Invited ReviewMaintenance scheduling in the electricity industry: A literature review
Introduction
The production of movement, heat, or light needs a common input: energy. Energy can be produced from fuel (e.g., oil, gasoline, uranium, gas, coal, wood) or natural forces (e.g., wind, water). The consumption of energy is growing with the development of countries and the increasing world population, and the production must meet this demand. Therefore, the reliability of power plants, and wind and solar farms is extremely important. In this context, equipment maintenance management is a major economic issue. Just to cite few examples, equipment maintenance management in electric power systems is concerned with decisions such as: when to stop a generating unit for maintenance, when to re-start it again, and how much resources (e.g., technicians) are to be assigned to the maintenance of a given unit during a given period. These decisions are taken under complex environments and constraints such as resource availability, demand satisfaction, and reliability thresholds.
One of the most successful contributions of operations research to improve decision making in equipment maintenance management is the application of optimization techniques to solve maintenance planning and scheduling problems. In the particular case of electric power systems, these problems range from simple technician-equipment assignments to complex problems considering interactions between different stakeholders and uncertainty in the problem parameters. In this paper, we build on the work of Yamayee (1982), Kralj and Petrović (1988), Dahal (2004), Khalid and Ioannis (2012) to update the state-of-the-art and provide a global overview of the current stream of research in the field. To make the document easier to read, the various acronyms used in this paper are summarized in Table 1.
The paper is organized as follows. Section 1 presents a brief description of the energy industry, Section 2 reviews maintenance scheduling problems rising in regulated and deregulated environments, Section 3 discusses existing solution methods for these problems, and Section 4 concludes the paper and outlines research perspectives.
Section snippets
The energy industry
The energy industry carries out three activities: production, transmission, and distribution. Traditionally the industry is organized in a centralized, vertically integrated way (see Fig. 1): a single company has a monopoly of the entire system in its area of operation. However, the government regulates the situation directly or indirectly: the entity must not take advantage of the end consumer. Therefore, the term regulated monopoly utilities is also used. With the deregulation of the
Maintenance in the electricity industry
Maintenance represents the actions required to ensure that a product provides reliable service. Maintenance can be split into two categories: corrective and preventive. Corrective maintenance is performed after a breakdown. Preventive maintenance is performed at predetermined intervals or according to prescribed criteria and intended to reduce the probability of failure. Maintenance in the electricity industry concerns generating units and transmission lines; the horizon can be long-term or
Solution methods
Various heuristic and exact approaches have been proposed for the GMS and/or TMS problems. The solution techniques mainly focus on metaheuristics and mathematical programming. This section provides details about all these techniques and discusses their applicability to the problems defined in the previous sections. To provide a global overview, Table A1 classifies the references according to the solution method they apply.
Conclusion and perspectives
The GMS and TMS problems are the two main maintenance scheduling problems in the electricity industry. The constraints concern the maintenance tasks (time windows, incompatibility, sequence), the resource requirements, the reliability, and the demand satisfaction. Sometimes, e.g., for nuclear power plants, fuel consumption management is required. The GMS and TMS problems can be solved jointly or network constraints can be introduced into the former. Production planning is often incorporated
References (89)
- et al.
Source and transmission line maintenance outage scheduling in a power system using teaching learning based optimization algorithm
Applied Soft Computing
(2014) Application of Benders’ decomposition to power plant preventive maintenance scheduling
European Journal of Operational Research
(2008)- et al.
Modelling generator maintenance scheduling costs in deregulated power markets
European Journal of Operational Research
(2015) - et al.
Generator maintenance scheduling using a genetic algorithm with a fuzzy evaluation function
Fuzzy Sets and Systems
(1999) - et al.
Generator maintenance scheduling in power systems using metaheuristic-based hybrid approaches
Electric Power Systems Research
(2007) - et al.
A multipopulation cultural algorithm for the electrical generator scheduling problem
Mathematics and Computers in Simulation
(2002) - et al.
An improved robust model for generator maintenance scheduling
Electric Power Systems Research
(2012) - et al.
A tabu search algorithm for maintenance scheduling of generating units
Electric Power Systems Research
(2000) Clonal selection algorithm for power generators maintenance scheduling
International Journal of Electrical Power & Energy Systems
(2014)- et al.
A fuzzy evolutionary programming-based solution methodology for security-constrained generation maintenance scheduling
Electric Power Systems Research
(2003)