The air quality of Hong Kong (HK), especially at the street level, has been a matter of grave public concern. In 2007, road transport was reportedly the major source for emission of carbon monoxide (CO) and respirable suspended particulates (RSP), as well as the second largest source for emission of nitrogen oxides (NOx) and volatile organic compounds (VOC). The Government has taken various measures to curb roadside pollution. Recent technological breakthroughs in electric vehicles (EVs) have regenerated the Government's interest in promoting the wider use ofEVs. The main objectives ofthis paper are to examine whether road transport-related measures adopted by the Government have been effective in coping with the air pollution problem and whether the EV policy would improve the air quality ofHK. The Government has taken a more proactive approach, since 1999, in dealing with roadside pollution problems. The emission of all major air pollutants from road transport against the continuous growth in the numbers of vehicles and vehicle kilometers travelled reduced significantly between 1994 and 2007. The reduction of S02, RSP and CO in this time period was 95%, 70% and 59% respectively. Nonetheless, air pollution in HK remams an unresolved problem as reflected by continuous rising trends in the hours with poor visibility, days with roadside Air Pollution Index exceeding 100, and concentration of some air pollutants exceeding the Air Quality Objectives. EVs have zero tailpipe emission but its potential in improving the air quality has been skeptical because part of the emission may be transferred to the power plants. Through quantitative analysis, it was found that if all vehicles in HK were converted to EVs, the overall emission of NOx, RSP, CO and VOC would reduce by 77.3%, 89.9%, 99.4% and 99.4% respectively but that of S02 would suffer a regrettable 13.5-fold increase. It was concluded that the wider use of EVs should be beneficial to the air quality of HK but the potential benefits would depend on the number of vehicles to be converted and simultaneous measures to cut S02 emission at the power sources. A qualitative analysis was made on factors affecting the change of vehicles to EVs. It was found that consumer decisions on EV purchases are likely influenced by availability, choice of models, driving range, reliability, whole life costing, and adequacy of infra structural support. The use of greener fuel and surplus electricity generation capacity as a means to reduce emissions from power plants were also explored. The paper concludes by making recommendations to encourage use of EVs and to maximize its potential benefits. It is expected that the Goverrunent will play an important role in implementing EV-related policies and prioritizing measures to reap immediate benefits. / published_or_final_version / Transport Policy and Planning / Master / Master of Arts in Transport Policy and Planning

The availability of non-renewable fuels is decreasing and therefore the prices of both petrol and diesel has increased in recent years. As a result more and more chooses to invest in cars powered by alternative fuels and the focus has long been on electric vehicles. However, this means greater weight on utility companies around the world which now have to adjust to a higher demand. The purpose of this study is to investigate how a local network are affected by electric car chargers and be able to describe the degree to which a low-voltage can be loaded with electric car chargers for commercial and private use, in order to provide recommendations for the future dimension of the local networks. Few studies have been conducted regarding electric cars from a network and supply perspective, but have instead been focused on energy storage in the actual vehicle. Therefore, this study has been processed with an electricity grid perspective. The intent of the study has been answered by both a measurement and several simulations. The study is based on Karlstad’s local electrical network and the commercial charging station Tesla in Våxnäs, Karlstad. The parameters of power quality for which this study has taken into account are load of the transformers, load loss, power factor, efficiency, voltage levels, voltage drop and asymmetry. The methodological conditions have led to a result that can be used as a basis for an expansion of electric cars, big or small. The measurement was of great support to get an overall view of how the characteristics of a charging session appeared and how the quality parameters were affected during high as well as low power charging. Limitations within the simulation program have led to the calculations to carry out in a more extreme scenario when it comes to the load. A result since the simulation time for constant power was minimum one hour. Based on the measurement and simulations of the charging station for commercial use is dimensioned well to cope with the current use of electric vehicle charging. More municipalities should follow Karlstad’s example for the development of commercial charging stations. In the countryside great problems occurred, especially with voltage drop at an increased use of home chargers for electric cars. The same problems emerged in the city part of the network. The study also showed serious problems with asymmetry in the city. The report concluded, therefore, several recommendations for the future dimension of local networks for private homes, for example that the local network should be divided into multiple trails.

Successful development of the electric power grid of the future, hereinafter referred to as a smart grid, implicitly demands the capability to model the behavior, performance, and cost of distribution-level smart grid components. The modeling and simulation of such individual components, together with their overall interaction, will provide a foundation for the design and configuration of a smart grid. It is the primary intent of this thesis, to provide a basic insight into the energy transfer of various distribution-level components by modeling and simulating their dynamic behavior. The principal operations of a smart grid must be considered, including variable renewable generation, energy storage, power electronic interfaces, variable load, and plug-in electric vehicles. The methodology involves deriving the mathematical equations of components, and, using the MATLAB/Simulink environment, creating modules for each component. Ultimately, these individual modules may be connected together via a voltage interface to perform various analyses, such as the treatment of harmonics, or to acquire an understanding of design parameters such as capacity, runtime, and optimal asset utilization. / text

Recently, electric vehicles (EVs) have been gaining attention in passenger transportation due to their greater fuel economy and reduced greenhouse gas (GHG) emissions compared to conventional vehicles (CVs). The amount of GHG emissions reduction from EVs depends on the energy sources used to generate electricity. Wind is a clean, renewable energy source and EVs charged from wind-generated electricity do not produce any emissions. However, wind is variable in nature. This thesis examines the potential impact of EVs on reducing a jurisdiction’s vehicular GHG emissions using locally available wind-electricity. Four methods of charging EVs using wind-electricity are considered, with grid-electricity as a backup, and the overall well-to-wheels GHG emission reductions are discussed. The thesis includes a case study of Summerside. The results show that up to 68% of the EVs’ demands were met with wind-electricity, and Summerside’s vehicular GHG emissions were reduced by between 56% and 73% when compared to CVs.

This thesis (1) reports a new Dynamic Programming (DP) approach, and (2) reports a Real Time Control strategy to optimize the energy management of a Hybrid Electric Vehicle(HEV). Increasing environmental concerns and rise in fuel prices in recent years has escalated interest in fuel efficient vehicles from government, consumers and car manufacturers. Due to this, Hybrid electric vehicles (HEV) have gained popularity in recent years. HEV’s have two degrees of freedom for energy flow controls, and hence the performance of a HEV is strongly dependent on the control of the power split between thermal and electrical power sources. In this thesis backward-looking and forward-looking control strategies for two HEV architectures namely series and parallel HEV are developed. The new DP approach, in which the state variable is not discretized, is first introduced and a theoretical base is established. We then prove that the proposed DP produces globally optimal solution for a class of discrete systems. Then it is applied to optimize the fuel economy of HEV's. Simulations for the parallel and series HEV are then performed for multiple drive cycles and the improved fuel economy obtained by the new DP is compared to existing DP approaches. The results are then studied in detail and further improvements are suggested. A new Real Time Control Strategy (RTCS) based on the concept of preview control for online implementation is also developed in this thesis. It is then compared to an existing Equivalent Cost Minimization Strategy (ECMS) which does not require data to be known apriori. The improved fuel economy results of the RTCS for the series and parallel HEV are obtained for standard drive cycles and compared with the ECMS results

This thesis begins with a literature review focusing on electric vehicle (EV) applications. Systems used for steering, braking and energy storage are investigated, with specific concentration on torque control in various DC and AC motors commonly used in EVs. A final solution for a low range personal transportation EV in the form of a wheelchair is proposed. The theme for this thesis is motion control, focusing on a two axis (or two wheel drive) brushless DC hub motor (BLDCHM) EV, with torque and direction control tracking a user reference. The operation principle for a BLDCHM is documented and the dynamic and electrical equations derived. Simulation results for motor response under different load and speed conditions are compared to practical measurements. Current and torque control loops are designed, implemented and tuned on a single-axis test-bed with an induction motor (IM) load coupled via a torque transducer. A Texas Instrument DSP development kit is used for the control algorithm bench testing. The final control algorithm is then duplicated and expanded in simulation to form a dynamic two axis system for an electric wheelchair. It incorporates both motor drive and regenerative capabilities. After demonstrating two axis controls for BLDCHMs, a control algorithm is designed simulated and compared to traditional systems. The final solution focuses specifically on an intuitive response to the driver input whilst maintaining direction tracking, even when there is a difference in smoothness of the individual terrains traversed by the left and right wheels. In addition the motor drives are equipped with controllers that ensure regenerative braking in order to recover as much energy as possible when the wheelchair is commanded to decelerate. / M. Sc. Eng. University of KwaZulu-Natal, Durban 2014.

Driven by technical, economic and environmental benefits for different stakeholders in the power industry, the electric distribution system is currently undergoing a major paradigm shift towards having an increasing portion of its growing demand supplied via distributed generation (DG) units. As the number of DG units increase; microgrids can be defined within the electric distribution system as electric regions with enough generation to meet all or most of its local demand. A microgrid should be able to operate in two modes, grid-connected or islanded. The IEEE standard 1547.4 enumerates a list of potential benefits for the islanded microgrid operation. Such benefits include: 1) improving customers’ reliability, 2) relieving electric power system overload problems, 3) resolving power quality issues, and 4) allowing for maintenance of the different power system components without interrupting customers. These benefits motivate the operation of microgrid systems in the islanded mode. However the microgrid isolation from the main grid creates special technical challenges that have to be comprehensively investigated in order to facilitate a successful implementation of the islanded microgrid concept. Motivated by these facts, the target of this thesis is to introduce new analysis and operational control algorithms to tackle some of the challenges associated with the practical implementation of the islanded microgrid concept. In order to accomplish this target, this study is divided into four perspectives: 1) developing an accurate steady-state analysis algorithm for islanded microgrid systems, 2) maximizing the possible utilization of islanded microgrid limited generation resources, 3) allowing for the decentralized operation of islanded microgrid systems and 4) enabling the islanded microgrid operation in distribution systems with high penetration of plug-in electric vehicles (PEVs). First for the steady-state analysis of islanded microgrid systems, a novel and generalized algorithm is proposed to provide accurate power flow analysis of islanded microgrid systems. Conventional power flow tools found in the literature are generally not suitable for the islanded microgrid operating mode. The reason is that none of these tools reflect the islanded microgrid special philosophy of operation in the absence of the utility bus. The proposed algorithm adopts the real characteristics of the islanded microgrid operation; i.e., 1) Some of the DG units are controlled using droop control methods and their generated active and reactive power are dependent on the power flow variables and cannot be pre-specified; 2) The steady-state system frequency is not constant and is considered as one of the power flow variables. The proposed algorithm is generic, where the features of distribution systems i.e. three-phase feeder models, unbalanced loads and load models have been taken in consideration. The effectiveness of the proposed algorithm, in providing accurate steady-state analysis of islanded microgrid systems, is demonstrated through several case studies. Secondly, this thesis proposes the consideration of a system maximum loadability criterion in the optimal power flow (OPF) problem of islanded microgrid systems. Such consideration allows for an increased utilization of the islanded microgrid limited generation resources when in isolation from the utility grid. Three OPF problem formulations for islanded microgrids are proposed; 1) The OPF problem for maximum loadability assessment, 2) The OPF for maximizing the system loadability, and 3) The bi-objective OPF problem for loadability maximization and generation cost minimization. An algorithm to achieve a best compromise solution between system maximum loadability and minimum generation costs is also proposed. A detailed islanded microgrid model is adopted to reflect the islanded microgrid special features and real operational characteristics in the proposed OPF problem formulations. The importance and consequences of considering the system maximum loadability in the operational planning of islanded microgrid systems are demonstrated through comparative numerical studies. Next, a new probabilistic algorithm for enabling the decentralized operation of islanded microgrids, including renewable resources, in the absence of a microgrid central controller (MGCC) is proposed. The proposed algorithm adopts a constraint hierarchy approach to enhance the operation of islanded microgrids by satisfying the system’s operational constraints and expanding its loading margin. The new algorithm takes into consideration the variety of possible islanded microgrid configurations that can be initiated in a distribution network (multi-microgrids), the uncertainty and variability associated with the output power of renewable DG units as well as the variability of the load, and the special operational philosophy associated with islanded microgrid systems. Simulation studies show that the proposed algorithm can facilitate the successful implementation of the islanded microgrid concept by reducing customer interruptions and enhancing the islanded microgrid loadability margins. Finally, this research proposes a new multi-stage control scheme to enable the islanded microgrid operation in the presence of high PEVs penetration. The proposed control scheme optimally coordinates the DG units operation, the shedding of islanded microgrid power demand (during inadequate generation periods) and the PEVs charging/discharging decisions. To this end, a three-stage control scheme is formulated in order to: 1) minimize the load shedding, 2) satisfy the PEVs customers’ requirements and 3) minimize the microgrid cost of operation. The proposed control scheme takes into consideration; the variability associated with the output power of renewable DG units, the random behaviour of PEV charging and the special features of islanded microgrid systems. The simulation studies show that the proposed control scheme can enhance the operation of islanded microgrid systems in the presence of high PEVs penetration and facilitate a successful implementation of the islanded microgrid concept, under the smart grid paradigm.

There is an increasing interest in sustainability and a growing debate about environmental policy measures aiming at the reduction of green house gas emissions across di erent economic sectors worldwide. The transportation sector is one major greenhouse gas emitter which is heavily regulated to reduce its dependance on oil. These regulations along with the growing customer awareness about global warming has led vehicle manufacturers to seek di erent technologies to improve vehicle e ciencies and reduce the green house gases emissions while at the same time meeting customer's expectation of mobility and exibility. Plug-in hybrid electric vehicles (PHEV) is one major promising solution for a smooth transition from oil dependent transportation sector to a clean electric based sector while not compromising the mobility and exibility of the drivers. In the medium term, plug-in hybrid electric vehicles (PHEV) can lead to signi cant reductions in transportation emissions. These vehicles are equipped with a larger battery than regular hybrid electric vehicles which can be recharged from the grid. For short trips, the PHEV can depend solely on the electric engine while for longer journeys the alternative fuel can assist the electric engine to achieve extended ranges. This is bene cial when the use pattern is mixed such that and short long distances needs to be covered. The plug-in hybrid electric vehicles are well-suited for logistics since they can avoid the possible disruption caused by charge depletion in case of all-electric vehicles with tight time schedules. The use of electricity and fuel gives rise to a new variant of the classical vehicle routing with time windows which we call the plug-in hybrid electric vehicle routing problem with time windows (PHEVRPTW). The objective of the PHEVRPTW is to minimize the routing costs of a eet of PHEVs by minimizing the time they run on gasoline while meeting the demand during the available time windows. As a result, the driver of the PHEV has two decisions to make at each node: (1) recharge the vehicle battery to achieve a longer range using electricity, or (2) continue to the next open time window with the option of using the alternative fuel. In this thesis, we present a mathematical formulation for the plug-in hybrid-electric vehicle routing problem with time windows. We solve this problem using a Lagrangian relaxation and we propose a new tabu search algorithm. We also present the rst results for the full adapted Solomon instances.

This thesis focuses on the feasibility of designing a commercial hybrid electric vehicle (HEV). In this work, relevant system models are developed for the vehicle including powertrain, braking system, electrical machines and battery. Based on these models ten different HEV configurations are assembled for detailed assessment of fuel consumption. This thesis also proposes a smart power management strategy which could be applied to any kind of HEV configuration. The suggested expert system deals with the external information about the driving conditions and modes of the driver as well as the internal states of the internal combustion engine efficiency and the state of charge of the battery, and decides on the power distribution between two different power supplies based on the predefined algorithms. The study illustrates the characteristics of the powertrain components for various HEV configurations. The work also shows the power flow of HEV configurations with the developed smart power management system and therefore, the effectiveness of power management strategies has been evaluated in detail.

Thesis (M.S.) -- Mississippi State University. Department of Electrical and Computer Engineering. / Title from title screen. Includes bibliographical references.