High-resolution spatial modelling of greenhouse gas emissions from land-use change to energy crops in the United Kingdom

Funded by Energy Technologies Institute EPSRC-Supergen. Grant Number: EP/M013200/1

Impacts of Electric Vehicle charging under electricity market operations

The Irish government set a target in 2008 that 10% of all vehicles in the transport fleet be powered by electricity by 2020. Similar electric vehicle targets have been introduced in other countries. In this study the effects of 213,561 electric vehicles on the operation of the single wholesale electricity market for the Republic of Ireland and Northern Ireland is investigated. A model of Ireland’s electricity market in 2020 is developed using the power systems market model called PLEXOS for power systems. The amount of CO2 emissions associated with charging the EVs and the impacts with respect to Ireland’s target for renewable energy in transport is also quantified. A single generation portfolio and two different charging scenarios, arising from a peak and off-peak charging profile are considered. Results from the study confirm that offpeak charging is more beneficial than peak charging and that charging EVs will contribute 1.45% energy supply to the 10% renewable energy in transport target. The net CO2 reductions are 147 and 210 kt CO2 respectively.

New SR drive with integrated charging capacity for plug-in hybrid electric vehicles (PHEVs)

Plug-in hybrid electric vehicles (PHEVs) provide much promise in reducing greenhouse gas emissions and, thus, are a focal point of research and development. Existing on-board charging capacity is effective but requires the use of several power conversion devices and power converters, which reduce reliability and cost efficiency. This paper presents a novel three-phase switched reluctance (SR) motor drive with integrated charging functions (including internal combustion engine and grid charging). The electrical energy flow within the drivetrain is controlled by a power electronic converter with less power switching devices and magnetic devices. It allows the desired energy conversion between the engine generator, the battery, and the SR motor under different operation modes. Battery-charging techniques are developed to operate under both motor-driving mode and standstill-charging mode. During the magnetization mode, the machine's phase windings are energized by the dc-link voltage. The power converter and the machine phase windings are controlled with a three-phase relay to enable the use of the ac-dc rectifier. The power converter can work as a buck-boost-type or a buck-type dc-dc converter for charging the battery. Simulation results in MATLAB/Simulink and experiments on a 3-kW SR motor validate the effectiveness of the proposed technologies, which may have significant economic implications and improve the PHEVs' market acceptance

New SR drive with integrated charging capacity for plug-in hybrid electric vehicles (PHEVs)

Plug-in hybrid electric vehicles (PHEVs) provide much promise in reducing greenhouse gas emissions and, thus, are a focal point of research and development. Existing on-board charging capacity is effective but requires the use of several power conversion devices and power converters, which reduce reliability and cost efficiency. This paper presents a novel three-phase switched reluctance (SR) motor drive with integrated charging functions (including internal combustion engine and grid charging). The electrical energy flow within the drivetrain is controlled by a power electronic converter with less power switching devices and magnetic devices. It allows the desired energy conversion between the engine generator, the battery, and the SR motor under different operation modes. Battery-charging techniques are developed to operate under both motor-driving mode and standstill-charging mode. During the magnetization mode, the machine's phase windings are energized by the dc-link voltage. The power converter and the machine phase windings are controlled with a three-phase relay to enable the use of the ac-dc rectifier. The power converter can work as a buck-boost-type or a buck-type dc-dc converter for charging the battery. Simulation results in MATLAB/Simulink and experiments on a 3-kW SR motor validate the effectiveness of the proposed technologies, which may have significant economic implications and improve the PHEVs' market acceptance.

Optimal Scheduling Methods to Integrate Plug-In Electric Vehicles with the Power System: A Review

The introduction of the Tesla in 2008 has demonstrated to the public of the potential of electric vehicles in terms of reducing fuel consumption and green-house gas from the transport sector. It has brought electric vehicles back into the spotlight worldwide at a moment when fossil fuel prices were reaching unexpected high due to increased demand and strong economic growth. The energy storage capabilities from of fleets of electric vehicles as well as the potentially random discharging and charging offers challenges to the grid in terms of operation and control. Optimal scheduling strategies are key to integrating large numbers of electric vehicles and the smart grid. In this paper, state-of-the-art optimization methods are reviewed on scheduling strategies for the grid integration with electric vehicles. The paper starts with a concise introduction to analytical charging strategies, followed by a review of a number of classical numerical optimization methods, including linear programming, non-linear programming, dynamic programming as well as some other means such as queuing theory. Meta-heuristic techniques are then discussed to deal with the complex, high-dimensional and multi-objective scheduling problem associated with stochastic charging and discharging of electric vehicles. Finally, future research directions are suggested.

Computational scheduling methods for integrating plug-in electric vehicles with power systems: a review

Traditional internal combustion engine vehicles are a major contributor to global greenhouse gas emissions and other air pollutants, such as particulate matter and nitrogen oxides. If the tail pipe point emissions could be managed centrally without reducing the commercial and personal user functionalities, then one of the most attractive solutions for achieving a significant reduction of emissions in the transport sector would be the mass deployment of electric vehicles. Though electric vehicle sales are still hindered by battery performance, cost and a few other technological bottlenecks, focused commercialisation and support from government policies are encouraging large scale electric vehicle adoptions. The mass proliferation of plug-in electric vehicles is likely to bring a significant additional electric load onto the grid creating a highly complex operational problem for power system operators. Electric vehicle batteries also have the ability to act as energy storage points on the distribution system. This double charge and storage impact of many uncontrollable small kW loads, as consumers will want maximum flexibility, on a distribution system which was originally not designed for such operations has the potential to be detrimental to grid balancing. Intelligent scheduling methods if established correctly could smoothly integrate electric vehicles onto the grid. Intelligent scheduling methods will help to avoid cycling of large combustion plants, using expensive fossil fuel peaking plant, match renewable generation to electric vehicle charging and not overload the distribution system causing a reduction in power quality. In this paper, a state-of-the-art review of scheduling methods to integrate plug-in electric vehicles are reviewed, examined and categorised based on their computational techniques. Thus, in addition to various existing approaches covering analytical scheduling, conventional optimisation methods (e.g. linear, non-linear mixed integer programming and dynamic programming), and game theory, meta-heuristic algorithms including genetic algorithm and particle swarm optimisation, are all comprehensively surveyed, offering a systematic reference for grid scheduling considering intelligent electric vehicle integration.

Real-Time Tariffs for Electric Vehicles in Wind Power based Power Systems

The use of Electric Vehicles (EVs) will change significantly the planning and management of power systems in a near future. This paper proposes a real-time tariff strategy for the charge process of the EVs. The main objective is to evaluate the influence of real-time tariffs in the EVs owners’ behaviour and also the impact in load diagram. The paper proposes the energy price variation according to the relation between wind generation and power consumption. The proposed strategy was tested in two different days in the Danish power system. January 31st and August 13th 2013 were selected because of the high quantities of wind generation. The main goal is to evaluate the changes in the EVs charging diagram with the energy price preventing wind curtailment.

Life-cycle analysis of energy and greenhouse gas emissions of automotive fuels in India: Part 2-Well-to-wheels analysis

In this second of the two-part study, the results of the Tank-to-Wheels study reported in the first part are combined with Well-to-Tank results in this paper to provide a comprehensive Well-to-Wheels energy consumption and greenhouse gas emissions evaluation of automotive fuels in India. The results indicate that liquid fuels derived from petroleum have Well-to-Tank efficiencies in the range of 75-85% with liquefied petroleum gas being the most efficient fuel in the Well-to-Tank stage with 85% efficiency. Electricity has the lowest efficiency of 20% which is mainly attributed due to its dependence on coal and 25.4% losses during transmission and distribution. The complete Well-to-Wheels results show diesel vehicles to be the most efficient among all configurations, specifically the diesel-powered split hybrid electric vehicle. Hydrogen engine configurations are the least efficient due to low efficiency of production of hydrogen from natural gas. Hybridizing electric vehicles reduces the Well-to-Wheels greenhouse gas emissions substantially with split hybrid configuration being the most efficient. Electric vehicles do not offer any significant improvement over gasoline-powered configurations; however a shift towards renewable sources for power generation and reduction in losses during transmission and distribution can make it a feasible option in the future. (C) 2015 Elsevier Ltd. All rights reserved.

Energy efficiency and greenhouse gas emissions of different supply chains: a comparison of French, UK and Belgian cases

Freight transportation system is critical to economic activity but it carries significant environmental costs, notably GHG emissions and climate change : energy use and corresponding CO2 emissions is increasing faster in freight transport than in other sectors and this increase is primarily the result of increased trade. This paper compares the transport activities, associated energy consumption and CO2 emissions of different supply chains for a range of products in three countries: Belgium, France and United Kingdom. Among the products considered are furniture and ‘fruits & vegetables’. For each of these products, different supply chains, involving more or less transport activity and associated energy consumption are analysed in each country. The comparison highlights some of the main factors that influence GHG emissions for different supply chains and illustrates how they vary according to product and country of final distribution. In more detail, the paper addresses the main differences between the supply chains of these products namely, the origin of their sourcing, the logistical organisation between production and retail and different types of retail outlet. The origin of the sourcing impact is mainly related to distance. The impact of the logistical organisation between raw material and retail on GHG emissions is linked to the mode and vehicle choice and to the load factor. As for retail, the consumer trip emissions, between his home and the retail outlet, are also an important part of the whole supply chain emissions. It is worthwhile to notice that our goal in this project is to consider the whole supply chain, from production to consumption. Therefore a particular focus is put on the mobility behaviours of consumers purchasing the studied products during their shopping and dropping back home activities related to these products. Especially a web based survey has been conducted and the gathered results offer an opportunity for drawing a more detailed picture of the associated CO2 emissions. This paper uses the results of an ongoing research on supply chain energy efficiency, funded by ADEME (the French Energy Agency) through the French program on transport research (PREDIT). This research is based on a comprehensive review of the various approaches to quantifying the environmental impacts of supply chains together with data collection from a range of organisations including manufacturers, retailers and transport companies. We will first present the developed methodologies, then the results corresponding to each studied product will be described. A discussion of the potential application of the research approach to the wider debate about the environmental impact of freight transport and the scope for GHG emissions reduction targets to be achieved will be included.

Energy efficiency and greenhouse gas emissions of different supply chains: a comparison of French, UK and Belgian cases

Freight transportation system is critical to economic activity but it carries significant environmental costs, notably GHG emissions and climate change : energy use and corresponding CO2 emissions is increasing faster in freight transport than in other sectors and this increase is primarily the result of increased trade. This paper compares the transport activities, associated energy consumption and CO2 emissions of different supply chains for a range of products in three countries: Belgium, France and United Kingdom. Among the products considered are furniture and fruits & vegetables. For each of these products, different supply chains, involving more or less transport activity and associated energy consumption are analysed in each country. The comparison highlights some of the main factors that influence GHG emissions for different supply chains and illustrates how they vary according to product and country of final distribution. In more detail, the paper addresses the main differences between the supply chains of these products namely, the origin of their sourcing, the logistical organisation between production and retail and different types of retail outlet. The origin of the sourcing impact is mainly related to distance. The impact of the logistical organisation between raw material and retail on GHG emissions is linked to the mode and vehicle choice and to the load factor. As for retail, the consumer trip emissions, between his home and the retail outlet, are also an important part of the whole supply chain emissions. It is worthwhile to notice that our goal in this project is to consider the whole supply chain, from production to consumption. Therefore a particular focus is put on the mobility behaviours of consumers purchasing the studied products during their shopping and dropping back home activities related to these products. Especially a web based survey has been conducted and the gathered results offer an opportunity for drawing a more detailed picture of the associated CO2 emissions. This paper uses the results of an ongoing research on supply chain energy efficiency, funded by ADEME (the French Energy Agency) through the French program on transport research (PREDIT). This research is based on a comprehensive review of the various approaches to quantifying the environmental impacts of supply chains together with data collection from a range of organisations including manufacturers, retailers and transport companies. We will first present the developed methodologies, then the results corresponding to each studied product will be described. A discussion of the potential application of the research approach to the wider debate about the environmental impact of freight transport and the scope for GHG emissions reduction targets to be achieved will be included.

Embodied Energy and Gas Emissions of Retaining Wall Structures

The embodied energy (EE) and gas emissions of four design alternatives for an embankment retaining wall system are analyzed for a hypothetical highway construction project. The airborne emissions considered are carbon dioxide (CO 2), methane (CH 4), nitrous oxide (N 2O), sulphur oxides (SO X), and nitrogen oxides (NO X). The process stages considered in this study are the initial materials production, transportation of construction machineries and materials, machinery operation during installation, and machinery depreciations. The objectives are (1) to determine whether there are statistically significant differences among the structural alternatives; (2) to understand the relative proportions of impacts for the process stages within each design; (3) to contextualize the impacts to other aspects in life by comparing the computed EE values to household energy consumption and car emission values; and (4) to examine the validity of the adopted EE as an environmental impact indicator through comparison with the amount of gas emissions. For the project considered in this study, the calculated results indicate that propped steel sheet pile wall and minipile wall systems have less embodied energy and gas emissions than cantilever steel tubular wall and secant concrete pile wall systems. The difference in CO 2 emission for the retaining wall of 100 m length between the most and least environmentally preferable wall design is equivalent to an average 2.0 L family car being driven for 6.2 million miles (or 62 cars with a mileage of 10,000 miles/year for 10 years). The impacts in construction are generally notable and careful consideration and optimization of designs will reduce such impacts. The use of recycled steel or steel pile as reinforcement bar is effective in reducing the environmental impact. The embodied energy value of a given design is correlated to the amount of gas emissions. © 2011 American Society of Civil Engineers.

Methodology To model the energy and greenhouse gas emissions of electronic software distributions

A new electronic software distribution (ESD) life cycle analysis (LCA)methodology and model structure were constructed to calculate energy consumption and greenhouse gas (GHG) emissions. In order to counteract the use of high level, top-down modeling efforts, and to increase result accuracy, a focus upon device details and data routes was taken. In order to compare ESD to a relevant physical distribution alternative,physical model boundaries and variables were described. The methodology was compiled from the analysis and operational data of a major online store which provides ESD and physical distribution options. The ESD method included the calculation of power consumption of data center server and networking devices. An in-depth method to calculate server efficiency and utilization was also included to account for virtualization and server efficiency features. Internet transfer power consumption was analyzed taking into account the number of data hops and networking devices used. The power consumed by online browsing and downloading was also factored into the model. The embedded CO2e of server and networking devices was proportioned to each ESD process. Three U.K.-based ESD scenarios were analyzed using the model which revealed potential CO2e savings of 83% when ESD was used over physical distribution. Results also highlighted the importance of server efficiency and utilization methods.

The Impact of office productivity cloud computing on energy consumption and greenhouse gas emissions

Cloud computing is usually regarded as being energy efficient and thus emitting less greenhouse gases (GHG) than traditional forms of computing. When the energy consumption of Microsoft’s cloud computing Office 365 (O365) and traditional Office 2010 (O2010) software suites were tested and modeled, some cloud services were found to consume more energy than the traditional form. The developed model in this research took into consideration the energy consumption at the three main stages of data transmission; data center, network, and end user device. Comparable products from each suite were selected and activities were defined for each product to represent a different computing type. Microsoft provided highly confidential data for the data center stage, while the networking and user device stages were measured directly. A new measurement and software apportionment approach was defined and utilized allowing the power consumption of cloud services to be directly measured for the user device stage. Results indicated that cloud computing is more energy efficient for Excel and Outlook which consumed less energy and emitted less GHG than the standalone counterpart. The power consumption of the cloud based Outlook (8%) and Excel (17%) was lower than their traditional counterparts. However, the power consumption of the cloud version of Word was 17% higher than its traditional equivalent. A third mixed access method was also measured for Word which emitted 5% more GHG than the traditional version. It is evident that cloud computing may not provide a unified way forward to reduce energy consumption and GHG. Direct conversion from the standalone package into the cloud provision platform can now consider energy and GHG emissions at the software development and cloud service design stage using the methods described in this research.

Global research alliance modelling platform (GRAMP): an open web platform for modelling greenhouse gas emissions from agro-ecosystems

Carbon (C) and nitrogen (N) process-based models are important tools for estimating and reporting greenhouse gas emissions and changes in soil C stocks. There is a need for continuous evaluation, development and adaptation of these models to improve scientific understanding, national inventories and assessment of mitigation options across the world. To date, much of the information needed to describe different processes like transpiration, photosynthesis, plant growth and maintenance, above and below ground carbon dynamics, decomposition and nitrogen mineralization. In ecosystem models remains inaccessible to the wider community, being stored within model computer source code, or held internally by modelling teams. Here we describe the Global Research Alliance Modelling Platform (GRAMP), a web-based modelling platform to link researchers with appropriate datasets, models and training material. It will provide access to model source code and an interactive platform for researchers to form a consensus on existing methods, and to synthesize new ideas, which will help to advance progress in this area. The platform will eventually support a variety of models, but to trial the platform and test the architecture and functionality, it was piloted with variants of the DNDC model. The intention is to form a worldwide collaborative network (a virtual laboratory) via an interactive website with access to models and best practice guidelines; appropriate datasets for testing, calibrating and evaluating models; on-line tutorials and links to modelling and data provider research groups, and their associated publications. A graphical user interface has been designed to view the model development tree and access all of the above functions.

National action plan for reducing greenhouse gas emissions : hearing before the Committee on Energy and Natural Resources, United States Senate, One Hundred Third Congress, first session ....

"October 28, 1993"--Pt. 2.