根据元件故障与保护动作和断路器跳闸之间的内在逻辑关系，建立了面向元件的电网故障诊断模型，并采用误差反向传播的梯度下降法修正网络参数。该模型是一种由Noisy-Or、Noisy-And节点组成的特殊的贝叶斯网络，能够处理电网故障诊断中的不确定性，具有语义精确、推理快速、学习效率高等特点，适用于大规模电力系统的多重复杂故障诊断。实际电网故障案例验证了该方法的正确性和有效性。

本文介绍了一个已投入试运行的地区电网继电保护定值在线校验智能系统。根据地区电网的特点，采用面向对象和链表等指针型数据结构对电网进行表示和数据管理，提出了基于矩阵模型的厂站实时结线分析新方法；总结归纳了地区电网继电保护定值的校验规则,提出了不规则线路的保护灵敏度校验和保护配合校验的策略。以某地区电网为实验对象，对其相间距离、接地距离、零序电流保护的灵敏性和选择性进行了校验。

This paper proposes a cooperative protection system with a multi-agent system, which could adapt protection functions to the complicated changes in the power system automatically and intelligently. In the cooperative protection system, multi-agent system allows the cooperation between plural numbers of equipments. Some agents stay in one place and collect local power system information such as current and voltage data. Other agents move about to utilize data or functions installed in other equipment. The cooperation of multi-agent enables the flexible utilization of all hardware resources by any equipment, so that various adaptive protection functions are realized. Simulation of the proposed method has been applied to some typical protection function, i.e. overcurrent protection function. The results showed that the cooperative protection system could achieve the optimum protection capability. Although many practical aspects need to be thoroughly studied, it is quite promising to realize the adaptive protection using the multi-agent technology.

This paper describes a new power network topology processor which has been successfully used in two practical power system application programs. Artificial intelligence (AI) techniques have been used and this provides several advantages. AI's frame representation method is used to represent electric network configuration. This avoids manual numbering on a large amount of circuit breaker terminals/circuits. Rule-based method has been adopted for substations' bus configuration analysis instead of the search method. This makes the analysis simple and adaptable to new types of bus configurations just by adding corresponding rules. AI's search techniques have been applied for network graph search making the search algorithm simpler and easier to be programmed. Some results from the application of the proposed topology processor are also included in the paper.

The framework of an assessment system on transformers' condition is proposed in this paper through mainly using data mining techniques. Moreover, a warehouse is used to collect transformers'testing data, and a multi-agent system is used to design the framework of the software. The present framework is open and flexible, so the objective system is easy to be developed and maintained. The system can support transformers' condition-based maintenance to reduce electric utility's cost. The condition of a transformer depends on its design, present and historical data relating to its installation environment, load amounts, being switched number and so on. Usually the off-line testing results, operational data, fault records and weather conditions have been stored in different systems, so finding an effective method to utilize all this information for condition assessment is difficult. Therefore, a data warehouse has been used to integrate all of the above data, and some data mining techniques have been used to find the pattern and trend of the condition of a transformer. Then whether it is healthy can be determined. In order to make the system open and flexible, Open Agent Architecture (OAA) is employed to compose the multiagent system. Seven application agents are designed to evaluate transformers' conditions synthetically. The Grey correlation method, grey theory prediction model GM (1,1), Bayesian network classifier and Bayesian network are employed in the agents.