Xiaozhong Liao

Wind power prediction using wavelet transform and chaotic characteristics

In the electricity system, supply and demand must be equal at all times. Wind power generation is fluctuating due to the variation of wind. As more and more wind power generation is integrated into the power system, it is very important to predict the wind power production to contribute the system reserve reduction and the operational costs of the power plants. This paper brings wavelet transform into the time series of wind power and verifies that the decomposed series all have chaotic characteristic, so a new method of wind power prediction in short-term with Artificial Neural Network (ANN) model based on wavelet transform is presented. To test the approach, the wind power data from the Fujin wind farm and Saihanba wind farm of China are used for this study. The prediction results are presented and compared to the no wavelet transform method and ARMA method. The results show that the new method based on wavelet transform neural networks will be a useful tool in wind power prediction.

Studies on wind farms ultra-short term NWP wind speed correction methods

Ultra-short term wind speed forecast for wind farm is of great significance to the real-time scheduling of wind power system. In this paper, NWP (Numerical Weather Prediction) wind speed time series and measured wind speed time series were decomposed into different bands by wavelet multi-resolution analysis. Pearson product-moment correlation coefficient was used to verify the correction premise. Then the linear correction method was used to correct the low frequency stationary NWP wind speed. To test the approach, the data from Yilan wind farm of Heilongjiang province were used. The results show that when a strong correlation exists in the system deviation of training periods and testing periods, the prediction accuracy of ultra-short term wind speed will be significantly improved.

Game theory applied on step-priced micro grid

In this paper, a micro grid price mechanism is discussed and optimised. Operators can increase the consumerss profile under step-price environment. With a novel low-carbon strategy designed in this paper, consumers make ones own decision whether to buy or sell energy with what price. By using this strategy, energy distribution can be optimised and the utilization of clean power will increase. A simulation is conducted to prove the robustness and effectiveness of the strategy.

Non-grid-connected wind power generating system with permanent magnet synchronous generator and buck/boost converter

In this paper, a distributed generation wind energy conversion system based on non-grid-connected and using a direct-drive permanent magnet synchronous generator (DD-PMSG) is proposed with a dual-loop PI controller. This energy system is suitable for applications in remote areas not connected to the grid such as Radio Base Stations (RBS) for mobile phone communications. Analysis, simulation, and prototyping test results are presented.