A study on smoothing effect on output fluctuation of distributed wind power generation
ABSTRACT Wind power generation in Japan has shown a marked increase in recent years. This increase has aroused growing concerns about the adverse effects of wind power generation on power system control, operation, and planning, because wind power output cannot be controlled and fluctuates much more than that of the conventional power plants. However, if wind power generators am distributed over a wide area, a "smoothing effect" an output fluctuation of distributed wind turbines could be expected because of the stochastic nature of wind. This paper examines the smoothing effect of output fluctuation of dispersed wind turbines. The remits reveal that the output of a single wind turbine fluctuates almost its rated power in ten minutes and little smoothing effect is expected in a wind farm scale (i.e., within sum kilometers) for a period of 10 minutes. On the other hand, a smoothing effect can be expected for a wider area in 100 minutes.
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ABSTRACT: An important aspect related to wind energy integration into the electrical power system is the fluctuation of the generated power due to the stochastic variations of the wind speed across the area where wind turbines are installed. Simulation models are useful tools to evaluate the impact of the wind power on the power system stability and on the power quality. Aggregate models reduce the simulation time required by detailed dynamic models of multiturbine systems.In this paper, a new behavioral model representing the aggregate contribution of several variable-speed-pitchcontrolled wind turbines is introduced. It is particularly suitable for the simulation of short term power fluctuations due to wind turbulence, where steady-state models are not applicable.The model relies on the output rescaling of a single turbine dynamic model. The single turbine output is divided into its steady state and dynamic components, which are then multiplied by different scaling factors. The smoothing effect due to wind incoherence at different locations inside a wind farm is taken into account by filtering the steady state power curve by means of Gaussian filter as well as applying a proper damping on the dynamic part.The model has been developed to be one of the building-blocks of a model of a large electrical system, therefore a significant reduction of simulation time has been pursued. Comparison against a full model obtained by repeating a detailed single turbine model, shows that a proper trade-off between accuracy and computational speed has been achieved.Procedia CS. 01/2010; 1:269-278.
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ABSTRACT: Optimal configuration of energy storage type and capacity is a difficult problem of planning and designing of Energy Storage System which is constructed for distributed generation. To solve the problem, we develop the software PDESS. The functions of PDESS include data analysis, capacity optimization, structure design and scheme evaluation. Considering the system's economy and technical capabilities, PDESS can evaluate different schemes and compare them based on capacity optimization. This system provides a user-friendly interaction platform for comprehensive evaluation and decision- making on alternatives, which can combine both advantages of machine calculation and human experience. The software is developed under Visual Studio.Net environment, in which VB is adopted to develop visual interfaces and VC is used to implement background algorithms. The versatility and scalability is emphasized during development.01/2011;