• 제어로봇시스템학회논문지
• /
• 제19권1호
• /
• pp.34-39
• /
• 2013

This paper proposes the implementation of robust fuzzy controller for designing intelligent wind farm and mitiagating the fluctuation of wind power generator. The existing researches are limited to individual wind turbine with variable speed so that it is necessary to study the multi-agent wind turbine power system. The scopes of these studies include from the arrangements of each power turbine to the control algorithms for the wind farm. For solving these problems, we introduce the composition of intelligent wind farm and use the T-S (Takagi-Sugeno) fuzzy model which is suitable for designing fuzzy controller. The control object in wind farm enables the minimizing the fluctuation of wind power generator. Simulation results for wind fram which is modelled as mathematically are demonstrated to visualize the feasibility of the proposed method.

• 제어로봇시스템학회논문지
• /
• 제20권1호
• /
• pp.22-28
• /
• 2014

This paper proposes the fuzzy modeling and robust stability analysis of wind farm based on prediction model for wind speed. Owing to the sensitivity of wind speed, it is necessary to study the dynamic equation of the variable speed wind turbine. In this paper, based on the least-square method, the wind speed prediction model which is varied by the surrounding environment is proposed so that it is possible to evaluate the practicability of our model. And, we propose the composition of intelligent wind farm and use the fuzzy model which is suitable for the design of fuzzy controller. Finally, simulation results for wind farm which is modeled mathematically are demonstrated to visualize the feasibility of the proposed method.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제12권2호
• /
• pp.108-112
• /
• 2012

A sustainable production of electricity is essential for low carbon green growth in South Korea. The generation of wind power as renewable energy has been rapidly growing around the world. Undoubtedly wind energy is unlimited in potential. However, due to its own intermittency and volatility, there are difficulties in the effective harvesting of wind energy and the integration of wind power into the current electric power grid. To cope with this, many works have been done for wind speed and power forecasting. It is reported that, compared with physical persistent models, statistical techniques and computational methods are more useful for short-term forecasting of wind power. Among them, support vector regression (SVR) has much attention in the literature. This paper proposes an SVR based wind speed forecasting. To improve the forecasting accuracy, a fuzzy clustering is adopted in the process of SVR modeling. An illustrative example is also given by using real-world wind farm dataset. According to the experimental results, it is shown that the proposed method provides better forecasts of wind power.

• 한국태양에너지학회 논문집
• /
• 제33권6호
• /
• pp.70-76
• /
• 2013

Recently industrial control systems have been required to ensure intelligent, high tech automation, interconnection and interoperability demands. Therefore, there is a need to redefine the structure concepts of SCADA system for wind power. Also, at this time, the integrated management system is required for the distributed development of wind farms where are needed often interoperability features and exchange information between different wind farms, wind turbines or SCADA systems. In this paper, an integrated structural concepts for SCADA system are defined. Based on this definition of an integrated SCADA system, the basic designs are analyzed on physical layer, system layer and application layer which are corresponded to wind turbine controller, the SCADA server and the SCADA client, and implement HMI. Between the implementation SCADA server and the client, their normal functions were verified at the small scale wind energy test facilities.