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Artificial intelligence techniques in power systems by Kevin Warwick, Arthur O. Ekwue, Raj Aggarwal

By Kevin Warwick, Arthur O. Ekwue, Raj Aggarwal

Study in man made intelligence has constructed many ideas and methodologies that may be tailored or used on to remedy complicated strength process difficulties

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It holds for the entire AS; otherwise, the relationship holds only in scenarios represented by ER. Mutual exclusion If two rules R\ and Ri can not be instantiated by the same set of PWMEs then rules R\ and R2 are mutually exclusive. lf3Eoc:Eg fm(E{) * E{ = £i and Then Rules Ri and R2 are mutually exclusive, in the region ER = u ( E\ KJ E2 ). If ER Eg * the relationship is complete. 30 Artificial intelligence techniques in power systems Redundancy If the LHS and RHS of rules R\ and R2 are equivalent then rules R\ and R2 are redundant with respect to each other.

In the RETE algorithm, the region Q , is represented by the PWME. ) If there are m ATs in rule R, then the region in AS where attribute tests in the rule are satisfied (a node in a discrimination network) is given by Inter-condition Tests (IT) : An inter-condition test fails at a node iff the two PWMEs cannot satisfy the condition (denoted by the node) at any point in the AS. Let Q& be the region of AS where an IT involving attributes / and k is satisfied (P node in a discrimination network). If there are n ITs in a rule R, then the region in the AS where ITs in the rule are satisfied is given by QR = A > X P23 X ...

The breadth of applications spanned a wide spectrum, ranging from alarm processing, fault diagnosis, system restoration, remedial control and security assessment to planning and engineering tasks. The level of maturity of applications varies from software prototypes to practical systems in use in the power industry environment. The knowledge engineering techniques started with simplistic rule-based techniques and extended to more advanced techniques such as object-oriented design, qualitative reasoning, verification and validation methods, natural languages, multi-agent systems, and machine learning.

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