نسل برنامه ریزی تعمیر و نگهداری در سیستم های قدرت با استفاده از بهینه سازی کلونی مورچه ها برای دامنه های پیوسته بر اساس برنامه ریزی عدد صحیح 0-1

In this paper, we present a formulation that enables Ant Colony Optimization for Continuous Domains (ACOR) to seek the optimal solution of the unit maintenance scheduling problem. ACOR is a direct extension of Ant Colony Optimization (ACO). Also it is the significant ant-based algorithm for continuous optimization. For the maintenance scheduling, cost reduction is as important as reliability. The objective function of this algorithm considers the effect of economy as well as reliability. Various constraints such as spinning reserve, duration of maintenance crew are being taken into account. The ACOR formulation developed is applied on a power system with six generating units. The simulation result of this technique is compared with those reported in literature. The outcome is very encouraging and proves that the authors’ proposed approach outperforms them in terms of reaching a better optimal solution and speed.

The power station maintenance department exists to help the production function to maximize plant reliability, availability and efficiency by determining both short and long term maintenance requirements and by carrying out the work accordingly. This includes work to comply with statutory and mandatory requirements and investigations into plant problems. The department has to make the most economic use of its available resources; this is achieved, in part, by having a level of staff (engineering, supervisory, craft) to deal with the general day-to-day steady workload and by making alternative arrangements to cater for work load peaks (Mohammadi Tabari, Pirmoradian, & Hassanpour, 2008). To achieve the above goal, periodic servicing must take place and normally falls under the following items (Mohammadi Tabari et al., 2008): (1) Planned maintenance: overhaul, preventive maintenance. (2) Unplanned maintenance: emergency maintenance. Preventive maintenance is expensive. It requires shop facilities, skilled labor, keeping records and stocking of replacement parts. However, the cost of downtime resulting from avoidable outages may amount to ten or more times the actual cost of repair. The high cost of downtime makes it imperative to economic operation that maintenance be scheduled into the operating schedule (Mohammadi Tabari et al., 2008). The maintenance scheduling problem is to determine the period for which generating units of an electric power utility should be taken off line for planned preventive maintenance over the course of a 1 or 2 year planning horizon, in order to minimize the total operating cost while system energy, reliability requirements and a number of other constraints are satisfied (Marwali and Shahidehpour, 1998a and Marwali and Shahidehpour, 1998b).

This paper introduces 0–1 Integer Programming based on the ACORACOR for finding an optimal generation maintenance schedule. The purpose of objective function is to make units maintain as earlier as possible. The authors’ proposed technique has been tested on a power system with six generating units. The obtained result of this technique is compared with other optimization methods; the result indicates its superiority. Based on this study, ACORACOR can be applied satisfactorily to different types of optimization problems in the area of power systems.