Masafumi Miyatake

The energy consumption of a battery-powered train in an interstation depends on the running time and state of energy (SOE) at departure. In this paper, we develop an optimization method of train timetables to minimize energy consumption in line with several stations. The variables in this proposed optimization model are running, dwell, and charging times as real numbers and places of charging facilities as binaries. Additionally, we conduct a case study using the real-world light rail transit (LRT) route, vehicle, and onboard battery model to confirm the effectiveness. In the case study, the proposed method can optimize the timetable and placement of charging facilities by considering the track gradient and battery SOE.

The timetable of urban rail greatly affects its daily energy consumption. To improve the utilization of renewable energy between trains using timetabling has become an effective way to reduce energy consumption. Previous studies ignore or simplify the modelling of traction power supply network, which failed to accurately describe the flow of energy between trains through the power network. This paper proposed an optimisation method of energy efficiency timetabling considering the power flow of traction power supply network. First, an urban rail transit DC traction network model is established, and the current-vector iterative method is used to characterize the energy consumption. Then, a train timetable optimisation model is proposed to minimize the total energy consumption of the traction network system by adjusting the dwell time and section running time. The genetic algorithm is used to solve the optimisation problem. Finally, simulation result shows that the proposed method can accurately characterize the energy flow and effectively reduce the total energy consumption of the urban rail transit.

In dense traffic railway networks, trains may often slow down or stop between stations owing to previous train delays. If preceding train trajectory can be predicted, energy-efficient driving can be achieved by suppressing unnecessary speed changes. In this paper, we propose an algorithm to find energy-efficient driving considering fixed-block signalling (FBS) system by using dynamic programming (DP). DP is suitable for use because it can optimize the control inputs with discrete and state constraints. In this paper, we discuss energy-efficient driving by considering a FBS system using some case studies of simulation. In the simulation, we examine a technique to drive an express train in an energy-efficient way when the preceding local train is running toward the station with passing loops. The results show that the proposed method can derive complex speed profiles for energy-efficient driving and the train can be operated with a maximum reduced energy consumption of 8.3%.

Multiple photovoltaic (PV) modules feeding a common load is the most common form of power distribution used in solar PV systems. In such systems, providing individual maximum power point tracking (MPPT) schemes for each of the PV modules increases the cost. Furthermore, its v-i characteristic exhibits multiple local maximum power points (MPPs) during partial shading, making it difficult to find the global MPP using conventional single-stage (CSS) tracking. To overcome this difficulty, the authors propose a novel MPPT algorithm by introducing a particle swarm optimization (PSO) technique. The proposed algorithm uses only one pair of sensors to control multiple PV arrays, thereby resulting in lower cost, higher overall efficiency, and simplicity with respect to its implementation. The validity of the proposed algorithm is demonstrated through experimental studies. In addition, a detailed performance comparison with conventional fixed voltage, hill climbing, and Fibonacci search MPPT schemes are presented. Algorithm robustness was verified for several complicated partial shading conditions, and in all cases this method took about 2 s to find the global MPP.

In this paper, the author proposes a simple comprehensive mathematical formulation for considering energy-saving train scheduling. The formulation is to optimize running time for each section between stations with fixing total time between origin and destination of a train. The model was demonstrated numerically with a simple railway line model with four stations and three sections. The result showed that optimal condition and energy saving effect could be evaluated easily. © 2011 The Institute of Electrical Engineers of Japan.

The optimal operation of railway systems minimizing total energy consumption is discussed in this paper Firstly, some measures of finding energy-saving train speed profiles are outlined After the characteristics that should be considered in optimizing train operation are clarified. complete optimization based on optimal control theory is reviewed Then basic formulations are summarized taking into account most of the difficult characteristics peculiar to railway systems Three methods of solving the formulation. dynamic programming (DP). gradient method. and sequential quadratic programming (SQP). are introduced The last two methods can also control the state of charge (SOC) of the energy storage devices By showing some numerical results of simulations. the significance of solving not only optimal speed profiles but also optimal SOC profiles oh energy storage are emphasized. because the numerical results are beyond the conventional qualitative studies Rutile scope for applying the methods to real-time optimal control is also mentioned (C) 2010 Institute of Electrical Engineers of Japan Published by John Wiley & Sons, Inc

In this paper a hybrid energy system combining variable speed wind turbine, solar photovoltaic and fuel cell generation systems is presented to supply continuous power to residential power applications as stand-alone loads. The wind and photovoltaic systems are used as main energy sources while the fuel cell is used as secondary or back-up energy source. Three individual dc-dc boost converters are used to control the power flow to the load. A simple and cost effective control with dc-dc converters is used for maximum power point tracking and hence maximum power extracting from the wind turbine and the solar photovoltaic systems. The hybrid system is sized to power a typical 2 kW/150 V dc load as telecommunication power plants or ac residential power applications in isolated islands continuously throughout the year. The results show that even when the sun and wind are not available; the system is reliable and available and it can supply high-quality power to the load. The simulation results which proved the accuracy of the proposed controllers are given to demonstrate the availability of the proposed system in this paper. Also, a complete description of the management and control system is presented. (C) 2008 Elsevier Ltd. All rights reserved.