摘要
该文提出一种基于模块网络预测市场清算价格的模型。该模型通过模糊C均值聚类(FCM)算法,将输入空间“软”分割成若干区域,由局部专家负责提取特定域的特征,由集成单元的竞争混合机制输出结果,在减少了计算量的同时提高了预测精度,是突破传统全局预测模型的一种尝试。用美国加州电能交易所(CalPX)公布的真实数据得到的仿真结果令人满意。该模型为市场参与者制定投标策略提供了一种方法,也为市场管理者提供了一种监督市场力的工具。
An innovative method to forecast MCP based on a modular network is presented. The architecture consists of one integrating unit and several local experts. The integrating unit based on FCM algorithm soft-partitions the input space into several regions while the local experts specialize to learn only the regions for which they are responsible. The output is given by a competition mixture mechanism. The predictor reduces the learning workload, and promotes performance. Finally, a simulation on real-world data acquired from California PX web site is given. This model gives out an effective bidding strategy, and may be a useful tool for monitoring market power.
出处
《中国电机工程学报》
EI
CSCD
北大核心
2002年第8期44-48,共5页
Proceedings of the CSEE
关键词
模块网络
市场清算价格
预测模型
电力市场
电力工业
电力系统
power market
price forecasting
market Clearing Price (MCP)
modular network
fuzzy C-means algorithm (FCM)
clustering segmentation