Greenhouse gas emissions from ships in ports – Case studies in four continents

Emissions of GHG from the transport sector and how to reduce them are major challenges for policy makers. The purpose of this paper is to analyse the level of greenhouse gas (GHG) emissions from ships while in port based on annual data from Port of Gothenburg, Port of Long Beach, Port of Osaka and Sydney Ports. Port call statistics including IMO number, ship name, berth number and time spent at berth for each ship call, were provided by each participating port. The IMO numbers were used to match each port call to ship specifications from the IHS database Sea-web. All data were analysed with a model developed by the IVL Swedish Environmental Research Institute for the purpose of quantifying GHG emissions (as CO₂-equivalent) from ships in the port area. Emissions from five operational modes are summed in order to account for ship operations in the different traffic areas. The model estimates total GHG emissions of 150,000, 240,000, 97,000, and 95,000 tonnes CO₂ equivalents per year for Gothenburg, Long Beach, Osaka, and Sydney, respectively. Four important emission-reduction measures are discussed: reduced speed in fairway channels, on-shore power supply, reduced turnaround time at berth and alternative fuels. It is argued that the potential to reduce emissions in a port area depends on how often a ship revisits a port: there it in general is easier to implement measures for high-frequent liners. Ships that call 10 times or less contribute significantly to emissions in all ports.     

船用伙食冷库自控系统的改造设计

文章针对早期船用伙食冷库以继电器为主导的控制系统所存在的问题,以某一滚装客船冷库为例,根据该冷库的运行技术特点,开发出以西门子s7系列可编程控制器为核心的自动控制系统,满足了冷库运行过程的精确掌控、节约耗能和可靠性等要求。     

Transport energy consumption in mountainous roads. A comparative case study for internal combustion engines and electric vehicles in Andorra

This paper analyses transport energy consumption of conventional and electric vehicles in mountainous roads. A standard round trip in Andorra has been modelled in order to characterise vehicle dynamics in hilly regions. Two conventional diesel vehicles and their electric-equivalent models have been simulated and their performances have been compared. Six scenarios have been simulated to study the effects of factors such as orography, traffic congestion and driving style. The European fuel consumption and emissions test and Artemis urban driving cycles, representative of European driving cycles, have also been included in the comparative analysis. The results show that road grade has a major impact on fuel economy, although it affects consumption in different levels depending on the technology analysed. Electric vehicles are less affected by this factor as opposed to conventional vehicles, increasing the potential energy savings in a hypothetical electrification of the car fleet. However, electric vehicle range in mountainous terrains is lower compared to that estimated by manufacturers, a fact that could adversely affect a massive adoption of electric cars in the short term.     

The load-dependent vehicle routing problem and its pick-up and delivery extension

The present paper examines a Vehicle Routing Problem (VRP) of major practical importance which is referred to as the Load-Dependent VRP (LDVRP). LDVRP is applicable for transportation activities where the weight of the transported cargo accounts for a significant part of the vehicle gross weight. Contrary to the basic VRP which calls for the minimization of the distance travelled, the LDVRP objective is aimed at minimizing the total product of the distance travelled and the gross weight carried along this distance. Thus, it is capable of producing sensible routing plans which take into account the variation of the cargo weight along the vehicle trips. The LDVRP objective is closely related to the total energy requirements of the vehicle fleet, making it a credible alternative when the environmental aspects of transportation activities are examined and optimized. A novel LDVRP extension which considers simultaneous pick-up and delivery service is introduced, formulated and solved for the first time. To deal with large-scale instances of the examined problems, we propose a local-search algorithm. Towards an efficient implementation, the local-search algorithm employs a computational scheme which calculates the complex weighted-distance objective changes in constant time. Solution results are presented for both problems on a variety of well-known test cases demonstrating the effectiveness of the proposed solution approach. The structure of the obtained LDVRP and VRP solutions is compared in pursuit of interesting conclusions on the relative suitability of the two routing models, when the decision maker must deal with the weighted distance objective. In addition, results of a branch-and-cut procedure for small-scale instances of the LDVRP with simultaneous pick-ups and deliveries are reported. Finally, extensive computational experiments have been performed to explore the managerial implications of three key problem characteristics, namely the deviation of customer demands, the cargo to tare weight ratio, as well as the size of the available vehicle fleet.     

Life cycle assessment of heated apron pavement system operations

Heated pavement systems (HPS) offer an attractive alternative to the cumbersome process of removing ice and snow from airport pavements using traditional snow removal systems. Although snow and ice removing efficiency and economic benefits of HPS have been assessed by previous studies, their environmental impact is not well known. Airport facilities offering public or private services need to evaluate the energy consumption and global warming potential of different types of snow and ice removal systems. Energy usage and emissions from the operations of hydronic heated pavement system using geothermal energy (HHPS-G), hydronic HPS using natural gas furnace (HHPS-NG), electrically heated pavement system (EHPS), and traditional snow and ice removal system (TSRS) are estimated and compared in this study using a hybrid life cycle assessment (LCA). Based on the system models assessed in this study, HPS application in the apron area seems to be a viable option from an energy or environmental perspective to achieve ice/snow free pavement surfaces without using mechanical or chemical methods. TSRS methods typically require more energy and they produce more greenhouse gas (GHG) emissions compared to HPS during the operation phase, under the conditions and assumptions considered in this study. Also, HPS operations require less energy and have less GHG emissions during a snow event with a smaller snowfall rate and a larger snow duration.     

A driver advisory system with dynamic losses for passenger electric multiple units

Driver advisory systems, instructing the driver how to control the train in an energy efficient manner, is one the main tools for minimizing energy consumption in the railway sector. There are many driver advisory systems already available in the market, together with significant literature on the mathematical formulation of the problem. However, much less is published on the development of such mathematical formulations, their implementation in real systems, and on the empirical data from their deployment. Moreover, nearly all the designed driver advisory systems are designed as an additional hardware to be added in drivers’ cabin. This paper discusses the design of a mathematical formulation and optimization approach for such a system, together with its implementation into an Android-based prototype, the results from on-board practical experiments, and experiences from the implementation. The system is based on a more realistic train model where energy calculations take into account dynamic losses in different components of the propulsion system, contrary to previous approaches. The experimental evaluation shows a significant increase in accuracy, as compared to a previous approach. Tests on a double-track section of the Mälaren line in Sweden demonstrates a significant potential for energy saving.     

Layout optimization of an inertial energy harvester for miniature underwater mooring platforms

Comprehensive analyses of the layout influence on power performance of a low-frequency miniature horizontal-pendulum-type inertial energy harvester for underwater mooring platforms are presented in this article. The mathematical models are obtained utilizing the Newton-Euler method. The power performance is evaluated by simulations over different parameters, such as damping, excitation frequency, and layout position. Simulation results indicate that the harvester can extract energy from low-frequency excitations over the range of 0.1 Hz–0.4 Hz, and maximum output power can reach to 0.7 W under excitation frequency f = 0.4 Hz. Different layout positions influence the energy harvesting performance of the harvester dramatically. Changing the layout position to positive value can enhance and broaden the power performance. The amplitude responses with different layout positions do not show resonant characteristics, even near the natural frequency of the harvester, due to large amplitude vibrations and strong nonlinear characteristic. As excitation frequency f = 0.4 Hz, there is a zero output power point appears at layout position d = −1.3 m. Moreover, the harnessed power has a quadratic relationship with the layout position value.     

Distributed MPC for cooperative highway driving and energy-economy validation via microscopic simulations

Traffic congestion and energy issues have set a high bar for current ground transportation systems. With advances in vehicular communication technologies, collaborations of connected vehicles have becoming a fundamental block to build automated highway transportation systems of high efficiency. This paper presents a distributed optimal control scheme that takes into account macroscopic traffic management and microscopic vehicle dynamics to achieve efficiently cooperative highway driving. Critical traffic information beyond the scope of human perception is obtained from connected vehicles downstream to establish necessary traffic management mitigating congestion. With backpropagating traffic management advice, a connected vehicle having an adjustment intention exchanges control-oriented information with immediately connected neighbors to establish potential cooperation consensus, and to generate cooperative control actions. To achieve this goal, a distributed model predictive control (DMPC) scheme is developed accounting for driving safety and efficiency. By coupling the states of collaborators in the optimization index, connected vehicles achieve fundamental highway maneuvers cooperatively and optimally. The performance of the distributed control scheme and the energy-saving potential of conducting such cooperation are tested in a mixed highway traffic environment by the means of microscopic simulations.     

Energy-aware control for automated container terminals using integrated flow shop scheduling and optimal control

The performance of container terminals needs to be improved to handle the growth of transported containers and maintain port sustainability. This paper provides a methodology for improving the handling capacity of an automated container terminal in an energy-efficient way. The behavior of a container terminal is considered as consisting of a higher level and a lower level represented by discrete-event dynamics and continuous-time dynamics, respectively. These dynamics represent the behavior of a large number of terminal equipment. The dynamics need to be controlled. For controlling the higher level dynamics, a minimal makespan problem is solved. For this, the minimal time required by equipment for performing an operation at the lower level is needed. The minimal time for performing an operation at the lower level is obtained using Pontryagin’s Minimum Principle. The actual operation time allowed by the higher level for processing an operation at the lower level is subsequently determined by a scheduling algorithm at the higher level. Given an actual operation time, the lower level dynamics are controlled using optimal control to achieve minimal energy consumption while respecting the time constraint. Simulation studies illustrate how energy-efficient management of equipment for the minimal makespan could be obtained using the proposed methodology.