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This study presents a method for high-impedance fault (HIF) detection in a low-voltage DC (LVDC) distribution system via mathematical morphology (MM), which is composed of two elementary transformations, namely, dilation and erosion. Various MM-based filters are used to detect abnormal signals of current waveform. The LVDC distribution system, including power conversion devices, such as AC/DC and DC/DC converters, is modelled with electromagnetic transient program (EMTP) software to verify the proposed method. The HIF arc model in the DC system is also implemented with EMTP/MODELS, which is a symbolic language interpreter for EMTP. Simulation results show that the proposed method can be applied to detect HIF effectively in the LVDC distribution system. [ABSTRACT FROM AUTHOR]

For the size reduction of high voltage (HV) power apparatus, the electric field stress around solid insulators is to be considered carefully. The application of nanoporous composite insulator with lower permittivity will be an effective solution. This paper attempts to show the effective porous-structure of the nanoporous-alumina composite insulator for gas insulated switchgears (GIS) solid spacer by using numerical analysis. Finite element analysis indicates that the reduction of triple junction (TJ) field stress by more than 15% requires the relative permittivity of less than 4.7 in nanoporous- alumina composite insulator. From the dielectric mixture formula, it is estimated that effective permittivity of less than 4.7 of nanoporous-alumina composite insulator required the particle porosity of more than 15%. Based on the Paschen's law, it is estimated that the discharge inception field of a nanopore with a size of less than 0.02 μm could be higher than the dielectric breakdown strength of epoxy composite material, that is, the nanoporous-alumina composite insulator with a nanopore size of less than 0.02 μm could have the voltage-endurance. [ABSTRACT FROM AUTHOR]

Photovoltaic (PV) systems are rapidly gaining acceptance as some of the best alternative energy sources. In the installation area of a large PV system, appropriate operation is required, for example, of a method considering power output fluctuation and solar radiation forecast errors. In addition, it is better to minimise the size of the battery and its capital cost. This paper proposes an optimisation approach to determine the operational planning of the power output for a large PV system. This approach includes the method of determination of the charge/discharge amount for the battery of an electric vehicle as a demand response. The method aims to obtain a more beneficial deal with the sale of electrical power. The optimisation method applies the genetic algorithm to smoothen the fluctuating power output due to the PV system, and also to determine the initial state of charge of the battery. The validity of the proposed method is confirmed by the simulation results. [ABSTRACT FROM PUBLISHER]

The output power fluctuation of such renewable energy power plants as a wind-turbine generator and a photovoltaic system results in frequency deviation and terminal voltage fluctuation. Furthermore, these power fluctuations also affect the turbine shafting of diesel generator and gas-turbine generators, which are the main power generation systems in isolated islands. This article presents a control strategy that achieves torsional torque suppression and power system stabilization. Since the measurement of torsional torque is difficult technically, and there is uncertainty in mechanical constants of the shaft torsional system, the torsional torque is estimated by using a linear quadratic regulator observer with a parameter identification system. The simulation results validate the effectiveness of the proposed control system. [ABSTRACT FROM AUTHOR]

This article explains a battery-based control method to reduce the photovoltaic output power fluctuations, which, in turn, will reduce the frequency deviations of the power system. The battery control method introduced here will maintain the state of charge near 50%. Therefore, it will increase the lifetime of the battery, as well as decreasing the maintenance cost. A local search algorithm is provided with this battery control method to search the optimal capacity of the battery required for smoothing the photovoltaic output power fluctuations. Then, a cost comparison is provided to realize the performance of the search algorithm. To verify the effectiveness of the proposed method, simulation results are presented using the actual insolation and load data. [ABSTRACT FROM AUTHOR]

There are concerns in regards to wind power generation as its output constantly, as well as considerably, varies. This article presents a control strategy for wind farms consisting of a wind turbine with variable pitch. In order to reduce output power fluctuation of wind farms, smoothed wind-farm output power command is determined by wind condition and fuzzy neural network. In addition, individual wind turbine generators are controlled by output power command derived from wind-farm output power command and coordination control for each wind turbine generator. Simulation results using an actual detailed model for wind-farm systems show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this article, a mathematical model of ultrasonic motors for speed control, which includes the non-linearity and approximation of the dead-zone in control input, is presented. The intrinsic properties of ultrasonic motors (high torque for low speed, high static torque, compact in size, etc.) offer great advantages for industrial applications. However, the speed property of ultrasonic motors has a strong non-linear property as well as the dead-zone effect in control input associated with load torque. These properties present serious problems for accurate speed control. This article presents a mathematical model represented by a sinusoidal function, which includes these properties. The model is simple and has good approximation of the non-linearity and time varying properties. The proposed speed model has been validated by experimental results. [ABSTRACT FROM AUTHOR]

The ultrasonic motor has nonlinearity characteristics, which varies with driving conditions associated with the variations of temperature and applied load torque of ultrasonic motor. The nonlinearity characteristics for actuators are problems in accurate position control. To improve the control performance of the ultrasonic motor, we apply two-control inputs H∞ controller for position control of the ultrasonic motor. Applying an H∞ methodology we derive a stabilizing controller to meet design objectives and robust stability and performance against such variations. The validity of the proposed method is confirmed by experimental results. [ABSTRACT FROM AUTHOR]

This article presents a new approach to generator scheduling using two-fold simulated annealing (two-fold-SA) method that consists of decomposed-SA and coupling-SA. An initial solution is generated by priority list method. Firstly, the solution is decomposed into hourly schedules and each hourly schedule is modified by decomposed-SA using single bit flipping. If the generated new hourly schedule is better, by convention, it is accepted deterministically. A worse hourly schedule is accepted with temperature dependent SA probability. A new solution consists of these accepted hourly schedules of entire scheduling period after repair as unit-wise constraints may not be fulfilled at the time of individual hourly schedule modification. This helps to detect and modify schedules of appropriate hours. Secondly, in coupling-SA, this new solution is accepted for the next iteration if its cost is less than that of current solution. A higher cost new solution is accepted with another temperature dependent SA probability. Besides, excess units with system dependent probability distribution handle constraints efficiently, and economic load dispatch (ELD) calculations are modified to save the execution time. The proposed method is tested using the reported problem data sets. Simulation results on two cases are compared to previous reported results. Numerical results show an improvement in solution cost and time compared to the results obtained from the powerful algorithms. [ABSTRACT FROM AUTHOR]

The ultrasonic motor has nonlinear characteristics, which vary with driving conditions and possess variable dead-zone in the control input that is associated with the applied load torque. The dead-zone has a problem in accurate positioning actuator. To improve the control performance of the ultrasonic motor, the dead-zone nonlinearity should be eliminated. This article proposes a new position control scheme for the ultrasonic motors that eliminates the problem due to dead-zone by employing fuzzy neural network (FNN). To achieve the accurate position control when drive conditions vary, FNN can adjust the membership function for the antecedent part. The training of FNN is achieved using online backpropagation algorithm. The dead-zone is compensated by FNN, and PI controller performs the accurate positioning of the drive system. The validity of the proposed method is confirmed by experimental results. [ABSTRACT FROM AUTHOR]

This paper presents a new approach to the unit commitment problem using the absolutely stochastic simulated annealing method. In each iteration, a solution is taken with a certain probability. Typically, in the simulated annealing minimization method, a higher cost feasible solution is accepted with temperature-dependent probability, but other solutions are accepted deterministically. That may lead to the near optimization slowly. However in this paper, all the solutions, both higher and lower cost, are associated with acceptance probabilities. Besides, the number of bits flipping is decided by an appropriate distribution. Excess units with system-dependent probability distribution handle constraints efficiently. To reduce the economic load dispatch (ELD) overhead recalculations, a sign bit vector is introduced as well. The proposed method is tested using the reported problem data sets. Simulation results for the systems up to 100 units are compared to the previous reported results. Numerical results show an improvement in solution cost and time over to the results obtained from recent powerful algorithms. [ABSTRACT FROM AUTHOR]

Motor parameters are necessary to achieve several surface-mounted permanent magnet synchronous motor (SPMSM) drive strategies, such as model-based high efficiency control and direct torque control. This article presents a new parameter measurement strategy for vector controlled SPMSM. Iron loss resistance associated with stator iron loss as well as conventional electrical parameters, i.e., electromotive-force (emf) coefficient and stator inductance, are measured on a vector control system. Stator iron loss is measured separately from mechanical and stray losses. As a result, the accuracy on the measurement of iron loss resistance is improved. The validity of the proposed method is confirmed by the comparison between calculated and measured torques. [ABSTRACT FROM AUTHOR]

This article presents the determination of optimal location and capacity of power facilities by using genetic algorithm (GA) based on reliability, loss of load and dump power. We determine optimal capacity after optimal location; however, since the optimal location and capacity are closely related, the optimal location varies with the capacity and vice versa. Hence, we propose the method that determines the optimal location and capacity at the same time. Using the proposed method, expected loss of load in faults can be reduced by 32.3% in comparison with that of separate optimization techniques. [ABSTRACT FROM AUTHOR]

In this article, an approach based on neural network combined with a fuzzy system is proposed for three-hours-ahead load forecasting. In this proposed prediction method, the forecasted load is obtained by adding a correction that is obtained from the neural network and a fuzzy logic to the selected similar days data. The neural network has the advantage of dealing with the nonlinear part of forecasted load curves and the fuzzy rules are constructed based on the expert knowledge. Therefore, by combining these methods, the proposed method is useful in situations where accurate forecasting models are difficult to obtain. The suitability of the proposed approach is illustrated through an application to actual load data of the Okinawa Electric Power Company in Japan. [ABSTRACT FROM AUTHOR]