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In this thesis, Discrete Integer Cuckoo Search Optimization Algorithm (DICS) is proposed for generating an Optimal Maintenance Schedule for power utility with multiple generator units and complex constraints of Man Power Availability, Load Demand and strict Maintenance Window. The objective is to maximize the levelness of the Reserve Power over the entire planning period while satisfying the multiple constraints. This is an NP hard problem and there is no unique solution available for it. Nature inspired Cuckoo Search algorithm has been chosen to address this problem. Cuckoo search algorithm is a metaheuristic algorithm based on the obligate brood parasitism of cuckoo bird species, where cuckoo tries to find the best nest of other birds whose eggs resemble her own to lay her eggs to be hatched by other birds. Therefore the problem is formulated to find the best host nest. The host nest is defined according to the constraints of the power utility.The algorithm was tested on two test systems, one with 21 generator units and the other with 9 generator units which is called IEEE RTS test system. The results obtained with the DICS on the 21 generator power utility system are compared with the work of previous researchers using the same test system and using the five traditional algorithms namely the Genetic Algorithm with Binary Representation (GABR), Genetic Algorithm with Integer Representation (GAIR), Discrete Particle Swarm Optimization (DPSO), Modified Discrete Particle Swarm Optimization (MDPSO) and Hybrid Scatter Genetic Algorithm (HSGA). The results obtained by applying DICS on the IEEE RTS test system are compared with HSGA algorithm. The results show that DICS outperformed all the other algorithms in the two test systems. |
