This paper presents an overview of existing research on wind speed and power forecasting. It first discusses state-of-the-art wind speed and power forecasting approaches. Then, forecasting accuracy is presented based on variable factors. Finally, potential techniques to improve the accuracy of forecasting models are reviewed. A full survey on all existing models is not presented, but attempts to highlight the most promising body of knowledge concerning wind speed and power forecasting.

Current status and future advances for wind speed and power forecasting

An operational matrix of integration based on Haar wavelets is established, and a procedure for applying the matrix to analyse lumped and distributed-parameters dynamic systems is formulated. The technique can be interpreted from the incremental and multiresolution viewpoint. Crude as well as accurate solutions can be obtained by changing the parameter m; in the mean time, the main features of the solution are preserved. Several nontrivial examples are included for demonstrating the fast, flexible and convenient capabilities of the new method.

Haar wavelet method for solving lumped and distributed-parameter systems

Methanol is an alternative, renewable, environmentally and economically attractive fuel; it is considered to be one of the most favorable fuels for conventional fossil-based fuels. Methanol has been recently used as an alternative to conventional fuels for internal combustion (IC) engines in order to satisfy some environmental and economical concerns. Because of a number of relatively large research projects that have been ongoing recently, much progress has been made that is worth reporting. This paper systematically describes the methanol productions, including the productions from coal, natural gas, coke-oven gas, hydrogen, biomass etc. It introduces the potentials of methanol as a renewable resource taking into account the world supply and demand, economic benefits and the effects on human health and the environment. Thirteen methods of application such as methanol/gasoline, methanol/diesel blends which can be used on the IC engines are summarized. Finally, this paper puts forward some new suggestions on the weakness in the researches of methanol engine.

An overview of methanol as an internal combustion engine fuel

Large intermittent generations have grown the influence on the grid security, system operation, and market economics. Although wind energy may not be dispatched, the cost impacts of wind can be substantially reduced if the wind energy can be scheduled using accurate wind forecasting. In other words, the improvement of the performance of wind power forecasting tool has significant technology and economic impact on the system operation with increased wind power penetration. Forecasting has been a vital part of business planning in today's competitive environment, especially in areas characterized by a high concentration of wind generation and a limited capacity of network. The target of this paper is to present a critical literature review and an up-to-date bibliography on wind forecasting technologies over the world. Various forecasting aspects concerning the wind speed and power have been highlighted. These technologies based on numeric weather prediction (NWP) methods, statistical methods, methods based upon artificial neural networks (ANNs), and hybrid forecasting approaches will be discussed. Furthermore, the difference between wind speed and power forecasting, the lead time of forecasting, and the further research will also be discussed in this paper.

A literature review of wind forecasting technology in the world

Application of artificial neural networks for the wind speed prediction of target station using reference stations data

A general expression of the Fourier operational matrix of integration P is derived which is analogous to that previously derived for other types of orthogonal functions such as Walsh, block-pulse, Laguerre, Legendre and Chebyshev. This matrix P may be used to solve problems like identification, analysis and optimal control.

The Fourier series operational matrix of integration

A method for establishing wind speed correlation between neighboring measuring stations is presented in this paper. The aim of this study is to develop a model, in which given the wind speed at a particular site to simulate the wind speed at another, nearby site, in order to estimate the wind power of an area. This method takes into account the evolution of the sample cross correlation function (SCCF) of wind speed in time domain and uses an artificial neural network to perform the wind speed simulation. Four separate pairs of wind data measuring stations at two different regions were examined. Tests showed that the higher the SCCF value between two sites, the better simulation achieved. Also, in a pair of stations under investigation the reference station must be the one that contains more information in its wind speed signal, in order to obtain the optimum simulation performance.

Correlation of wind speed between neighboring measuring stations

The problems of system identification, analysis and optimal control have been recently studied using orthogonal functions. The specific orthogonal functions used up to now are the Walsh, the block-pulse, the Laguerre, the Legendre, the Chebyshev, the Hermite and the Fourier functions. In the present paper solutions to these problems are derived using the Taylor series expansion. The algorithms proposed here are similar to those already developed for the orthogonal functions; however, due to the simplicity of the operational matrix of integration, the Taylor series presents considerable computational advantages compared with the other polynomial series, provided that the input and the output signals may be assumed to be analytic functions of t .

Taylor series approach to system identification, analysis and optimal control

Behavior of a Small Four-Stroke Engine Using as Fuel Methanol - Gasoline Mixtures

The Taylor series is used for the analysis of time-varying linear systems with the introduction of the product matrix of the Taylor polynomial vector and its transpose. For the solution of the optimal control problem, the operational matrix of backward integration for the Taylor series is introduced. In this way, the state transition matrix of optimal control of linear systems with quadratic performance index may be integrated approximately via Taylor series. The results obtained indicate an excellent agreement with the exact solution for a small number of terms.

Panagiotis D. Sparis

Papers

The Fourier series operational matrix of integration

Correlation of wind speed between neighboring measuring stations

Taylor series approach to system identification, analysis and optimal control

Behavior of a Small Four-Stroke Engine Using as Fuel Methanol - Gasoline Mixtures

Analysis and optimal control of time-varying linear systems via Taylor series