Search

Strong growth figures prove that wind is now a mainstream option for new power generation. All the successful megawatt-class wind technology developments to date are results of evolutionary design efforts based on the premise that control can significantly improve energy capture and reduce dynamic loads. The main challenge is wind stochasticity that impacts both power quality and drivetrain fatigue life for a wind generating system. In the proposed paradigm, control is exercised through a self-tuning regulator (STR) that incorporates a recursive least-squares algorithm to predict the process parameters and update the states. In above rated regimes, the control strategy incorporating a pitch regulatory system aims to regulate turbine power and maintain stable, closed-loop behavior in the presence of turbulent wind inflow. The control scheme is formulated based on a detailed performability model; the wind speed is generated by a stochastic model, while the drivetrain is modeled as a multiinertia system linked by a non-ideal ([K.sub.s] [not equal to] [infinity]) shaft described by nonlinear equations. Computer simulations reveal that achieving the two objectives of maximizing energy extraction and load reduction by the STR becomes more attractive relative to the classical PID controller design. Index Terms--Aerodynamic power, drivetrain torsional torque, pitch control, recursive least squares (RLSs), self-tuning regulator (STR), state estimation, turbine modeling, turbulence.

A Photovoltaic (PV) system's power output is not constant and fluctuates depending on weather conditions. Fluctuating power causes frequency deviations and reduction in reliability of the isolated power utility or microgrid when large output power from several PV systems is penetrated in the utility. In this paper, to overcome these problems, a simple coordinated control method for leveling the fluctuations of combined power output from multiple PV systems is proposed. The conflicting objective of output power leveling and acquisition power increase is achieved by means of the proposed method. Here, output power command is generated in two steps: central and local. Fuzzy reasoning is used to generate the central leveling output power command considering insolation, variance of insolation, and absolute average of frequency deviation. In local step, a simple coordination is maintained between central power command and local power commands by producing a common tuning factor. Power converters are used to achieve the same output power as local command power employing PI control law for each of the PV generation systems. The proposed method is compared with the method where a modified maximum power point tracking control is used for smoothing the short-term change in each of the PV system's output. Simulation results show that the proposed method is effective for leveling output power fluctuations and feasible to reduce the frequency deviations of the isolated power utility to maintain reliability. Index Terms--Coordinated control, frequency deviation, fuzzy reasoning, insolation, photovoltaic (PV) output power fluctuations.

In recent years, distributed generation, as clean natural energy generation and cogeneration system of high thermal efficiency, has increased due to the problems of global warming and exhaustion of fossil fuels. Many of the distributed generations are set up in the vicinity of the customer, with the advantage that this decreases transmission losses. However, output power generated from natural energy, such as wind power, photovoltaics, etc., which is distributed generation, is influenced by meteorological conditions. Therefore, when the distributed generation increases by conventional control techniques, it is expected that the voltage change of each node becomes a problem. Proposed in this paper is the optimal control of distribution voltage with coordination of distributed installations, such as the load ratio control transformer, step voltage regulator (SVR), shunt capacitor, shunt reactor, and static var compensator. In this research, SVR is assumed to be a model with tap changing where the signal is received from a central control unit. Moreover, the communication infrastructure in the supply of a distribution system is assumed to be widespread. The genetic algorithm is used to determine the operation of this control. In order to confirm the validity of the proposed method, simulations are carried out for a distribution network model with distributed generation (photovoltaic generation). Index Terms--Centralized control, coordinated control, distribution system, genetic algorithm (GA), voltage/reactive power control.

The rapid expansion of wind power generation has brought problems involving lightning strikes to the fore. Many such incidents have damaged not only the wind turbine that was actually struck but also other turbines that were not, a phenomenon that has yet to be fully explained. In this paper, the authors present a case study using a wind farm model with multiple wind turbines connected to a power system. The aim is to clarify the influence of the grounding system on surge propagation from a wind turbine that has been struck to others which have not, during a winter lightning strike. Sensitivity analyses show that the surge propagated to nearby wind turbines can sometimes become large, depending on the conditions of the grounding system, and result in the burnout of surge arresters in turbines that have not been struck, especially during winter lightning strikes. Index Terms.--Grounding (earthing) resistance, lightning surge, surge arrester, transient analysis, wind power generation, wind turbine.

Price forecasting in competitive electricity markets is critical for consumers and producers in planning their operations and managing their price risk, and it also plays a key role in the economic optimization of the electric energy industry. This paper explores a technique of artificial neural network (ANN) model based on similar days (SD) method in order to forecast day-ahead electricity price in the PJM market. To demonstrate the superiority of the proposed model, publicly available data acquired from the PJM Interconnection were used for training and testing the ANN. The factors impacting the electricity price forecasting, including time factors, load factors, and historical price factors, are discussed. Comparison of forecasting performance of the proposed ANN model with that of forecasts obtained from similar days method is presented. Daily and weekly mean absolute percentage error (MAPE) of reasonably small value and forecast mean square error (FMSE) of less than 7$/MWh were obtained for the PJM data, which has correlation coefficient of determination ([R.sup.2]) of 0.6744 between load and electricity price. Simulation results show that the proposed ANN model based on similar days method is capable of forecasting locational marginal price (LMP) in the PJM market efficiently and accurately. Index Terms--Day-ahead electricity market, neural network, price forecasting, similarity technique.

This is the second part of a two-part paper that has arisen from the work of the IEEE Power Engineering Society's Multi-Agent Systems (MAS) Working Group. Part I of this paper examined the potential value of MAS technology to the power industry, described fundamental concepts and approaches within the field of multi-agent systems that are appropriate to power engineering applications, and presented a comprehensive review of the power engineering applications for which MAS are being investigated. It also defined the technical issues which must be addressed in order to accelerate and facilitate the uptake of the technology within the power and energy sector. Part II of this paper explores the decisions inherent in engineering multi-agent systems for applications in the power and energy sector and offers guidance and recommendations on how MAS can be designed and implemented. Given the significant and growing interest in this field, it is imperative that the power engineering community considers the standards, tools, supporting technologies, and design methodologies available to those wishing to implement a MAS solution for a power engineering problem. This paper describes the various options available and makes recommendations on best practice. It also describes the problem of interoperability between different multi-agent systems and proposes how this may be tackled. Index Terms--Multi-agent systems.

This is the first part of a two-part paper that has arisen from the work of the IEEE Power Engineering Society's Multi-Agent Systems (MAS) Working Group. Part I of this paper examines the potential value of MAS technology to the power industry. In terms of contribution, it describes fundamental concepts and approaches within the field of multiagent systems that are appropriate to power engineering applications. As well as presenting a comprehensive review of the meaningful power engineering applications for which MAS are being investigated, it also defines the technical issues which must be addressed in order to accelerate and facilitate the uptake of the technology within the power and energy sector. Part II of this paper explores the decisions inherent in engineering multi-agent systems for applications in the power and energy sector and offers guidance and recommendations on how MAS can be designed and implemented. Index Terms--Multi-agent systems.

This paper presents an adaptive dead-time compensation strategy to obtain fundamental phase voltage for inverter-fed vector-controlled permanent magnet synchronous motor drives. A phase dead-time compensation voltage (DTCV) to compensate the disturbance voltage due to undesirable characteristics of inverter, such as dead time, turn on/off time of switching devices, and on-voltages of switching devices and diode, is transformed into q-axis DTCV in the rotor reference frame. The relationship between q-axis DTCV and a dead-time compensation time (DTCT) is investigated. DTCT is identified online by using q-axis disturbance voltage, which is estimated by a disturbance observer. The amplitude of phase DTCV is adaptively determined according to the identified DTCT. The accuracy of identified DTCT is experimentally confirmed by calculating the mean absolute percentage error (MAPE) between calculated active power and measured one. MAPE for adaptive DTCT is within 5% at any operating point and is less than that for the fixed DTCT. Index Terms--Dead-rune compensation time (DTCT), dead time compensation voltage (DTCV), disturbance voltage, permanent magnet synchronous motor (PMSM), voltage source inverter.

Wind energy is not constant and windmill output is proportional to the cube of wind speed, which causes the generated power of wind turbine generators (WTGs) to fluctuate. In order to reduce fluctuation, different methods are available to control the pitch angle of blades of windmill. In a previous work, we proposed the pitch angle control using minimum variance control, and output power leveling was achieved. However, it is a controlled output power for only rated wind speed region. This paper presents a control strategy based on average wind speed and standard deviation of wind speed and pitch angle control using a generalized predictive control in all operating regions for a WTG. The simulation results by using actual detailed model for wind power system show the effectiveness of the proposed method. Index Terms--Generalized predictive control, output power fluctuation, pitch angle control, wind turbine generator (WTG).

Photovoltaic power generation and wind power generation have an advantage that energy is clean and infinite, but they have a disadvantage in that electrical output energy is unstable, and initial and maintenance costs are expensive. This paper presents an optimal configuration for renewable generating systems in residence using a genetic algorithm (GA). We define that the objective function is the total cost, where the total cost is the sum of initial cost, an operation cost, and a maintenance cost. We determine an optimal configuration of renewable generating systems, where total cost is more reasonable using GA. The simulation using this technique is shown. Index Terms--Genetic algorithm (GA), optimal configuration, renewable generating system.

This paper presents a new approach to the fuzzy unit commitment problem using the absolutely stochastic simulated annealing method. In every 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. However, in this paper, all the solutions, both higher and lower cost, are associated with acceptance probabilities, e.g., the minimum membership degree of all the fuzzy variables. Besides, the number of bits flipping is decided by the linguistic fuzzy control. Excess units with system-dependent distribution handle constraints efficiently and reduce overlooking the optimal solution. To reduce the economic load dispatch calculations, a sign bit vector is introduced with imprecise calculation of the fuzzy model as well. The proposed method is tested using the reported problem data sets. Simulation results are compared to previous reported results. Numerical results show an improvement in solution cost and time compared to the results obtained from powerful algorithms. Index Terms--Best heat rate, fuzzy logic, linguistic fuzzy control, sign vector, simulated annealing (SA), unit commitment (UC).

This paper presents an adaptive dead-time compensation strategy to obtain fundamental phase voltage for inverter fed vector controlled permanent magnet synchronous motor drives. The amplitude of phase dead-time compensation voltage (DTCV) to compensate disturbance voltage due to undesirable characteristics of inverter, such as dead-time, turn-on/off time of switching devices, and on-voltages of switching devices and diodes is adaptively determined according to a dead-time compensation time (DTCT). DTCT is identified on-line with using a [delta]-axis disturbance voltage in the current reference frame that is synchronized with current vector. The [delta]-axis disturbance voltage is estimated by a disturbance observer. The accuracy of identified DTCT is experimentally confirmed by calculating the mean absolute percentage error (MAPE) between a calculated active power and a measured one. MAPE for adaptive DTCT is almost within 5% at any operating point. Index Terms--Current vector, dead-time, disturbance observer, permanent magnet synchronous motor (PMSM), voltage source inverter (VSI).

A hybrid power system uses many wind turbine generators in isolated small islands. The output power of wind turbine generators is mostly fluctuating and has an effect on system frequency. In order to solve this problem, we propose a new power system using renewable energy in small, isolated islands. The system can supply high-quality power using an aqua electrolyzer, fuel cell, renewable energy, and diesel generator. The generated hydrogen by an aqua electrolyzer is used as fuel for a fuel cell. The simulation results are given to demonstrate the availability of the proposed system in this paper. Index Terms--Aqua electrolyzer, frequency fluctuation, fuel cells, power-supply system, wind turbine generators.

This paper presents an approach for short-term load forecast problem, based on hybrid correction method. Conventional artificial neural network based short-term load forecasting techniques have limitations especially when weather changes are seasonal. Hence, we propose a load correction method by using fuzzy logic approach in which a fuzzy logic, based on similar days, corrects the neural network output to obtain the next day forecasted load. An Euclidean norm with weighted factors is used for the selection of similar days. The load correction method for the generation of new similar days is also proposed. The neural network has an advantage of dealing with the nonlinear parts of the forecasted load curves, whereas, the fuzzy rules are constructed based on the expert knowledge. Therefore, by combining these two methods, the test results show that the proposed forecasting method could provide a considerable improvement of the forecasting accuracy especially as it shows how to reduce neural network forecast error over the test period by 23% through the application of a fuzzy logic correction. The suitability of the proposed approach is illustrated through an application to actual load data of the Okinawa Electric Power Company in Japan. Index Terms--Fuzzy logic approach, hybrid correction method, neural network, short-term load forecasting.

Surge tests were performed to derive a generator model considering its frequency characteristics. Impulse voltages were applied to one terminal of the generators after placing a variable capacitor at the same terminal. The inductances and the core-loss resistances of a generator model can be determined from the measured oscillating voltages. This paper presents a generalization of the method aimed at deriving these generator parameters. The accuracy of the proposed method is confirmed to be satisfactory after comparing measured and simulated transfer voltages. Index Terms--Frequency characteristics, generator model, generator step-up transformer, oscillation frequency, transfer voltage.

This paper introduces a new unit commitment problem, adapting extended priority list (EPL) method. The EPL method consists of two steps, in the first step we get rapidly some initial unit commitment problem schedules by priority list (PL) method. At this step, operational constraints are disregarded. In the second step unit schedule is modified using the problem specific heuristics to fulfill operational constraints. To calculate efficiently, however, note that some heuristics applied only to solutions can expect improvement. Several numerical examples demonstrate the effectiveness of proposed method. Index Terms--Heat rate, power system operation and planning, priority list, priority order, unit commitment.

Twenty-nine backflashovers were recorded on a 77-kV double-circuit transmission line with single overhead groundwire. Twenty-six of these occurred on phases where power-frequency voltage bias was positive. EMTP analysis of the line shows that the multistory tower model, recommended by the Japanese Guideline of Insulation Design/Coordination against Lightning, suggests a stronger influence of phase position than was observed. Best simulation results were obtained with a simple tower model of constant surge impedance. Index Terms--Flashover, lightning, surges, transient analysis.

Load forecasting has always been the essential part of an efficient power system planning and operation. Several electric power companies are now forecasting load power based on conventional methods. However, since the relationship between load power and factors influencing load power is nonlinear, it is difficult to identify its nonlinearity by using conventional methods. Most of papers deal with 24-hour-ahead load forecasting or next day peak load forecasting. These methods forecast the demand power by using forecasted temperature as forecast information. But, when the temperature curves changes rapidly on the forecast day, load power changes greatly and forecast error would going to increase. In conventional methods neural networks uses all similar day's data to learn the trend of similarity. However, learning of all similar day's data is very complex, and it does not suit learning of neural network. Therefore, it is necessary to reduce the neural network structure and learning time. To overcome these problems, we propose a one-hour-ahead load forecasting method using the correction of similar day data. In the proposed prediction method, the forecasted load power is obtained by adding a correction to the selected similar day data. Index Terms--Load forecasting, recurrent neural network, on-line learning.

Measurements were performed to get the response of arrester block to steep front impulse current(1/2[[micro]seconds]), 4/10[[micro]seconds] impulse current and standard impulse (8/20[[micro]seconds]). As the steep front wave response model, the conventional model, IEEE model, and nonlinear inductance model have been studied. The method of building arrester block model was explained in this paper. The nonlinear inductance model proposed in this paper has accuracy with about 1% error in calculations of steep front impulse in block model study. This model can be built easily and simply. Keywords - Insulation coordination, Steep front impulse, residual voltage characteristics, Arrester block, IEEE recommended Model, Nonlinear inductance model