A Pattern Recognition and Associative Memory Approach to Power System Security Assessment

Abstract
As the cost of computer memory continues to decline faster than that of processors, it may be realistic to effectively apply pattern recognition methodology to security evaluation of an electric power system. Efficient implementation techniques are developed to achieve assessment in real time with a modest level of memory requirement. The basic idea is to recognize the unknown security of a particular system state operation from stored knowledge about similar operating patterns. Two efficient data structures are proposed here for its implementation. First, a distributed memory device, an associative memory is developed for recognition. This particular memory is found to be capable of parallel pattern matching along with reduced computer storage. Second, for an efficient implementation of the memory structure, these associative memories are configured in a hierarchical structure which not only expands storage capacity but also utilizes the speed of tree search. This structure provides a basis of an error-free, rapid, and memory-saving recognition algorithm.