scholarly journals The Measures of State Support for the Development of Electric Vehicles in Germany

2021 ◽  
Vol 20 (2) ◽  
pp. 93-99
Author(s):  
Andrey Sobolev ◽  
◽  
Dmitriy Poptsov ◽  
Keyword(s):  
Electric Vehicles ◽  
Financial Incentives ◽  
Financial Support ◽  
Federal Republic Of Germany ◽  
Charging Infrastructure ◽  
Support Measures ◽  
Separate Area ◽  
Direct Payments ◽  
The Government ◽  
Main Support

The development of electromobility is currently the focus of the government of the Federal Republic of Germany. To stimulate the transition to new types of environmentally friendly and climate-neutral transport, various measures of financial support are used – both direct payments and tax preferences. A separate area of work is the introduction of modern charging infrastructure. Much attention is paid to building up research and development competencies in these areas. The article provides an overview of the main support measures in force for electromobility in Germany. It is concluded that the transition to climate neutral transport is possible with a combination of both direct financial incentives and large government investments in new charging infrastructure.

scholarly journals Redefining Goods Movement: Building an Ecosystem for the Introduction of Heavy-Duty Battery-Electric Vehicles

2021 ◽  
Vol 12 (3) ◽  
pp. 147
Author(s):  
Dawn Fenton ◽  
Aravind Kailas
Keyword(s):  
Electric Vehicles ◽  
Market Development ◽  
Lead Times ◽  
Heavy Duty ◽  
Charging Infrastructure ◽  
Goods Movement ◽  
Movement Building ◽  
The Government ◽  
The Many ◽  
Development Incentives

This article reviews the Volvo Low-Impact Heavy Green Transport Solution (LIGHTS) project, a multifaceted public–private partnership in Southern California, and provides some early insights and a model for successful fleet adoption of Class 8 battery-electric trucks. This paradigm shift in commercial trucking is emerging, forcing greater interdependence among many stakeholders—fleets, %, truck manufacturers, and policymakers—not currently engaged in the traditional heavy-duty commercial truck market. The many perspectives from this article such as lead times and costs associated with the deployment of charging infrastructure, developing the workforce to support largescale deployments, and the need for market development incentives from the government can be used to inform the programs and policies of California and other states seeking to follow their lead.

Electrifying Ride-Hailing in the United States, Europe, and Canada: How to Enable Ride-Hailing Drivers to Switch to Electric Vehicles

2021 ◽  
Author(s):  
Leah Lazer ◽  
Sadanand Wachche ◽  
Ryan Sclar ◽  
Sarah Cassius
Keyword(s):  
United States ◽  
Internal Combustion Engine ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Financial Incentives ◽  
Combustion Engine ◽  
The United States ◽  
Charging Infrastructure ◽  
Transportation Emissions ◽  
Ev Charging

Efforts to reduce transportation emissions through electrification can accelerate their impact by focusing on intensively used vehicles. Vehicles driven on ride-hailing platforms such as Uber and Lyft are intensively used, and their distinct charging patterns can support the development of essential electric vehicle (EV) charging infrastructure. However, vehicles used for ride-hailing are often missed by actions to electrify other intensively used vehicles, and an array of disparately available financial incentives, EV models, and charging options produce a complicated landscape where it is often unclear whether an EV costs more or less than an internal combustion engine (ICE) vehicle or is suitable for ride-hailing. As a result, in U.S., European, and Canadian cities, the share of EVs among vehicles used for ride-hailing is often lower than or similar to the share of EVs in the overall vehicle stock. This paper identifies the largest barriers that prevent ride-hailing drivers from accessing EVs and analyzes ways that governments, industry and other stakeholders can tackle those barriers. It includes city scorecards that evaluate 10 U.S., European and Canadian cities on their progress towards dismantling these barriers, using an original methodology and data from Uber.

ARTIFICIAL NEURAL NETWORK FOR LONG TERM LOAD FORECASTING IN UTTARAKHAND STATE: A CASE STUDY

2021 ◽  
pp. 55-56
Author(s):  
Rakesh Kumar ◽  
Rakesh Ranjan ◽  
Mukesh Verma
Keyword(s):  
Neural Network ◽  
Electric Vehicles ◽  
New Technologies ◽  
Load Forecasting ◽  
Consumption Pattern ◽  
Hydro Power ◽  
Charging Infrastructure ◽  
The Government ◽  
New Infrastructure

Electricity is one of the essential part of our life. With the increase in consumption of resources the demand of electricity is also increased. Uttarakhand as hilly state is approaching towards implementation of new Technologies and Techniques in the area of growth and suistainable development. Due to the implementation of better road infrastructure, tourism connectivity and IoT devices in various projects and inclusion of electric vehicles and their charging infrastructure in Uttarakhand State the demand of electricity has also increased. The Uttarakhand State has planned the establishment of new infrastructure by providing relaxation on various taxes and option of subsidy to investors. The exemption on xed electricity charges is provided to investors in Uttarakhand. The highest part of Electricity Generation is based on Hydro Power in Uttarakhand. By establishment of new infrastructure in Uttarakhand it would be a thrust to load generation companies to produce demanded of electricity on time. In this study the long-term load forecasting from 2022 to 2030 is analysed using Articial Neural Network. The input data is received from Uttarakhand Electricity Regulatory Commission and Uttarakhand Power Corporation Limited. The prediction is based on last 10 years data of historical load, GDP, Population, and past two years data of electric vehicles, and charging infrastructure. In this study, it has reported that by 2030 there would be huge change in infrastructure and most of diesel and petrol vehicles would come on electric vehicles. This study is focused on the Long-Term Load Forecasting in Uttarakhand State where electric vehicles and charging infrastructure load requirement is also calculated. Using Deep Learning Technique in this paper Articial Neural Network is used for forecasting the results. This tool is used to identify the consumption pattern of electricity in Uttarakhand State for further nine years from 2022 to 2030. The Government of Uttarakhand has planned Vision 2030 for the sustainable development in Uttarakhand.

scholarly journals Determining policy recommendations towards electric vehicles incentives in Jakarta using AHP-Entropy

2021 ◽  
Vol 927 (1) ◽  
pp. 012007
Author(s):  
Arighi Radevito ◽  
Dannya Maharani Putri Utami
Keyword(s):  
Electric Vehicles ◽  
Entropy Method ◽  
Capital City ◽  
The Sustainable Development ◽  
Charging Infrastructure ◽  
Incentive Policy ◽  
Consumer Benefits ◽  
Environmental Failures ◽  
Effective Policy ◽  
The Government

Abstract One solution for diminishing carbon outflows is to provide electric vehicles (EV), which can help the sustainable development of the ecosystem in an environmentally way. Jakarta, as a capital city with high levels of pollution, has forced the government to recognize the need for policymakers to correct environmental failures through effective policy solutions. To support policy-driven adoption of EV, incentives shall be given to stimulate EV users. Current regulations have not yet explained regulations for EV’s, direct and indirect consumer benefits, infrastructure for charging, and complementary policies. This paper will compare the world’s best EV policy which will determine the main policy criteria to be developed for Jakarta’s regulation using the analytical hierarchy process and entropy method in giving scaled preferences of sets of standards and alternatives with acceptable inconsistency. AHP is used to determine initial subjective weights from experts, while then entropy will enhance AHP’s weights into objective weight. This study shows that charging infrastructure is the most influential criterion among other criteria followed by consumer incentive, both direct and indirect, complimentary policies, and regulatory incentives. Therefore, it is highly recommended that Jakarta’s government develop EV’s incentive policy in detail as the order above.

scholarly journals A Study on the Adoption of Electric Vehicles in India: The Mediating Role of Attitude

2019 ◽  
Vol 24 (1) ◽  
pp. 23-34
Author(s):  
Anil Khurana ◽  
V. V. Ravi Kumar ◽  
Manish Sidhpuria
Keyword(s):  
Electric Vehicles ◽  
Internal Combustion Engines ◽  
Charging Infrastructure ◽  
Electric Cars ◽  
Mediating Role ◽  
Electric Car ◽  
Toxic Emission ◽  
Range Anxiety ◽  
Fossil Fuel Emission ◽  
The Government

Pollution of the environment is currently a global concern. Toxic emission from internal combustion engines is one of the primary air pollutants. In order to mitigate the effects of fossil fuel emission and address environmental concerns (ECs), electric vehicles (EVs) are being promoted aggressively all over the world. Various governments are encouraging people to switch to EVs by incentivizing the transition. Previous studies indicate that the high cost of the electric car, non-availability of charging infrastructure, time and range anxiety act as impediments to consumer adoption. The Government of India has given a call for ‘only Electric Vehicles’ on Road by 2030. This article is contemporary and examines the different factors that affect a consumer’s adoption of an EV. The respondents of the study are existing car owners in India. The data were analysed using Structured Equation Modelling (SEM). Attitude (ATT) emerged as a strong mediator, influencing the adoption of electric cars.

Colombia’s economy will begin to recover in 2021

2021 ◽  
Keyword(s):  
Central Bank ◽  
Financial Support ◽  
Household Consumption ◽  
Economic Recovery ◽  
Inflation Expectations ◽  
Content Type ◽  
National Statistics ◽  
Support Measures ◽  
The Government

Significance This partial revival, fuelled by an increase in household consumption, nevertheless fell short of offsetting the devastating effects of the strict COVID-19 lockdown measures imposed in the first half of the year. The economy closed 2020 with a 6.8% contraction, according to the latest figures published by the national statistics agency. Impacts The Central Bank will maintain its accommodative stance to support economic recovery; inflation expectations remain well anchored. The weakness of the ruling coalition in Congress will see Duque struggle to advance his agenda. Protests will resume as restrictions ease and the government ends financial support measures delivered over the last year.

scholarly journals Spatial Differentiation of the Public Transport Modal Split for Integration into the Location Analysis for Charging Infrastructure

2018 ◽  
Author(s):  
Waldemar Brost ◽  
Teresa Funke ◽  
Michael Lembach
Keyword(s):  
Electric Vehicles ◽  
Public Transport ◽  
Spatial Differentiation ◽  
Traffic Modeling ◽  
Data Sets ◽  
Federal Republic Of Germany ◽  
Charging Infrastructure ◽  
Modal Split ◽  
Traffic Volumes ◽  
Model Approach

The spread of charging infrastructure (CIS) for battery electric vehicles is crucial for coping with the increasing number of electric vehicles. Therefore, the selection of ideal (fast-) charging locations determines acceptance, utilization and, thus, the economic viability of a single site or the whole charging network. The methodology of the Integrated Model Approach STELLA[1] for site identification of CIS uses proven methods of traffic modeling such as the classic four-step traffic modeling in a new context to enable statements regarding the positioning of CIS. Based on different spatial analyzes and characterizations of urban quarters, traffic generated by individuals is calculated using the FGSV approach of 2010. Because only (electric) motorized individual traffic is of importance for CIS, the share of trips is calculated by differentiating the modal split between various transport groups. One approach is to concretize the modal split share of public transport based on analyzes of different criteria and data sets, e.g. the accessibility of stops. The model approach STELLA, which also combines various extensive data (e.g. transport networks and traffic volumes, settlement structures, vehicle characteristics, power supply data and user requirements), is currently developed for a planning area covering the entire territory of the Federal Republic of Germany. [1] STELLA is the acronym for the German term "STandortfindungsmodell für ELektrische LAdeinfrastruktur”.

European and Ukrainian experience in financial support to farming activities through fiscal instruments

2020 ◽  
Vol 23 (9) ◽  
pp. 1040-1063
Author(s):  
E.A. Nepochatenko ◽  
E.T. Prokopchuk ◽  
B.S. Guzar
Keyword(s):  
Agricultural Production ◽  
Financial Incentives ◽  
Financial Support ◽  
Financial Regulation ◽  
Negative Impact ◽  
Developed Countries ◽  
European Countries ◽  
Main Task ◽  
Statistical Research ◽  
Tax Regimes

Subject. The article considers financial regulation through the use of tax mechanisms. Objectives. The aim of the study is to evaluate European and Ukrainian practices of fiscal incentives for farming through fiscal instruments with VAT playing the key role. Methods. In the study we employed economic and statistical research methods, like monographic, comparison, scientific generalization. Results. Based on the analysis of VAT implementation on farmers in developed countries in Europe we substantiated the conclusion about its focus on simplifying the tax procedures and eliminating the negative impact on operations of economic entities. Special tax treatment (including VAT collection) is mainly used to streamline tax relations, taking into account the specifics of farming, rather than to improve the financial support to farms. We revealed that in the Ukrainian practice its main task is financial support to agricultural production. Conclusions and Relevance. The experience of developed European countries on the use of special tax regimes and taxation procedures should serve as a model for Ukraine. Financial incentives for agricultural production development should be directly supported by the State, and special tax treatment and tax administration should be focused on streamlining tax relations in the region, based on the practice of developed European countries such as UK, Germany, Italy and France.

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