW of installations combined with an annual import of 18 TWh. For the 2050 goal of 97 % renewable energy, the study proposes 1300 GW installation without external support, or 600 GW renewable energy source installation with a 50 TWh import. Detailed analysis shows that the storage provided by 3.15 million EVs can replace 122 GW of new energy storage installation in 2030 and 22.7 million EVs replace 2.7 TW of new energy storage requirements in 2050 to support high penetration of intermittent renewable energy installations. The analysis showcases the substantial storage capacity provided by EVs, emphasizing their potential as a primary ESS and the effectiveness of V2G technology in grid support. The overall results underscore V2G technology's role in minimizing the need for additional energy storage infrastructure in the future

Agent-based modelling of charging behaviour of electric vehicle drivers

The combination of electric vehicles (EVs) and intermittent renewable energy sources has received increasing attention over the last few years. Not only does charging electric vehicles with renewable energy realize their true potential as a clean mode of transport, charging electric vehicles at times of peaks in renewable energy production can help large scale integration of renewable energy in the existing energy infrastructure. We present an agent-based model that investigates the potential contribution of this combination. More specifically, we investigate the potential effects of different kinds of policy interventions on aggregate EV charging patterns. The policy interventions include financial incentives, automated smart charging, information campaigns and social charging. We investigate howwell the resulting charging patterns are aligned with renewable energy production and how much they affect user satisfaction of EV drivers. Where possible, we integrate empirical data in our model, to ensure realistic scenarios. We use recent theory from environmental psychology to determine agent behaviour, contrary to earlier simulation models, which have focused only on technical and financial considerations. Based on our simulation results, we articulate some policy recommendations. Furthermore, we point to future research directions for environmental psychology scholars and modelers who want to use theory to inform simulation models of energy systems