Benchmarks for maintenance scheduling problems in power generation

Hydro and thermal power plants are planned to reduce the overall operation cost of the thermal power plants by optimally allocating the hydro units and thermal units in the power generation system. In this research work a combined particle swarm optimization (PSO) and improved bacterial foraging algorithm (IBFA) is proposed for short term hydro thermal scheduling (STHTS) with prohibited operating zones (POZs). The PSO algorithm yields the fastest convergence rate and possesses maximum capability of finding the global optimal solutions to the HTS (Hydro Thermal Scheduling) problems. Also BFA has succeeded in solving several issues in optimization, but it demonstrates poor convergence characteristics for large-scale issues such as the STHTS problem. Critical improvements to the basic BFA are implemented to tackle this complex issue in view of its high-dimension search space. The chemotactic step is changed in IBF, so that the convergence becomes dynamic rather than static. The combined PSO-IBF algorithm is assessed on a typical power generation plants consists of a hydroelectric power plant and an equivalent thermal power plant with a time slot of six 12-hour intervals and simulated using the MATLAB software. The simulation result shows that the combined PSO-IBF algorithm yields minimum cost value and optimal convergence rate than the existing algorithms.

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A zero-one integer programming for preventive maintenance scheduling for electricity and distiller plants with production

Journal of Quality in Maintenance Engineering ◽

10.1108/jqme-12-2018-0102 ◽

2019 ◽

Vol 26 (4) ◽

pp. 555-574

Author(s):

Khaled Alhamad ◽

Mohammad Alhajri

Keyword(s):

Integer Programming ◽

Preventive Maintenance ◽

Programming Model ◽

Practical Method ◽

Maintenance Scheduling ◽

Scheduling Problems ◽

Cogeneration Plant ◽

Content Type ◽

Proposed Model ◽

Effective Decision Making

Purpose The purpose of this paper is to describe a method that has been set up to schedule preventive maintenance (PM) tasks for power and water plants with all constraints such as production and maintenance. Design/methodology/approach The proposed methodology relies on the zero-one integer programming model that finds the maximum number of power and water units available in separate generating units. To verify this, the model was implemented and tested as a case study in Kuwait for the Cogeneration Station. Findings An effective solution can be achieved for scheduling the PM tasks and production at the power and water cogeneration plant. Practical implications The proposed model offers a practical method to schedule PM of power and water units, which are expensive equipment. Originality/value This proposed model is an effective decision-making tool that provides an ideal solution for preventive maintenance scheduling problems for power and water units in a cogeneration plant, effectively and complies with all constraints.

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