基于贝叶斯网络算法的发电系统可靠性评估

Reliability Evaluation of Generation System Based on Bayesian Network Algorithms

提高发电机组的可用度和加大发电备用容量是提高发电系统稳定性的两个重要因素。通过建立发电容量模型,对发电系统的可靠性进行定量分析,先建立3台机模型,然后推断出4台机及其以上的容量模型。该模型检验结果基于贝叶斯网络,不仅能方便描述系统最大容量和负荷需求之间的平衡关系,而且系统失去负荷的概率和其他各种概率也能通过高效的贝叶斯网络推理算法进行有效计算。仿真结果证明,该模型操作简单,实际结果准确,精度较高,具有普遍的推广意义。

Improving the availability of generating units and increasing the reserve capacity of power generation are two important factors to improve the stability of power generation system. Through the establishment of power generation capacity model,the reliability of power generation system is quantitatively analyzed. Firstly,three machine models are established,and then four or more capacity models are deduced. The model test results are based on Bayesian network, which can not only describe the balance between the maximum capacity and load demand of the system,but also calculate the probability of system losing load and other probabilities through efficient Bayesian network reasoning algorithm. The simulation results show that the model is simple to operate ,accurate in actual results,high in accuracy,and has universal popularization significance.