A Mathematical Program for Scheduling Preventive Maintenance of Cogeneration Plants with Production

Abstract

This paper considers the scheduling of preventive maintenance for the boilers, turbines, and distillers of power plants that produce electricity and desalinated water. It models the problem as a mathematical program (MP) that maximizes the sum of the minimal ratios of production to the demand of electricity and water during a planning time horizon. This objective encourages the plants’ production and enhances the chances of meeting consumers’ needs. It reduces the chance of power cuts and water shortages that may be caused by emergency disruptions of equipment on the network. To assess its performance and effectiveness, we test the MP on a real system consisting of 32 units and generate a preventive maintenance schedule for a time horizon of 52 weeks (one year). The generated schedule outperforms the schedule established by experts of the water plant; it induces, respectively, 16% and 12% increases in the surpluses while either matching or surpassing the total production. The sensitivity analysis further indicates that the generated schedule can handle unforeseen longer maintenance periods as well as a 120% increase in demand—a sizable realization in a country that heavily relies on electricity to acclimate to the harsh weather conditions. In addition, it suggests the robustness of the schedules with respect to increased demand. In summary, the MP model yields optimal systematic sustainable schedules.

Hybrid Genetic Algorithm and Tabu Search for Solving Preventive Maintenance Scheduling Problem for Cogeneration Plants

“…Many experiments were applied to find the optimal or near optimal solution through the following factors: number of chromosomes in each population CR, general iteration 𝛿 , internal iteration 𝛼, method of genes selection, and the value of the tenure 𝛾 of Tabu list. It is important to mention before starting with the details that the results of the proposal approach have been compared with the two published articles, [25] and [26] that used optimal method, IP and NLIP, for the same case.…”

“…To prove the effectiveness of the proposed structure, IEEE Reliability Testing System (RTS) was used, with promising results. Al-Hamad et al [25] provided a paper for PMS on a real case study of 32-unit system of boilers, turbines and distillers for power plants in the State of Kuwait. The problem is formulated as a Mathematical Program (MP) that increases minimum output to demand ratios, for a period of 52 weeks.…”

“…A hybrid Genetic Algorithm and Tabu Search would be the methodology to tackle this problem, as the study provides the PMS for each piece of equipment in the power plant, for time period of 12 months. The results will be compared with the results of the previous optimization approaches [25,26] in order to measure the quality of this methodology, in terms of solution quality and implementation time. Certain constraints will be taken into account, such as maintenance window restrictions, maintenance duration for each equipment, the level of reservoir water limits, etc.…”

Nonlinear Integer Programming for Solving Preventive Maintenance Scheduling Problem for Cogeneration Plants with Production

“…Equation (18) ensure that every boiler maintenance must occur in the specified time window for starting maintenance, likewise for Equation (19) for turbines and Equation (20) for distillers. Constraint (21) calculates the available production of electricity, and Constraint (22) calculates the available production of water. Constraint (23) calculates the gap between available production and the demand for electricity, while Constraint (24) calculates the gap between available production and the demand for water.…”

“…In addition, factories [15][16][17][18][19] that contain machines and devices used in industry need preventive maintenance. Moreover, oil companies and power stations apply PM for their equipment [20][21][22][23][24]. The purpose of the PMS function is clearly to contribute to achieving the goals of the organization, which, in turn, requires the need for practical maintenance to be consistent with the organization objective.…”