Comparing Three Separate Discrete Algorithms for Generation Maintenance Optimization

In general, distribution, generation and transmission are the three primary parts of an electric power system. All of them are in need of maintenance to enhance the energy efficiency, stability and reliability of the comprehensive power system. Nowadays, the entrance of distributed generation into distribution networks has been significantly developed. Basic Maintenance Planning Scheduling (GMS) combinations focus on planning preventive maintenance for units over a period of one or two years to reduce total operating costs accompanied by meeting the energy of system requirements. In state-of-the-art power systems, the involvement of systems like budget constraints, combustion, demand, and crew for electricity have increased dramatically, as the system size has. Therefore, they have caused more generators and less reserve margin, complicating the problem of GMS. This research presents two models for a budget and a fixed security constraint model for the problems of scheduling preventive maintenance. To contain a more optimal program, a multi-objective function (reliability and cost-effective cost) is involved and resolved. For a rather pragmatic and complete study, a new manpower restriction, likewise relationship restriction to solve the function of multi-objective, is analyzed and proposed for the scheduling maintenance problem. This function is simulated by 3 optimization methods and the matters of population size and iterations are expressed and compared in GMS problem. An experimental system containing 21 generators is noticed for simulation and the accuracy of the results in our case study indicates the capability of DPSO optimization algorithm for scheduling maintenance and other economic and crew constraints.