关键词: 电力市场, 发电企业, 负荷预测, LSSVM算法, 周气象特征, 周用电量

Abstract: With the deepening of the reform of electric power system and the vigorous development of electric power market, a more refined electricity consumption forecast is required by power generation enterprises in order to make a reasonable powergeneration plan and a market bidding strategy. A prediction method for weekly electric power consumption is proposed based on Least Squares Support Vector Machine (LSSVM) and shortterm electricity consumption forecast.Fully considering the periodicity and continuity of the electricity demand, weekly meteorological characteristics are added into the model input,which makes up for the shortcomings of traditional power forecasting models that only consider historical electricity quantity and cannot accurately predict shortterm power trends during great weather changes. The model proposed can meet the demand of a more refined electric quantity prediction in commercialized electric power market.It is of great practicability.

Key words: electricity market, power generation enterprises, load forecast, LSSVM algorithm, weekly meteorological characteristics, weekly electricity consumption