Modeling,control and simulation of an autonomous wind turbine/photovoltaic/fuel cell/ultra-capacitor hybrid power system

This paper focuses on the combination of wind turbine (WT), photovoltaic (PV), fuel cell (FC) and ultra-capacitor (UC) systems for grid-independent applications. The dynamic behavior of the proposed hybrid system is tested under various wind speed, solar radiation and load demand conditions. The developed model and its control strategy exhibit excellent performance for the simulation of a complete day. In the simulation, the solar radiation and power demand data are based on real world measurements, while the wind speed data are quasi-real because it is simulated based on special wind speed generation algorithms.     

Overview of worldwide wind generation

An summary of the growth in wind energy generation worldwide.     

Investigation on wind power potential on Hong Kong islands—an analysis of wind power and wind turbine characteristics

This paper discusses the potential for electricity generation on Hong Kong islands through an analysis of the local weather data and typical wind turbine characteristics. An optimum wind speed, u_op, is proposed to choose an optimal type of wind turbine for different weather conditions. A simulation model has been established to describe the characteristics of a particular wind turbine. A case study investigation allows wind speed and wind power density to be obtained using different hub heights, and the annual power generated by the wind turbine to be simulated. The wind turbine's capacity factor, being the ratio of actual annual power generation to the rated annual power generation, is shown to be 0.353, with the capacity factor in October as high as 0.50. The simulation shows the potential for wind power generation on the islands surrounding Hong Kong.     

An integrated control method for a wind farm to reduce frequency deviations in a small power system

Output power of wind turbine generator (WTG) is not constant and fluctuates due to wind speed changes. To reduce the adverse effects of the power system introducing WTGs, there are several published reports on output power control of WTGs detailing various researches based on pitch angle control, variable speed wind turbines, energy storage systems, and so on. In this context, this paper presents an integrated control method for a WF to reduce frequency deviations in a small power system. In this study, the WF achieves the frequency control with two control schemes: load estimation and short-term ahead wind speed prediction. For load estimation in the small power system, a minimal-order observer is used as disturbance observer. The estimated load is utilized to determine the output power command of the WF. To regulate the output power command of the WF according to wind speed changing, short-term ahead wind speed is predicted by using least-squares method. The predicted wind speed adjusts the output power command of the WF as a multiplying factor with fuzzy reasoning. By means of the proposed method, the WF can operate according to the wind and load conditions. In the WF system, each output power of the WTGs is controlled by regulating each pitch angle. For increasing acquisition power of the WF, a dispatch control method also is proposed. In the pitch angle control system of each WTG, generalized predictive control (GPC) is applied to enhance the control performance. Effectiveness of the proposed method is verified by the numerical simulations.     

An investigation on the impacts of regulatory interventions on wind power expansion in generation planning

Large integration of intermittent wind generation in power system has necessitated the inclusion of more innovative and sophisticated approaches in power system investment planning. This paper presents a novel framework on the basis of a combination of stochastic dynamic programming (SDP) algorithm and game theory to study the impacts of different regulatory interventions to promote wind power investment in generation expansion planning. In this study, regulatory policies include Feed-in-Tariff (FIT) incentive, quota and tradable green certificate. The intermittent nature and uncertainties of wind power generation will cause the investors encounter risk in their investment decisions. To overcome this problem, a novel model has been derived to study the regulatory impacts on wind generation expansion planning. In our approach, the probabilistic nature of wind generation is modeled. The model can calculate optimal investment strategies, in which the wind power uncertainty is included. This framework is implemented on a test system to illustrate the working of the proposed approach. The result shows that FITs are the most effective policy to encourage the rapid and sustained deployment of wind power. FITs can significantly reduce the risks of investing in renewable energy technologies and thus create conditions conducive to rapid market growth.     

PSCAD/EMTDC环境下双馈风力发电机组的建模与仿真

介绍了一种在PSCAD/EMTDC环境中建立双馈风电机组模型以用于电磁暂态分析的方法。分析了风力机风速与输出转矩的关系,建立了机侧换流器的定子磁链定向矢量控制模型、网侧换流器的电网电压定向矢量控制模型,并考虑了低电压穿越控制策略。最后在PSCAD/EMTDC环境中建立了双馈风电机组的模型,仿真验证了建模方法的有效性和正确性。仿真结果表明,在PSCAD/EMTDC环境中,双馈风机建模方法能够准确地描述风电机组的电磁暂态特性。     

Adequacy evaluation of wind power generation systems

This paper attempts to assess the adequacy of wind power generation systems using the data collected from seven wind farms in Muppandal, Tamilnadu (India) with a total capacity of 37 MW. A Monte Carlo model simulation is incorporated in the algorithm to obtain the hourly power output of wind farms, which also takes into account the unavailability of wind turbines. A typical load demand profile is used to examine the chronological hourly wind power generation for each month. The reliability index of LOLE (loss of load expectation) is used to estimate the reliable contribution of wind farm power generation.     

The influence of generation mix on the wind integrating capability of North China power grids: A modeling interpretation and potential solutions

The large-scale wind power development in China has reached a bottleneck of grid integrating capability. As a result, excess wind electricity has to be rejected in the nighttime low demand hours, when the wind power is ramping up. To compensate for the fluctuation of wind power, new coal-fired power plants are being constructed along with the big wind projects in the North China grids. This study analyzed why adding coal-fired generation cannot remove the bottleneck of wind integration by modeling the operating problem of the wind integration. The peak-load adjusting factor of the regional grid is defined. Building more coal-fired power plants will not increase the adjusting factor of the current grid. Although it does help to increase the total integrated wind power in the short term, it will add difficulties to the long-term wind integration. Alternatively, the coordinated resource utilization is then suggested with the discussion of both the effective pumped hydro storage and the potential electric vehicle storage.     

Impact of wind farms on a power system. An eigenvalue analysis approach

This paper analyzes the frequency dynamic behavior in a power system with a high wind power penetration. To this end, wind farms equipped with squirrel cage and doubly fed induction generators are compared. Aspects of the modeling of the different kinds of wind generation and power systems are cited. Then, it is shown, through an eigenvalue analysis, that wind farms equipped by doubly fed induction machines, adequately controlled, can contribute to improve the frequency dynamics. Simulations are presented which verify the theoretical results.     

Comparative study on the performance of control systems for doubly fed induction generator (DFIG) wind turbines operating with power regulation

As a result of the increasing wind power penetration on power systems, the wind farms are today required to participate actively in grid operation by an appropriate generation control. This paper presents a comparative study on the performance of three control strategies for DFIG wind turbines. The study focuses on the regulation of the active and reactive power to a set point ordered by the wind farm control system. Two of them (control systems 1 and 2) are based on existing strategies, whereas the third control system (control system 3) presents a novel control strategy, which is actually a variation of the control system 2. The control strategies are evaluated through simulations of DFIG wind turbines, under normal operating conditions, integrated in a wind farm with centralized control system controlling the wind farm generation at the connection point and computing the power reference for each wind turbine according to a proportional distribution of the available power. The three control systems present similar performance when they operate with power optimization and power limitation strategies. However, the control system 3 with down power regulation presents a better response with respect to the reactive power production, achieving a higher available reactive power as compared with the other two. This is a very important aspect to maintain an appropriate voltage control at the wind farm bus.     

Dynamic model of wind energy conversion systems with variable speed synchronous generator and full-size power converter for large-scale power system stability studies

This paper presents a dynamic model for variable speed wind energy conversion systems, equipped with a variable pitch wind turbine, a synchronous electrical generator, and a full power converter, specially developed for its use in power system stability studies involving large networks, with a high number of buses and a high level of wind generation penetration. The validity of the necessary simplifications has been contrasted against a detailed model that allows a thorough insight into the mechanical and electrical behavior of the system, and its interaction with the grid. The developed dynamic model has been implemented in a widely used power system dynamics simulation software, PSS/E, and its performance has been tested in a well-documented test power network.     

Application of a control algorithm for wind speed prediction and active power generation

The main objective of the work described in this paper is to offer a new method of prediction of wind speeds, whilst aware that the method develops predictions in time-scales that can vary from a few minutes to an hour. This is needed because wind energy generation is increasing its participation in energy distribution and has to compete with other energy sources that are not so variable in terms of generated active power. It is important to consider that active power demand can vary quite rapidly and different sources of electricity generation must be available. In the case of wind energy, wind speed predictions are an important tool to help producers make the best decisions when selling the energy produced. These decisions are crucial in the electricity market, because of the economic benefits for producers and consequently their profitability, depends on them. The algorithm presented in this paper is based on an artificial neural network and two types of wind data have been used to test the algorithm. In the first, data was collected from a not very windy area; in the second data was collected from a real wind farm located in Navarre (North of Spain), and the values vary from very low to high speeds. Although the algorithm was not tested with typical wind speed values measured on offshore wind farm applications, it can be concluded from the first set of results presented in this paper that the algorithm is valid for estimating average speed values. Finally, a generic algorithm for the active power generation of a wind farm is presented.     

Maximum wind power generation in a power system imposed by system inertia and primary reserve requirements

Although the technology to simulate inertia or to provide primary control in wind power generators is mature, most of them are a source of power with neither inertia nor primary reserve provision mainly because it means wind spilling. Therefore, an increasing wind power penetration means a reduction in the inertia of the system and of the primary reserve due to the substitution of conventional generation. In this paper, the maximum wind power penetration focusing on system inertia and primary reserve value is assessed. The Spanish power system is used as an example for the calculation of these values. For this purpose, real Spanish scenario data are used. Results will show that high penetrations of wind power can be achieved without risking adequate values of primary reserve or inertia of the power system even if wind power does not contribute to these items. Copyright © 2014 John Wiley & Sons, Ltd.     

Simultaneous planning of plug-in hybrid electric vehicle charging stations and wind power generation in distribution networks considering uncertainties

Recently, plug-in hybrid electric vehicles (PHEV) are becoming more attractive than internal combustion engine vehicles (ICEV). Hence, design and modeling of charging stations (CSs) has vital importance in distribution system level. In this paper, a new formulation for PHEV charging stations is presented with the strategic presence of wind power generation (WPG). This study considers constraints of the system losses, the regulatory voltage limits, and the charge/discharge schedule of PHEV based on the social behavior of drivers for appropriate placement of PHEV charging stations in electricity grid. The role of CSs and WPG units must be correctly assessed to optimize the investment and operation cost for the whole system. However, the wind generation owners (WGOs) have different objective functions which might be contrary to the objectives of distribution system manager (DSM). It is assumed that aggregating and management of charge/discharge program of PHEVs are smartly carried out by DSM. This paper presents a long-term bi-objective model for optimal planning of PHEV charging stations and WPG units in distribution systems which simultaneously optimize two objectives, namely the benefits of DSM and WGO. It also considers the uncertainty of load growth, electricity price and PHEV access to the charging station using Mont-Carlo simulation (MCS) method. Initial state of charge uncertainty is also modeled based on scenario approach in PHEV batteries and wind turbine power generation using weibull distribution. Non dominated sorting genetic algorithm (NSGA-II) is used to solve the optimization problem. The simulation has been conducted on the nine-bus system.     

基于叶素理论的风力机组建模与仿真

基于叶素理论建立了风力发电机组空载状况下的数学物理模型,以攻角为控制对象设计控制器,在此基础上,以Matlab/Simulink为工具,建立了系统仿真模型,采用"试凑法"选择PI控制器的参数,通过设定风速分析了风力发电机组的运行特性,仿真结果验证了理论分析的正确性。该研究对控制器的设计具有参考价值。     

Multi-objective optimization of the hybrid wind/solar/fuel cell distributed generation system using Hammersley Sequence Sampling

As the development of China's economy, environmental problems in China become more and more serious. Solar energy and wind energy are considered as ones of the best choices to solve the environmental problems in China and the hybrid wind/solar distributed generation (DG) system has received increasing attention recently. However, the instability and intermittency of the wind and solar energy throw a huge challenge on designing of the hybrid system. In order to ensure the continuous and stable power supply, optimal unit sizing of the hybrid wind/solar DG system should be taken into consideration in the design of the hybrid system. This paper establishes a multi-objective optimization framework based on cost, electricity efficiency and energy supply reliability models of the hybrid DG system, which is composed of wind, solar and fuel cell generation systems. Detailed models of each unit for the hybrid wind/solar/fuel cell system were established. Advanced ε-constraints method based on Hammersley Sequence Sampling was employed in the multi-objective optimization of the hybrid DG system. The approximate Pareto surface of the multi-objective optimization problems with a range of possible design solutions and a logical procedure for searching the global optimum solution for decision makers were presented. In this way, this work provided an efficient method for decision makers in the design of the hybrid wind/solar/fuel cell system.     

Forecasting method of monthly wind power generation based on climate model and long short-term memory neural network

Predicting wind power generation over the medium and long term is helpful for dispatching departments, as it aids in constructing generation plans and electricity market transactions. This study presents a monthly wind power generation forecasting method based on a climate model and long short-term memory (LSTM) neural network. A nonlinear mapping model is established between the meteorological elements and wind power monthly utilization hours. After considering the meteorological data (as predicted for the future) and new installed capacity planning, the monthly wind power generation forecast results are output. A case study shows the effectiveness of the prediction method.     

Modelling of a domestic wind power system including storage

A simulation analysis is presented of domestic heating by a wind power system including storage at a location 54°39′ N, 6°13′ W (Aldergrove, Northern Ireland). A simple theoretical model is constructed comprising a house of specified dimensions and heat loss characteristics, an aerogenerator and a thermal store. the data base used is a magnetic tape of hourly wind speed and air temperature readings taken at Aldergrove meteorological station during 1949–75. the results suggest a measure of optimization between store capacity and generator rating based on technical considerations alone, and a simple economic optimization is also presented.     

Short-term optimal wind power generation capacity in liberalized electricity markets

Mainly because of environmental concerns and fuel price uncertainties, considerable amounts of wind-based generation capacity are being added to some deregulated power systems. The rapid wind development registered in some countries has essentially been driven by strong subsidizing programs. Since wind investments are commonly isolated from market signals, installed wind capacity can be higher than optimal, leading to distortions of the power prices with a consequent loss of social welfare. In this work, the influence of wind generation on power prices in the framework of a liberalized electricity market has been assessed by means of stochastic simulation techniques. The developed methodology allows investigating the maximal wind capacity that would be profitably deployed if wind investments were subject to market conditions only. For this purpose, stochastic variables determining power prices are accurately modeled. A test system resembling the size and characteristics of the German power system has been selected for this study. The expected value of the optimal, short-term wind capacity is evaluated for a considerable number of random realizations of power prices. The impact of dispersing the wind capacity over statistical independent wind sites has also been evaluated. The simulation results reveal that fuel prices, installation and financing costs of wind investments are very influential parameters on the maximal wind capacity that might be accommodated in a market-based manner.