Intelligent Economic Alarm Processor (IEAP)



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The advent of electricity market deregulation has placed great emphasis on the availability of information, the analysis of this information, and the subsequent decision-making to optimize system operation in a competitive environment. This creates a need for better ways of correlating the market activity with the physical grid operating states in real time and sharing such information among market participants. Choices of command and control actions may result in different financial consequences for market participants and severely impact their profits.

This work provides a solution, the Intelligent Economic Alarm Processor to be implemented in a control center to assist the grid operator in rapidly identifying the faulted sections and market operation management.

The task of fault section estimation is difficult when multiple faults, failures of protection devices, and false data are involved. A Fuzzy Reasoning Petri-nets approach has been proposed to tackle the complexities. In this approach, the fuzzy reasoning starting from protection system status data and ending with estimation of faulted power system section is formulated by Petri-nets. The reasoning process is implemented by matrix operations.

Next, in order to better feed the FRPN model with more accurate inputs, the failure rates of the protections devices are analyzed. A new approach to assess the circuit breaker?s life cycle or deterioration stages using its control circuit data is introduced. Unlike the traditional ?mean time? criteria, the deterioration stages have been mathematically defined by setting up the limits of various performance indices. The model can be automatically updated as the new real-time condition-based data become available to assess the CB?s operation performance using probability distributions.

The economic alarm processor module is discussed in the end. This processor firstly analyzes the fault severity based on the information retrieved from the fault section estimation module, and gives the changes in the LMPs, total generation cost, congestion revenue etc. with electricity market schedules and trends. Then some suggested restorative actions are given to optimize the overall system benefit. When market participants receive such information in advance, they make estimation about the system operator's restorative action and their competitors' reaction to it.