Wind Generator Output Power Research Articles

Performance analysis method for cogeneration system with multiple energy supplies

Compressed air storage technology plays an important role in the utilization of renewable energy sources and has received extensive attention in recent years. This paper proposes a cogeneration system with multiple energy supplies to generate electricity, heat energy and domestic hot water. Compressed air energy storage equipment is used to stabilize the wind generator output power, and the air compression process is used to heat domestic water and the air release process is used to assist the gas turbine generating electricity. The stability and efficiency of the multi-energy cogeneration system can be improved by simulating and analyzing the influencing factors and setting the equipment parameters reasonably.

Fuzzy-based smoothing of fluctuations in output power from wind and photovoltaics in a hybrid power system with batteries

Higher penetration of intermittent renewable sources such as wind and photovoltaic systems requires an efficient way to manage the fluctuated power before injecting it into the grid. This paper proposes a fuzzy‐based smoothing of the output power of wind and photovoltaic generators in a hybrid power system with batteries. The state of charge of the battery system, as well as the pitch angle of wind turbines, is used to limit the fluctuations of the injected power. A first‐order filter is adaptively adjusted by incorporating changes in the battery power, state of charge, and pitch angle through the use of fuzzy logic. The proposed method is verified for different levels of state of charges, and the simulation results show that the proposed approach produces a better smoothing as compared to other methods.

Technology Development of Wind Power Ramp Forecast and Generation Output Control

Technology Development of Wind Power Ramp Forecast and Generation Output Control

Analysis and Design of Filters for the Energy Storage System: Optimal Tradeoff Between Frequency Guarantee and Energy Capacity/Power Rating

This paper proposes a new filter design method that can smooth the wind power generation output while keeping the energy capacity and power rating of the energy storage system (ESS) small. Wind power generation causes frequency fluctuations in power systems. Therefore, in many cases, the ESS is needed for smoothing the fluctuations of wind generator output. In order to improve the performance of the ESS controlled with the conventional low-pass filter (LPF), this paper investigates other types of filters. First, the relations between filter and energy capacity/power rating of the ESS are disclosed through the worst-case study. Then, the frequency fluctuation analysis of the power system with respect to the wind power generation is carried out in order to realize a pin-point smoothing. Finally, a metaheuristic optimization method is proposed for the multiobjective design of the filter based on these relations so as to achieve an optimal tradeoff between the output smoothing and energy capacity/power rating of the ESS. It is shown via simulation analysis with real wind data that the proposed method can suppress the frequency fluctuation of the power system effectively with the ESS having smaller energy capacity and power rating.

Study on the ramp fluctuation suppression control of wind power generation output using optimization method

AbstractRecently, wind power generation are installed as a countermeasure for the environmental issue in Japan. However, wind power generation output is fluctuated due to wind condition. Moreover, it is some negative impact for system operation such as the economic load dispatching control and the load frequency control. In Japan, NEDO has started the project as a countermeasure for massive penetration of wind power generation in 2014, called “R&D Project on Grid Integration of Variable Renewable Energy.” In this paper, we proposed the output fluctuation suppression control method of wind power generation using the battery and forecast data of wind generation output. Specifically, the target value of wind power generation output is calculated to decrease the deviation output from fluctuation suppression code for ramp event using deterministic optimization method. The effectiveness of proposed method is evaluated through the computational simulation using forecast data and actual wind power generation output in Tohoku area.

The Research on the Braking System of the Small Danielle Wind Generators

By researching on the mathematical model of small danielle wind generators, it is easily to find that reasonable load connection and disconnection or changing the load characteristics could control the rotational speed and output power of wind generators. Using the controlling strategy combined with switching braking resistor and three-phase short-circuit braking, the rotational speed of wind generator could be controlled accurately in the scenes of sustainable strong wind or the wind speed continuously increasing. At the same time, users’ cost could be ensured. A lot of field experiments had proved the feasibility and practicality of the controlling strategy. The research of this paper would promote the application of small danielle wind generators.

Testing of a Solar-PV/Wind operated AC-DC Microgrid with LabVIEW Controller

This paper discusses about a LabVIEW based controller for the hybrid renewable energy system operated AC-DC microgrid with the major objectives of: i) predicting the power generation potential of the solar–PV and wind generators ii) effective power management iii) load scheduling based on the available power with the renewable sources and iv) grid/islanding mode of operation of the microgrid. In order topredict the output power of wind generator and Solar-PV system, an artificial neural network is developed.The laboratory-scale model of three phase, 400 V, 10 kVA microgrid structure is developed at National Institute of Technology Calicut, India. The developed LabVIEW based controller has been tested successfully for a real-time load and source in the laboratory environment. Test results show that the designed controller is effectively managing the output powerof the primary energy sources under different scenarios.

Wind Power Interval Prediction Based on Improved PSO and BP Neural Network

As is known to all that the output of wind power generation has a character of randomness and volatility because of the influence of natural environment conditions. At present, the research of wind power prediction mainly focuses on point forecasting, which can hardly describe its uncertainty, leading to the fact that its application in practice is low. In this paper, a wind power range prediction model based on the multiple output property of BP neural network is built, and the optimization criterion considering the information of predicted intervals is proposed. Then, improved Particle Swarm Optimization (PSO) algorithm is used to optimize the model. The simulation results of a practical example show that the proposed wind power range prediction model can effectively forecast the output power interval, and provide power grid dispatcher with decision.

Short-term wind power forecasting using a double-stage hierarchical ANFIS approach for energy management in microgrids

Determination of the output power of wind generators is always associated with some uncertainties due to wind speed and other weather parameters variation, and accurate short-term forecasts are essential for their efficient operation. This can efficiently support transmission and distribution system operators and schedulers to improve the power network control and management. In this paper, we propose a double stage hierarchical adaptive neuro-fuzzy inference system (double-stage hybrid ANFIS) for short-term wind power prediction of a microgrid wind farm in Beijing, China. The approach has two hierarchical stages. The first ANFIS stage employs numerical weather prediction (NWP) meteorological parameters to forecast wind speed at the wind farm exact site and turbine hub height. The second stage models the actual wind speed and power relationships. Then, the predicted next day’s wind speed by the first stage is applied to the second stage to forecast next day’s wind power. The influence of input data dependency on prediction accuracy has also been analyzed by dividing the input data into five subsets. The presented approach has resulted in considerable forecasting accuracy enhancements. The accuracy of the proposed approach is compared with other three forecasting approaches and achieved the best accuracy enhancement than all.

Uncertain flow calculations of a distribution network containing DG based on blind number theory

A large number of distributed generations (DG) integrated into a distribution network challenge the planning for traditional power systems making traditional deterministic power flow calculations not applicable. Based on the interval and credibility of the blind number theory, this study is about the uncertainty of DG and the correlation between DGs. The interval models for wind power and solar power are established based on the characteristics of the wind power generator output and the photovoltaic cell output. The improved analytic hierarchy process is applied to determine the credibility of the intervals. The blind number theory and Cholesky decomposition are applied to study the correlation between wind speed and light intensity. According to the result of the power flow calculation with uncertainty, the voltage operational quality index is proposed to measure the impact of the DG. Through a modified IEEE 33-bus system, the feasibility and effectiveness of the blind number model for the DG and the necessity of considering the correlation between wind speed and light intensity are verified.

A Novel DFIG Damping Control for Power System with High Wind Power Penetration

Aiming at the fact that large-scale penetration of wind power will to some extent weaken the small signal stability of power systems, in this paper, the dynamic model of a doubly fed induction generator (DFIG) is established firstly, to analyze the impact of wind generation on power oscillation damping. Then, based on the conventional maximum power point tracking control of variable speed wind turbine, a supplementary control scheme is proposed to increase the damping of power system. To achieve best performance, parameters of the damping control are tuned by using a genetic algorithm. Results of eigenvalue analysis and simulations demonstrate the effectiveness of supplementary damping control with fixed wind speed. At last, due to the problem that fluctuation of output power of wind generators would cause the unstable performance of the DFIG damping controller above, a new algorithm that adapts to the wind variation is added to the supplementary damping control scheme. Results of the simulation show that an improved damping control scheme can stably enhance system damping under various wind speeds and has higher practical value.

Design and Implementation of Bi-Directional DC-DC Converter for Wind Energy System

This paper proposes a design and implementation of the bi-directional DC-DC converter for Wind Energy Conversion System. The proposed project consists of boost DC/DC converter, bi-directional DC/DC converter (BDC), permanent magnet DC generator and batteries. A DC-DC boost converter is interface with proposed wind system to step up the initial generator voltage and maintain constant output voltage. The fluctuation nature of wind makes them unsuitable for standalone operation. To overcome the drawbacks an energy storage device is used in the proposed system to compensate the fluctuations and to maintain a smooth and continuous power flow in all operating modes to load. Bi-directional DC-DC converter (BDC) is capable of transforming energy between two DC buses. It can operate as a boost converter which supplies energy to the load when the wind generator output power is greater than the required load power. It also operates in buck mode which charges from DC bus when output power is less than the required load power. The proposed converter reduces the component losses and increases the performance of the overall system. The complete system is implemented in MATLAB/SIMULINK and verified with hardware.

Improvement in Solar Chimney Power Generation by Using a Diffuser Tower

The solar chimney prototype, operated in Spain from 1982 to 1989, verified the concept of the solar chimney. The power generation mechanism in this system is to turn the wind turbine placed inside a high rise cylindrical hollow tower by an induced thermal updraft. As long as the thermal updraft is induced inside the tower by the solar radiation, this system can produce electricity. The disadvantage of this system is the low power generation efficiency compared to other solar energy power generation systems. To overcome this disadvantage, we improved the mechanism in order to augment the velocity of the air which flows into the wind turbine. By applying a diffuser tower instead of a cylindrical one, the efficiency of the systems power generation is increased. The mechanism that we investigated was the effect of the diffuser on the solar chimney structure. The inner diameter of the tower expands as the height increases so that the static pressure recovery effect of the diffuser causes a low static pressure region to form at the bottom of the tower. This effect induces greater airflow within the tower. The laboratory experiment, as does the computational fluid dynamics (CFD) analysis of the laboratory sized model, shows that the proposed diffuser type tower induces a velocity approximately 1.38–1.44 times greater than the conventional cylindrical type. The wind power generation output is proportional to the cube of the incoming wind velocity into the wind turbine; therefore, approximately 2.6–3.0 times greater power output can be expected from using the diffuser type tower.

Design and Performance Analysis of Coreless Axial-Flux Permanent-Magnet Generator for Small Wind Turbines

This paper presents an innovative design for a low-speed, direct-drive, axial-flux permanent-magnet (AFPM) generator with a coreless stator and rotor that is intended for application to small wind turbine power generation systems. The performance of the generator is evaluated and optimized by means of comprehensive 3D electromagnetic finite element analysis. The main focus of this study is to improve the power output and efficiency of wind power generation by investigating the electromagnetic and structural features of a coreless AFPM generator. The design is validated by comparing the performance achieved with a prototype. The results of our comparison demonstrate that the proposed generator has a number of advantages such as a simpler structure, higher efficiency over a wide range of operating speeds, higher energy yield, lighter weight and better power utilization than conventional machines. It would be possible to manufacture low-cost, axial-flux permanent-magnet generators by further developing the proposed design.

Modeling Large-Scale Wind Farms for Reliability Analysis Considering Wake Effect

Large scale wind power penetration has a significant impact on the reliability of the electric generation systems. A wind farm consists of a large number of wind turbine generators (WTGs). A major difficulty in modeling wind farms is that the WTG not have an independent capacity distribution due to the dependence of the individual turbine output on the same energy source, the wind. In this paper, a model of the wind farm output power considering multi-wake effects is established according to the probability distribution of the wind speed and the characteristic of the wind generator output power: based on the simple Jenson wake effect model, the wake effect with wind speed sheer model and the detail wake effect model with the detail shade areas of the upstream wind turbines are discussed respectively. Compared to the individual wake effect model, this model takes the wind farm as a whole and considers the multi-wakes effect on the same unit. As a result the loss of the velocity inside the wind farm is considered more exactly. Furthermore, considering the features of sequentially and self-correlation of wind speed, an auto-regressive and moving average (ARMA) model for wind speed is built up. Also the reliability model of wind farm is built when the output characteristics of wind power generation units, correlation of wind speeds among different wind farms, outage model of wind power generation units, wake effect of wind farm and air temperature are considered. Simulation results validate the effectiveness of the proposed models. These models can be used to research the reliability of power grid containing wind farms, wind farm capacity credit as well as the interconnection among wind farms

Study on Accuracy of Wind-Power Caused Flicker Estimation

Intermittent and volatility of wind energy makes wind power generation output power characterized by its instability make adverse impact on grid power quality , will give a rise to serious problems of voltage fluctuation and flicker. It is very important to calculate the flicker emission when analysis the power quality. However, flicker level is hard to predict and the way given by IEC61400-21 has been verified to be lack of accuracy. This paper analyzes a constant speed wind turbines caused grid voltage fluctuation and flicker on the mechanism. Illustrates the two way to measure flickers caused by voltage fluctuation. Improves the on-site calculation of flicker by considering the impact of tower shadow and wind shear. Finally, verified the feasibility of the improved methodology by comparing the results of the three calculation.

Multi-Objective Stochastic Distribution Feeder Reconfiguration in Systems With Wind Power Generators and Fuel Cells Using the Point Estimate Method

This paper presents a multi-objective algorithm to solve stochastic distribution feeder reconfiguration (SDFR) problem for systems with distributed wind power generation (WPG) and fuel cells (FC). The four objective functions investigated are 1) the total electrical energy losses, 2) the cost of electrical energy generated, 3) the total emissions produced, and 4) the bus voltage deviation. A probabilistic power flow based on the point estimate method (PEM) is employed to include uncertainty in the WPG output and load demand, concurrently. Different wind penetration strategies are examined to capture all economical, operational and environmental aspects of the problem. An interactive fuzzy satisfying optimization algorithm based on adaptive particle swarm optimization (APSO) is employed to determine the optimal plan under different conditions. The proposed method is applied to Taiwan Power system and the results are validated in terms of efficiency and accuracy.

Study of a Hybrid Wind and Solar Energy Power System

A new kind of hybrid wind and solar energy power system was proposed in this paper. In the hybrid system, the technologies of compressed air energy storage (CAES), solar heat storage and gas-steam combined cycle power generation were combined together. At same oil consumption of 19.48 t/h, the output power of the hybrid system in the paper was 194.69 MW, while that of the conventional gas-steam combined cycle was 103.15 MW. The difference between the two cycles was 91.54 MW, which was equivalent to the amount of wind and solar energy power generation. When annual effective operating time of the hybrid system was 2600 h, the power output of wind and solar energy power generation reached 238 million kW•h. If coal-fired power plants were taken as the reference standard, about 113,050 tons of coal was saved per year. An overall benefit of Ұ604.28~626.01 million was obtained per year. As a result, a good economic, environmental and social benefit was achieved.

The Doubly Fed Wind Power Generator Output Characteristic with the Asymmetrical Grid Voltage

The paper describe the imbalance loads、single phase short circuit to ground or bidirectional circuit to ground in the grid can bring unbalanced fault and the asymmetrical grid voltage. In the DFIG the faint imbalance stator voltage can bring much imbalance current, electromagnetic torque and active power would fluctuate. The DFIG performance will deteriorate, the central reason is the negative sequence component of the stator voltage、current with the asymmetrical grid voltage. The comparison between evaluated results and simulation of stator、rotor transient currents when the grid voltage drops is similar much.

Study on output prediction system of wind power generation using complex‐valued neural network with multipoint GPV data

AbstractIn recent years, wind power generation has seen rapid growth as a solution to the depletion of fossil fuels and to global warming. However, the output of the wind power generator fluctuates widely depending on the wind speed, which affects the power grid. In this paper, we propose a prediction system of wind power generation ahead of 24 h by using a complex‐valued neural network (CVNN). To predict the output of wind power generation, it is necessary to predict the wind speed accurately. Generally, wind data is expressed as a vector, which has both magnitude and direction. Therefore, it is also possible to treat wind data by a complex number and then use it as input information of the CVNN, which is very useful for operation of a complex number and nonlinear data. In computer simulations, we use multipoint numerical weather prediction data that surround the wind prediction point to realize long‐time prediction. Thereby, we expect that the CVNN can take into account wind dynamics in two‐dimensional space. Several simulation results and t‐tests demonstrate the effectiveness of the proposed prediction system. © 2012 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.