The Study Of The Elecricity Market Operation Mode And Market Clearing Price Forecasting

In today's world,a profound transform of electric power industry mechanisms is taking place. Its inevitable trend is breaking monopoly,inducing competition and setting up a uniform, normative,open,orderd and competitive electricity market. China attempted to have a reformation of electric power market in 1990s,breaking the traditional integrative management mode,and carrying out separation of net and plant, transition and distribution. How to establish corresponding elecricity market operation mode rationally and how to use the relative historic data to forecast the future market clearing electricity price is a very meaningful work for every participator in the power market.Firstly,The problem of establishing regional electric power market exchange pattern is researched thoroughly in the paper. After compared of several typical electric power market exchange patterns worldwide,the principle of regional power market trading mode is put forward. In this paper, China power market's orientation, structure and possible bilateral exchange manner are analyzed and discussed. And the regional power markets of wholesale competition model in China is designed in the paper. The purpose of this paper is to exploratory research the reformational orientation and the operational manner of China power market and optimal bidding strategies for participants in future market.Secondly,The electric power market pricing mechanism is introduced, and the establishment and the influence factors of the electricity price are discussed. According to actual market clearing price's data,vary and distributing character of MCP data is researched.we obtained that different period data of MCP have different time series characteristic,the change of MCP have different trend. So the forecasting MCP idea based on period of time is put forward. Then, analyzed and compared the adventages and disadventages of some current forecasting methods, the forecasting models of market clearing price is proposed. To improve the accurary of price forecasting,two aspects of improvements are proposed:(1)selector of the factors which can show the change of the price sequence accurately;(2)the pretreatment of the input variables.Two price forecasting model using Support Vector Machine is proposed: (1)similarity searching technique is applied to building the training set and input variables .The electricity price of next day is forecasted successfully by this model. The precision of forecasting based on similarity searching technique is higher than traditional methods.(2)The forecasting price model based on Wavelet Transform and Support Vector Machine is proposed. Selected of appropriate wavelet basis and decomposition scale, the market clearing price series is decomposed into one low-frequency and some high-frequency sub-series in the wavelet domain,So MCP feature is extracted form the market clearing price series. Using each new component of the original electricity price signal, LSSVM forecasting models for each sub-series is independently set up, then adding up to the forecasting results of all sub-series, the whole forecasted electricity price series are obtained. The results of forecasting show that this model impove the forecasting accurate of MCP remarkablly.