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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 conducted 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. [ABSTRACT FROM AUTHOR]

SUMMARY: In this paper, a hybrid model of fuzzy clustering and ANN (Artificial Neural Network) is proposed for electricity price forecasting. Due to the complicated behavior of electricity price in power markets, market players are interested in maximizing profits while minimizing risks. As a result, more accurate models are required to deal with electricity price forecasting. This paper proposes a new method that makes use of fuzzy clustering preconditioned GRBFN (Generalized Radial Basis Function Network) to provide more accurate predicted prices. Fuzzy clustering plays a key role to prevent the number of learning data from decreasing at each cluster. GRBFN is one of efficient ANNs to approximate nonlinear systems. Furthermore, a modified GRBFN model is developed to improve the performance of GRBFN with the use of DA (Deterministic Annealing) clustering for the parameters initialization and EPSO (Evolutionary Particle Swarm Optimization) for optimizing the parameters of GRBFN. The proposed method is successfully applied to real data of ISO New England, USA. [ABSTRACT FROM AUTHOR]

In recent years, the smart inverter that is an advanced inverter has been investigated as a solution to voltage problem in the distribution network in which a lot of photovoltaic(PV)s are introduced Among multiple functions of the smart inverter, voltage‐reactive power control (Volt‐Var) and voltage‐active power control (Volt‐Watt) have been attracted attention because of their effectiveness. However, the problem is how to determine optimal curves setting of Volt‐Var and Volt‐Watt. In this paper, we suggest the determination method of optimal Volt‐Var and Volt‐Watt curves, and verify the effectiveness of the optimal curves on distribution network. [ABSTRACT FROM AUTHOR]

SUMMARY Factory power generation plants supply electric power and heat to manufacturing lines. Because demand changes are uncertain, the power plant must adjust its output to match the demand and to avoid violation of constraints such as inverse load flow. Conventionally, these violations have been avoided by purchasing surplus electric power. However, surplus power raises the energy cost. There exists an optimization method that considers uncertainty in demands for cogeneration systems, and uses a triangle function to approximate the probability distribution. However, this method does not consider the tail of the probability distribution. In this paper we propose an operation optimization method considering an uncertainty in the demands for factory power plants. The proposed method aims to avoid violation of constraints and to reduce energy cost. Through simulation experiments, we confirm the validity of the proposed method. [ABSTRACT FROM AUTHOR]

This paper deals with estimation of total output of solar photovoltaic (PV) generators widely distributed in future power systems. In the proposed framework of estimation, the estimated signal in each frequency band is a linear combination of observed signals. The observation gain for each observed signal in each frequency band is designed through following two steps. First, an estimation error function is defined using assumed root mean square of output of PVs, predicted distribution of future PVs in the area, and correlation coefficients, which are identified in advance based on actual synchronized measurements of PVs. Second, observation gain in each frequency band is designed so as to minimize the estimation error function. The appropriateness of the proposed framework of estimation is demonstrated in small- and large-scale examples. [ABSTRACT FROM AUTHOR]

This paper presents a new form of Particle Swarm Optimization (PSO) based on the concept of tabu search (TS). In PSO, when a particle finds a local optimal solution, all of the particles gather around that one, and cannot escape from it. On the other hand, TS can escape from the local optimal solution by moving away from the best present solution. The proposed Tabu List PSO (TL-PSO) is a method for combining the strong points of PSO and TS. This method stores the history of pbest in a tabu list. When a particle has a reduced searching ability, it selects a pbest of the past from the historical values, which is used for the update. This makes each particle active, and the searching ability of the swarm makes progress. The proposed method was validated by numerical simulations with several functions that are well known as optimization benchmark problems for comparison to the conventional PSO method. © 2010 Wiley Periodicals, Inc. Electr Eng Jpn, 172(4): 31–37, 2010; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.20966 [ABSTRACT FROM AUTHOR]

In order to carry out energy saving service, it is indispensable to calculate the energy saving effect quantitatively by presuming the energy cost at the time of not executing the energy saving measure. However, it is difficult because the energy cost changes when environment (energy demand, unit prices of fuel or electric power, and so on) changes even if an energy saving measure is not executed. Although the effect has been conventionally evaluated by the difference between the energy costs before and after the energy saving measure, the effect cannot be calculated correctly when there is environmental change. In this paper, we propose the method of estimating the energy saving effect by presuming the energy cost after an energy saving measure, assuming that the measure is not executed, and show the results of its application to the practical power plants. © 2009 Wiley Periodicals, Inc. Electr Eng Jpn, 168(4): 14–20, 2009; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.20880 [ABSTRACT FROM AUTHOR]

In this paper, we present the development of interior magnet motors reducing iron loss at high rotational speed under the flux weakening control. The rotor core and magnet shapes are determined by the automatic numerical calculation using combination of the optimization method and the adaptive finite element method. The optimized motor is manufactured to prove the effectiveness by the measurement of the iron loss. Both results of the calculation and the measurement indicate that the iron loss of the proposed motor at the high rotational speed under the flux weakening control is reduced by half compared with the initial rotor shape while the torque is nearly constant. © 2009 Wiley Periodicals, Inc. Electr Eng Jpn, 168(3): 59–66, 2009; Published online in Wiley InterScience (www.interscience. wiley.com). DOI 10.1002/eej.20827 [ABSTRACT FROM AUTHOR]

According to recent understanding of brain science, it is suggested that there is a distribution of functions in the brain, which means that different neurons are activated depending on which sort of sensory information the brain receives. We have already developed a learning network with a function distribution which is called the Learning Petri Network (LPN) and have shown that this network could learn nonlinear and discontinuous mappings which the Neural Network (NN) cannot. In this paper, a more realistic application which has dynamic characteristics is studied. From simulation results of a nonlinear crane control system using LPN controller, it is clarified that the control performance of LPN controller is superior to that of NN controller. © 2000 Scripta Technica, Electr Eng Jpn, 131(3): 58-69, 2000 [ABSTRACT FROM AUTHOR]

Carbon emissions which would cause global warming were agreed to be constrained at COP3 in Kyoto. In addition, carbon emission permits trading was also approved to be introduced. The emission permits trading is expected to achieve efficient carbon emission reduction, equalizing the marginal costs of the emission reduction for the participating countries. In other words, the permits trading allows participants to reduce emissions where it is least expensive to do so. However, the inadequate introduction of the trading systems may impose an unfairly greater burden on some countries, and therefore careful evaluation of the system would be indispensable for its implementation. In this paper, we attempt to analyze emission permits trading, using the theory of cooperative games with a global energy model of optimization type. We assume that seven world regions as players participate in the permits trading system under the condition of the emission reduction target presented at COP3 and so on, and show the nucleolus of the grand coalition games, and the computational results of primary energy supplies and CO2 shadow prices. The insights of this research indicate that in order to stabilize the grand coalition, a noticeable amount of additional transfer of money would be needed besides the payments associated with the emission permits transactions. © 2000 Scripta Technica, Electr Eng Jpn, 131(2): 40–50, 2000 [ABSTRACT FROM AUTHOR]

Recent steady increase of electric power demand causes power sources to be large and far from cities. Wide area power interchanges lead to larger and more complex power systems. This makes the network susceptible to poor damping power swing oscillations of relatively low frequencies which influence the whole system. This paper describes a newly developed generator's double input signal PSS (P+ ω input PSS) design method. Several power system conditions (power flow and/or power patterns) are considered to satisfy a well-stabilized power system for each system condition. Major features of this method are: (1) Weighting factor for eigenvalue sensitivity of the oscillation mode is considered when the parameters of the PSS are updated during the optimization process. (2) The new method provides good results for the generator's local and interarea oscillation modes under peak and off-peak power flow conditions. © 2000 Scripta Technica, Electr Eng Jpn, 131(1): 19–31, 2000 [ABSTRACT FROM AUTHOR]

For EDS-type magnetically levitated trains, magnetic shielding of stray fields produced by superconducting magnets is an important task. We seek the “optimal” thickness distribution (configuration) of magnetic material, which is the lightest and keeps the magnetic field at tolerable levels in the vehicle. In many cases, trial-and-error methods have been adopted for this purpose. In this paper, we propose a new method for preliminary design of the magnetic shielding. In this method, we simplify the magnetic shielding problem, assuming infinite permeability of the magnetic material, and calculate the magnetic flux going into or out of the shield surface. In this case, we can design an optimal magnetic shield (distribution and configuration of the magnetic material) and know the minimum weight of the magnetic shielding. We finally present an example of the magnetic shielding designed by this method and investigate its characteristics in a magnetically levitated train. © 1998 Scripta Technica, Electr Eng Jpn, 124(1): 42–54, 1998 [ABSTRACT FROM AUTHOR]

To improve energy consumption and to meet quality requirements for the slab heating process of reheat furnaces in hot strip mills, a new optimal slab heat pattern calculation simulator has been developed. The simulator consists of the following functions; (1) two-dimensional (slab thickness direction and slab length direction) slab temperature calculation function, which is capable of calculating skidmarks along the length of a slab, (2) furnace heat balance calculation function, (3) optimizing calculation function of slab heat pattern using a linear programming method. The simulator developed has been installed into a furnace computer control system for an actual plant. This paper describes the functions of the simulator and simulation results using the simulator. © 1997 Scripta Technica, Inc. Electr Eng Jpn, 120(3): 42–53, 1997 [ABSTRACT FROM AUTHOR]

This paper describes an optimal load-shedding method which can be applied to local buses in order to suppress voltage deviations, based on local information obtained at each bus. When a generation outage occurs, adequate amounts of loads must be shed within a few seconds in order to maintain the balance between supply and demand. This method is able to decide quickly the optimal amounts of loads to be shed after the fault. The proposed method is based on the fact that the location of the fault can be estimated exclusively from power flow deviations at local buses, measured after the outage. Because the amounts of load to be shed have constraints, it is necessary to find the optimal factors which decide the amounts of load-shedding at each bus by quadratic programming. To solve this problem we first linearize the study system. Next, in order to relate power flows to voltage deviations at each bus, the voltage sensitivity factors obtained by ac power flow calculation are evaluated. Numerical simulations with 4-machine and 9-machine power system models show the effectiveness of the proposed method. It distributes adequate loads which are almost identical to the completely optimized loads, and it produces smaller voltage deviations than the conventional method. Improved transient characteristics of voltage deviations are also demonstrated. © 1997 Scripta Technica, Inc. Electr Eng Jpn 119(1): 35–44, 1997 [ABSTRACT FROM AUTHOR]

This paper proposes a new method of optimizing the operation of a power transmission system, based on a structured neural network. Because the structured neural network is built by prewiring, the network construction time is very short. Simulations of transmission loss of reduction have been carried out. It is shown that the optimization performance of the proposed method is satisfactory in practice. © 1997 Scripta Technica, Inc. Electr Eng Jpn. 118 (4): 27–34, 1997 [ABSTRACT FROM AUTHOR]

This paper describes an optimal load-shedding policy based on quadratic programming using only some power system state variables after severe generation outages. When generation outage is severe, the imbalance between supply and demand causes a declining frequency. Utilities generators cannot be operated excessively at frequencies above normal. Some of the load must be shed to prevent system damage. Optimal load-shedding policies have been studies using all state variables of the power system. However, in real power system operations, it is difficult to obtain remote information in that fraction of a second following generation outages. An optimal load-shedding method is constructed in this research using quadratic programming (QP) under the assumption that all power system state variables can be available. However, these state variables cannot be easily accessible (as already mentioned). A suboptimal load-shedding scheme based on the local state variables is then studied. The proposed load-shedding method is based on the aforementioned optimal one. The change in line-power flows and the amount of generation power outage are used as accessible data at each load point. Incorporating this local information into the optimal load-shedding method based on the QP method, the proposed load-shedding method is established here. The effectiveness of this proposed method is illustrated by two examples and simulation results on a model power system show that the method is encouraging. [ABSTRACT FROM AUTHOR]

SUMMARY This paper investigates the impact of an extensive introduction of electric vehicles ( EV) and plug-in hybrid vehicles ( PHEV) into the global energy system by 2050. The significant growth of automobile ownership in emerging countries is likely to increase world oil demand and the associated carbon dioxide emissions. In order to address these energy, security, and environmental concerns, the deployment of clean energy vehicles, such as EV and PHEV, is expected to play a crucial role due to their high fuel efficiency. Consequently, we develop both a global energy system model and a world vehicle penetration model, which can explicitly analyze the impact of EV introduction into the seasonal daily electric load curve, with consideration of the specific electricity charging profile through 2050. The simulation results confirm that EV deployment contributes to energy conservation, because oil demand reduction outstrips the growth in electricity demand and the associated fuel input into the power generation mix. Concerning carbon dioxide abatement, the magnitude of the impact relies on the carbon intensity of the power generation mix. If the intensity is low enough to guarantee a carbon mitigation effect due to EV fuel saving, emissions reduction is well assured. It should be noted, however, that in regions with high carbon intensity in the power generation mix, carbon emissions per mileage of EVs is almost equivalent to that of efficient gasoline vehicles such as hybrid vehicles, and the figure for PHEV is slightly higher than for hybrid vehicles. © 2013 Wiley Periodicals, Inc. Electr Eng Jpn, 186(4): 20-36, 2014; Published online in Wiley Online Library (wileyonlinelibrary.com). DOI 10.1002/eej.22373 [ABSTRACT FROM AUTHOR]

SUMMARY: It has become desirable to develop energy control technologies for environmental issues such as global warming and exhaustion of fossil fuel. Power fluctuations in large power consumer facilities may cause instability of electric power systems and increase the cost of the electric power facilities and electricity charges. Developing electric power leveling systems (EPLS) to compensate power fluctuations is necessary for future electric power systems. EPLS with an SMES has been proposed as one countermeasure for use in electric power quality improvement. SMES is superior to other energy storage devices in response and storage efficiency. The authors have proposed EPLS based on fuzzy control with SMES. For this practical implementation, optimizing the control gain and SMES capacity is an important issue. This paper proposes a new method for optimization of the EPLS. The proposed algorithm is a novel particle swarm optimization based on taper‐off reflectance (TRPSO). The proposed TRPSO optimizes the design variables of the EPLS efficiently and effectively. © 2013 Wiley Periodicals, Inc. Electr Eng Jpn, 186(3): 10–18, 2014; Published online in Wiley Online Library ( wileyonlinelibrary.com). DOI 10.1002/eej.22472 [ABSTRACT FROM AUTHOR]