Power Generation Planning of Galapagos’ Microgrid Considering Electric Vehicles and Induction Stoves

Islands located far away from the mainland and remote communities depend on isolated microgrids based on diesel fuel, which results in significant environmental and cost issues. This is currently being addressed by integrating renewable energy sources (RESs). Thus, this paper discusses the generation planning problem in diesel-based island microgrids with RES, considering the electrification of transportation and cooking to reduce their environmental impact, and applied to the communities of Santa Cruz and Baltra in the Galapagos Islands in Ecuador. A baseline model is developed in HOMER for the existing system with diesel generation and RES, while the demand of electric vehicles and induction stoves is calculated from vehicle driving data and cooking habits in the islands, respectively. The integration of these new loads into the island microgrid is studied to determine its costs and environmental impacts, based on diesel cost sensitivity studies to account for its uncertainty. The results demonstrate the economic and environmental benefits of investing in RES for Galapagos’ microgrid, to electrify the local transportation and cooking system.

Electric Vehicle (EV) demand modeling constitutes the cornerstone of studies aiming to facilitate the integration of EVs into the power system. The different characteristics of the EV demand (departure time, arrival time, and electric demand), as well as the correlation between thereof, render EV demand modeling a complex task. The Majority of previous methods, which were developed based on the Monte Carlo simulation, are unable to observe and preserve the correlation between EV demand characteristics; because, in these methods, the EV demand characteristics are generated separately in an unsupervised manner. This study proposes a novel semi-supervised EV demand modeling approach by mapping the different EV demand characteristics into a three-dimensional (3D) space as a 3D image. To effectively realize the 3D EV demand modeling, we have employed Generative Adversarial Networks (GANs) with a 3D convolutional structure to develop EV-GANS network—a GANs structure tailored to the needs of EV demand modeling in environments hosting high demand diversity such as EV charging stations. Numerical results confirmed the effectiveness of the proposed EV-GANS in estimating the trend of the actual EV demand on the test day with a small error margin compared to the existing benchmark generation-based methods (Monte Carlo and Copula).

The urgency of sustainable, energy-efficient transportation has become extremely important as the US 1 and Global 2 energy sectors review their 2035-2040 phase-out of fossil fuel use. Top Global vehicle manufacturers have released a timeline to limit production for diesel and petrol-based three vehicles as early as 2024 4. The 2022 United States fuel costs increase reignited consumer interest in electric and hybrid transportation 5. Still, consumers are met with a limited understanding of the environmental impact expected with the fuel transition to electric transportation changes. CURRENTLY, the US has 275 million registered gas vehicles; 1.5 million electric vehicles 6. This means nearly 300 million electric automobiles will soon be introduced into the US Energy infrastructure within the next decade. Currently, the EPA approves two charging systems for residential EV charging options 7, SAE Electric Vehicle Conductive Charge Coupler (SAE J1772) Level 1, charging up to 120VAC, and Level 2, charging up to 240VAC. Level 3 direct-current (DC) Fast Charging, primarily provided by commercial providers, requires 480VAC and is not recommended for residential use due to its high energy costs 8. EPA regions in the United States experience increased electrical grid disturbances such as climate emergencies, seasonal infrastructure grid spikes, and commercial usage. The inevitable increase in EV charging raises concerns about current US federal and state policies based on the specific environmental impact of each US EPA region to support the eGrid subregion 9 preparations for expanding energy needs of an increased electric vehicle supply. Introduction By 2030, the electric vehicle will become a part of our daily necessities and social needs. The implementation of EVs can introduce similar culture-shifting changes seen with the expanded smartphone use in the 2000s or create many concerns that arose with social media in the late 2010s. Should EVs dramatically affect transportation patterns, environmental impact, energy needs, and economic changes? Can society understand the responsibility for equipment that can have profound implications if not understood? While we can assume these changes can create a greener outlook for vehicle emissions until we see the effects of gas-to-electric transitions, EVs' actual impact on our social patterns can verge on speculation. This review identifies the manufacturing impact, maintenance, and charging needs; as the economic and social equity factors for those who may lack the resources to maintain an electric vehicle responsibly. Furthermore, lastly, does the expansion of EV innovation inspire other technological and social improvements for inventors? Will this lead to re-engineering other appliances and equipment with the potential of a greener result? With the implementation of EVs, regulation must consider all aspects of accessibility to review if it improves or hinders social improvement. The maintenance of these vehicles, the accessibility of charging, the environmental regulatory needs for manufacturing, and safety are all things every potential consumer has to consider. When the expiration of gas-powered vehicles begins in 2030, regulators need to be prepared to transition prior vehicle concerns with expanded EV usage more seriously to ensure consumer safety and understand what risks come with greener expectations. Methods Regulations for electric vehicle (EV) manufacturers vary by country and region but generally aim to promote EV adoption and reduce transportation's environmental impact. Current regulations are the following: Emission standards: Local State and Federal regulations are to determine emission standards for EVs based on NEPA <> to reduce air pollution and greenhouse gas emissions per US region. Zero-emission vehicle (ZEV) mandates: Some countries and states have ZEV mandates, which require a certain percentage of new vehicle sales to be zero-emission vehicles. Financial incentives: US Department of Energy tax credits or rebates <> encourage consumers to purchase EVs. Charging infrastructure: Governments may provide funding or require the installation of charging infrastructure to support the growth of the EV market. Battery recycling: Governments may set regulations for battery recycling to ensure the proper disposal of used batteries and reduce the environmental impact of battery production. In the European Union, the European Commission has set a target of at least 30 million EVs on the road by 2025 and 60-70% of new cars to be emissions-free by 2030. In the United States, the Biden Administration has announced plans to promote the deployment of 500,000 charging stations by 2030. In China, the government has set a target of 20% of new vehicle sales to be EVs by 2025. During 2021, approximately 60,000 public electric vehicle (EV) charging stations function within the United States. The number of charging stations has been proliferating in recent years due to increased demand for EVs and efforts by governments and private companies to build out charging infrastructure. The 2021-2024 United States Presidential Administration stated plans to provide consumer access to 500,000 charging stations by 2030 eventually. This is compared to 120,000 to 130,000 working gas stations within the United States<>. The maintenance requirements for an electric vehicle (EV) are typically different from those of a traditional internal combustion engine vehicle. As such, some specialized equipment may be needed to maintain an EV properly. Here are some examples of equipment that may be required for EV maintenance: High-Voltage Disconnect Tool: To safely disconnect the high-voltage battery in an EV, a unique tool is required to safely cut power to the battery while preventing any electrical arcing. Charging Equipment: Depending on the type of EV and charging system, specialized equipment may be needed to charge the battery, including charging cables, charging stations, and DC fast-charging equipment. Diagnostic Tools: To diagnose issues with the electrical and charging systems in an EV, specialized diagnostic tools are needed that can communicate with the vehicle's onboard computers. Brake System Tools: Electric vehicles typically use regenerative braking, which can wear the brake system more than traditional internal combustion engine vehicles. As such, specialized tools may be needed to service the brake system on an EV. Tire Changing Equipment: Electric vehicles can be heavy due to the battery's weight; specialized tire changing equipment may be needed to properly adjust the tires on an EV. Discussion The average cost of an electric vehicle (EV) can vary widely depending on the model and its features. In 2021, the average price of a new EV in the United States was around $55,000. Not including EV operating costs, costs for hybrid-fuel considerations, diagnostics, and general maintenance can offset the higher upfront cost compared to internal combustion engine vehicles over time. The Department of Energy has provided financial incentives, such as tax credits or rebates, to encourage EV purchases. The cost of recharging an electric vehicle (EV) can vary widely depending on several factors, including the local cost of electricity, the size of the battery, and the charging rate. As a rough estimate, it can cost anywhere from $5 to $15 to charge an EV, depending on the specific circumstances. This can range from $5 to $8 for a small, hatchback-style EV with a 30 kWh battery to $15 or more for a large SUV with a 100 kWh battery. It is important to note that the cost of charging an EV is still typically lower than the cost of fueling an internal combustion engine vehicle with gasoline. Additionally, many electric utilities offer time-of-use rates that allow EV owners to charge their cars during off-peak hours when electricity is less expensive. This helps minimize the cost of recharging an EV. The impact of electric vehicles (EVs) on electric bills will depend on several factors, including the electric utility's rate structure, the EV owner's driving habits, and the source of the electricity used for charging. The additional costs of an EV will increase a household's electric consumption and, therefore, its electric bill. However, the impact on the electric bill will be influenced by the cost of electricity in the local area, the size of the EV battery, and how often the EV is charged. It is estimated that charging an EV can add $30 to $50 per month to a household's electric bill. However, the actual cost can be higher or lower depending on the specific circumstances.

To establish a sustainable energy supply system, renewable energy sources and low-carbon vehicles will have to become more widespread. However, it is often pointed out that the dissemination of these technologies will cause difficulties in balancing supply and demand in a power system, due to the fluctuation in the amounts of renewable energy generated and the fluctuation in the power demanded for numerous electric vehicles (EVs). The numerous EVs charging control seems to be difficult due to the difficulties in predicting EV trip behaviors, which vary depending on individual EV users. However, if we can control the total demand of numerous EVs, we can not only level their total load shape but also improve the supply-demand balancing capability of a power system to create new ancillary service businesses in the power market. This paper proposes a novel centralized EV-charging-control method to modify the total demand of EV charging by scheduling EV charging times. The proposed method is expected to be a powerful tool for a power aggregator (PAG), which will supply EV charging services to EV users and load leveling services to transmission system operators (TSOs) without inconveniencing EV users. The simulation showed that under the assumed EV trip patterns, the total charging demand of numerous EVs was successfully shaped so that the differences between watt-hours of the requirement and those of the controlled results were less than 4%.

A mountain hut (MH) is usually located in very sensitive parts of the nature. Operation phase of the MH emits pollutants into environment, because of energy supply for electricity and heat and transport linked with MH operation. If energy carriers used are mainly fossil fuel based that can cause significant environmental impacts. One of the goals of the EU SustainHuts project (http://sustainhuts.eu) is identification of technologies used for heat and electricity generation in MH. Through environmental assessment, technologies are compared to show environmental impacts of each technology prior to make case studies of specific MH. Life cycle assessment (LCA) is the basic methodology used in the study. Functional unit is 1kWh of generated energy, heat or electricity. Gabi Thinkstep software was used for LCA modelling and in life cycle impact assessment CML2001 indicators were used with additional Sofi indicators. Generic data was used from Ecoinvent 3.5 and Gabi professional database. In all MH observed electricity is partly generated with diesel generators. On other hand it is good to realize that in many cases the photovoltaic (PV) is used at least to partially cover the electricity demand. In one case (Bachimana, Pyrenes, Spain) there is small hydropower, but without optimal control. Wind turbine is a case in one MH but not working because of mechanical failure. For heat generation in many cases mixed wood is used as a main fuel source. In the case of Lizara hut propane-butane (natural gas) is used in gas heater, in the case of Bachimana diesel heater is present and the Refugio Torino is connected to the electrical grid what makes this MH unique in the sense of environmental assessment. For transportation main technologies are minivans, ropeways with electricity or diesel generators and helicopters in the case of inaccessibility. For electricity generation it is showed that from environmental point of view diesel electricity generation is the worst case, but still used in many MH since it is simple to manage and control. In many MH PV with battery energy storage/buffer slowly takes over that is much better from environmental point of view. Wind and hydro electricity generation have the lowest environmental impact, but they are not applicable in all locations. The worst case in heat generation is diesel and electricity heat generation. Natural gas has much smaller environmental impact than diesel or electricity heat generation. Wood heat generation has quite low environmental impact in global environmental indicators, but quite high in local environmental indicators, where combustion process of wood contribute to photochemical ozone creation, toxicity of marine/fresh water and also human toxicity.

Hierarchical power control strategy on small-scale electric vehicle fast charging station

The study is conducted to show the sample country applications regarding the demand for electric vehicles (EVs) and hybrid vehicles (HEVs) and the guiding role of tax policies for these instruments on the basis of tax legislation in Türkiye. In this context, the research evaluates regulatory frameworks and their impact on incentivizing the adoption of alternative fuel vehicles. The methodology employs a combination of qualitative analysis and benchmarking to assess the influence of tax policies on the demand for EVs and HEVs. Based on an examination of Türkiye’s current legislation and data on existing vehicles, the study identifies a need for adjustments in the Value Added Tax (VAT), Motor Vehicles Tax (MVT), and Special Consumption Tax (SCT) frameworks, particularly within the scope of limiting climate change. Given the identified shortcomings in Türkiye’s existing tax policies for promoting alternative fuel vehicles, the study aims to provide insights and recommendations to guide future research and policy development in this area.

This paper proposes a method for analyzing and simulating the time-dependent flexibility of electric vehicle (EV) demand. This flexibility is influenced by charging power, which depends on the charging stations, the EV characteristics, and several environmental factors. Detailed charging station data from a Dutch case study have been analysed and used as input for a simulation. In the simulation, the interdependencies between plug-in time, connection duration, and required energy are respected. The data analysis of measured data reveals that 59% of the aggregated EV demand can be delayed for more than 8 h, and 16% for even more than 24 h. The evening peak shows high flexibility, confirming the feasibility of congestion management using smart charging within flexibility constraints. The results from the simulation show that the average daily EV demand increases by a factor 21 between the ‘Present-day’ and the ‘High’ scenario, while the maximum EV demand peak increases only by a factor 6, as a result of the limited simultaneity of the transactions. Further, simulations using the average charging power of individual measured transactions yield more accurate results than simulations using a fixed value for charging power. The proposed method for simulating future EV flexibility provides a basis for testing different smart charging algorithms.

Modeling electric vehicles adoption for urban commute trips

Subsidy scheme or price discount scheme? Mass adoption of electric vehicles under different market structures

When solar PV irradiation was insufficient, a combination of solar energy, a diesel generator, and an electric car provided a satisfactory outcome in terms of maintaining a reliable power supply. A solar energy system is the building's primary energy source, and it is designed to supply all of the building's daily energy requirements. In the event of poor solar irradiation, backup energy storage technologies such as plug-in hybrid electric vehicles and diesel generators are utilised to ensure that the power supply stays uninterrupted. Three-phase active filters are employed in the electrical system to improve power quality, regulate power, and correct unbalance. When solar PV irradiation was insufficient, a combination of solar energy, a diesel generator, and an electric car provided a satisfactory outcome in terms of maintaining a reliable power supply. A solar energy system is the building's primary energy source, and it is designed to supply all of the building's daily energy requirements. In the event of poor solar irradiation, backup energy storage technologies such as plug-in hybrid electric vehicles and diesel generators are utilised to ensure that the power supply stays uninterrupted. Three-phase active filters are employed in the electrical system to improve power quality, regulate power, and correct unbalance. Local power generation, such as renewable energy sources (RES), can be integrated into the charging infrastructure to reduce the impact. Due to the intermittent and discontinuous nature of renewable energy sources, it has become increasingly difficult to synchronise the charging of electric vehicles with other grid demands and renewable energy sources. This research examines the charging of electric vehicles using smart grid technologies and considers how it interacts with renewable energy sources. In accordance with the objectives, the present research effort has been grouped into three categories: cost awareness, efficiency awareness, and emission awareness of the relationship between electric vehicles and renewable energy sources. Each discussion topic includes an explanation of the central concept, an overview of the solution, and a comparison of different works. The PHEV only transmits electricity to the load during emergencies to save battery life. This acts as impetus for the development of this work, which includes the creation of a robust algorithm, sizing, and energy management to balance load consumption and power output, all of which is done with MATLAB Simulink.

Issues related to energy sustainability and carbon emission reduction are continuously being concerned by the Government of the Republic of Indonesia. Various efforts and programs have been launched to achieve targets of the related issues. As known that energy use for cooking by the household is continuously increasing in relation to population growth that will of course increase in energy need which relates to the sustainability of presence energy and carbon emission. Accordingly, the LPG stove conversion program to an electric stove was introduced in order to achieve the target to solve such issues. This paper compared of efficiency and carbon emissions of both electric filament stoves and induction stoves. The result indicated that the induction stove has better efficiency compared with the electric stove. The study also was proved that the carbon emissions for both types of stoves were relatively low in comparison with LPG stoves. However, the enormous operational power of the induction stove is still a challenge that must be resolved to achieve the target of energy sustainability in Indonesia.

This paper identifies and quantifies major determinants of future electric vehicle (EV) demand in order to inform widely-held aspirations for market growth. Our model compares three channels that will affect EV market share in the United States from 2020-2035: intrinsic (no-subsidy) EV demand growth, net-of-subsidy EV cost declines (e.g. batteries), and government subsidies. Geographic variation in preferences for sedans and light trucks highlights the importance of viable EV alternatives to conventional light trucks; belief in climate change is highly correlated with EV adoption patterns; and the first $500 billion in cumulative nationwide EV subsidies is associated a 7-10 percent increase in EV market share in 2035, an effect that diminishes as subsidies increase. The rate of intrinsic demand growth dwarfs the impact of demand-side subsidies and battery cost declines, highlighting the importance of non-monetary factors (e.g. charging infrastructure, product quality and/or cultural acceptance) on EV demand.

This paper identifies and quantifies major determinants of future electric vehicle (EV) demand in order to inform widely-held aspirations for market growth. Our model compares three channels that will affect EV market share in the United States from 2020-2035: intrinsic (no-subsidy) EV demand growth, net-of-subsidy EV cost declines (e.g. batteries), and government subsidies. Geographic variation in preferences for sedans and light trucks highlights the importance of viable EV alternatives to conventional light trucks; belief in climate change is highly correlated with EV adoption patterns; and the first $500 billion in cumulative nationwide EV subsidies is associated a 7-10 percent increase in EV market share in 2035, an effect that diminishes as subsidies increase. The rate of intrinsic demand growth dwarfs the impact of demand-side subsidies and battery cost declines, highlighting the importance of non-monetary factors (e.g. charging infrastructure, product quality and/or cultural acceptance) on EV demand. Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

Grid frequency regulation strategy considering individual driving demand of electric vehicle