Fuzzy Artificial Immune System based Generators Preventive Maintenance Scheduling

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Abstract
Preventive Maintenance Schedule (PMS) is a technique used for the scheduling of electric generators in power systems. PMS increases system reliability, and decreases the overall system production and maintenance costs. Recently, expert systems, fuzzy logic sets, simulated annealing, genetic algorithms, and evolutionary programming were developed and used to solve PMS problems. In this work, a new technique based on a fuzzy artificial immune system is used to solve the PMS problem. The fuzzy logic is used to handle the uncertainty associated with the PMS problem, such as the uncertainty in load, production cost, and the spinning reserve. The idea is to mimic the human immune system response due to an antigen attack. Once feasible solutions (candidates) are determined, the fuzzy technique will be applied to identify the candidate that best satisfies the constraints related to the PMS problem. Results from the proposed technique were compared with complementary decision variable technique to check the efficacy of the fuzzy immune system technique. Test results demonstrate the viability of the proposed technique to solve the PMS problem considering uncertainties.