Power system protection is important for service reliability and quality assurance. Various faults may occur due to natural and artificial calamity. To reduce the outage duration and promptly restore power services, fault section estimate has to be done effectively and accurately with fault alarms. Dispatchers study the changed statuses of protection devices from the Supervisory Control and Data Acquisition (SCADA) system to identify the fault. Single and multiple faults could coexist with the failed operation of relays and circuit breakers, or with the erroneous data communication. It needs a long time to process a large number of alarms under various conditions involving multiple faults and many uncertainties. To cope with the problem, an effective tool is helpful for the fault section estimation and alarm processing. Besides, power transformer plays a major role in a power system. For a better service quality, it is important to be routinely examined for detecting incipient faults inside transformers. Preventive techniques for early detection can find out the incipient faults and avoid outages. Power quality is another issue to considerable attentions from utilities and customers due to the popular uses of many sensitive electronic equipment. Harmonics, voltage swell, voltage sag, and, power interruption could downgrade the service quality. To ensure the power quality, detecting harmonic and voltage disturbances becomes important. A detection method with classification capability will be helpful for detecting disturbances. This dissertation developed various algorithm for detection including fault section detection, alarm processing, transformer fault diagnosis, and power quality detection. For a well-dispatched power system, the adaptive detection idea will be used, and the existing SCADA/EMS will be integrated without extra devices.