基于大数据技术的智慧电厂竞价上网系统设计

Design of intelligent power plant bidding system based on big data technology

针对传统智慧电厂竞价上网系统没有明确电厂边际网损成本,导致存在预测电价误差大、效率低的问题,提出基于大数据技术的智慧电厂竞价上网系统。引入大数据技术采集智慧电厂竞价上网数据,通过构建电厂实时电价负荷模型确定电厂实时电价,利用边际网损系数法,计算电厂边际网损成本,采用微粒群算法实现电厂负荷优化调度,完成智慧电厂竞价上网系统的设计。实验结果表明,此次设计的智慧电厂竞价上网系统,预测电价误差更小、效率更高,实际应用效果更好。

In view of the problem that the marginal net loss cost of power plant is not clearly defined in the traditional smart power plant’s bidding system,which leads to large error in predicting electricity price and low efficiency,a smart power plant’s bidding system based on big data technology is proposed.Big data technology is introduced to collect the bidding data of smart power plants,the real-time electricity price of power plants is determined by constructing the real-time electricity price load model of power plants,the marginal network loss coefficient method is used to calculate the marginal network loss cost of power plants,and the particle swarm optimization algorithm is adopted to realize the optimal load scheduling of power plants,thus completing the design of bidding network system of smart power plants.The experimental results show that the design of the smart power plant bidding system,electricity price error prediction is smaller,more efficient,better practical application.