یک مدل برای برنامه ریزی تعمیر و نگهداری پیشگیرانه در نیروگاه های برق از جمله مزارع بادی

This paper considers the problem of Power Plant Preventive Maintenance Scheduling (PPPMS). The goal is to evaluate which generators must stop production to be checked periodically for safety reasons. Preventive maintenance is crucial because a failure in a power plant may cause a general breakdown in an electric grid. This situation might result in a disruption of electric service to customers. The objective is to perform the problem of PPPMS from a reliability perspective, so the reliability of the system is maximized. The model presented considers the integration of wind power plants or wind farms into a traditional electric generating system comprising thermal, hydroelectric, and nuclear power units. The resulting model is categorized as an optimization problem. A case study based on a real power system is presented. Its main objective is to validate the efficiency of the proposed analysis.

The aim of a power plant in a power system is to supply the electric demand in an economical, reliable, and environmentally acceptable way. Various power plants can meet these requirements in different ways. This paper addresses the problem of power plant preventive maintenance scheduling (PPPMS). The main task is to determine the period for which generators of an electric system should be stopped for planned preventive maintenance over a certain time horizon. This problem is classified in the long-term exploitation of electric energy production systems [1]. Several types of power plants are considered here: wind, thermal, hydroelectric, and nuclear power plants. Incorporating wind power into an electric system makes the problem of PPPMS more realistic, given current energy production circumstances. In general for complex systems, e.g., electric systems, maintenance does not necessarily mean replacing the whole system. It often includes the repair or replacement of a part of the system. There are many preventive maintenance policies [2], [3] and [4]. For power plants, preventive maintenance consists of periodic inspection to detect potential failures. This planned maintenance is designed to extend the useful life by minimizing breakdowns and depreciation during normal operation. The amount of preventive maintenance needed at a power plant depends on many factors, such as technical, human, and operations. Considering that power plants are integrated into a global electric system, an unforeseen failure could affect the whole system, and cause an undesirable break in the electric supply. Immediate customer complaints would be unavoidable. Different authors have addressed the issue of planning of power plant preventive maintenance. They have introduced models of the problem and methodologies such as heuristic techniques [5], mixed integer programming [6], stochastic programming [7], decomposition methods [8], fuzzy methods [9], tabu search [10], multiobjective optimization [11], or hybrid approaches [12]. To date, most related industries have been unable to achieve highly efficient maintenance decisions because decision-making employs historical data rather than optimization processes. In addition, wind power plants have not been sufficiently considered in the problem of PPPMS. An approach based on reliability centered maintenance is proposed in order to select a suitable maintenance strategy. To maintain efficiency, power plants must be disconnected periodically to review how well they function. The consequence is an increase in reliability. The resulting optimization problem of this study is framed as 0/1 mixed integer linear programming. The topic touches on both traditional power plant management as well as concurrent wind generating systems. In addition, a case study based on a real power system is depicted in order to validate the efficiency of the proposed analysis. These points summarize the most interesting contributions of this paper. The remainder of the paper is organized as follows. Section 2 presents a conceptual framework of wind power and its integration in electric systems. Section 3 explains the features of the model. Section 4 describes the mathematical formulation of the problem. Section 5 gives the methodology for the problem resolution. A case study based on a real power system is shown in Section 6. Finally, conclusions and future work are drawn in Section 7.

Wind power integration is an emerging field in power system studies. This paper addresses the inclusion of wind power plants in the problem of preventive maintenance scheduling (PPPMS) for electric generating systems, comprising other traditional power plants such as thermal, nuclear and hydroelectric. It is a large and highly complex problem requiring many variables and constraints. Including topics aligned with reliability and maintenance in the model makes this study very detailed and gives insight into the problem. The goal is solved in order to generate an optimal preventive maintenance schedule for reliable operation of a power system while satisfying system load demand and a group of constraints. This will increase the availability of the system. The model proposed is illustrated in a real-world case study representative of the Spanish mainland power system. Its relevance stems from the increasing importance of wind farms in Spain, which can be a useful frame of reference for other countries working on this type of renewable energy. The results prove that the methodology works. Furthermore, they are consistent and reflect the expected behavior for the electric system. The schedule achieved is adequate for the modeled requirements, given the imposed constraints, and optimizes the reliability of the system. This model is simple to put into practice, and requires a reasonable amount of computing time. This study could be helpful to electric companies with production activity, particularly companies that coordinate power plant production in an electric system. To guarantee reliability is the duty of these operators. The implementation of the work developed provides the maximization of reliability and the fulfilment of electric demand. When reliability is included in the model by means of the objective function and some appropriate constraints, it is viable to prevent or reduce failures in the electricity supply. In view of this reason, it is possible to maintain a specific quality level, resulting in improved service and consumer welfare. The work presented in this paper suggests future research: (a) improving the model by considering other renewable energies and costs as the objective function; (b) estimating the power produced by every power plant; and (c) implementing other resolution methods such as metaheuristics.