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In a deregulated power industry, a maintenance strategy is of critical importance for transmission systems composed of aging components. Such a strategy can provide significant cost savings by optimizing maintenance decisions for power system operation. This paper presents a Reliability-Centered Maintenance (RCM) model for developing a maintenance strategy in a transmission system. This model is applicable to transmission components whose degradation can be classified according to the severity of the aging. Particle Swarm Optimization (PSO) is used to extract the optimal RCM strategy from a large class of possible maintenance scenarios. A numerical example shows that a maintenance strategy based on the proposed RCM model is more cost-efficient than traditional maintenance strategies.

As part of the restructuring of the electric power industry, transmission utilities have tried to maximize profit while maintaining reliability. These systems must be operated to meet customer needs by reducing the cost of electricity. To accomplish this objective, maintenance strategies have been established to provide a tradeoff between cost and reliability [1], [2] and [3]. Reliability-Centered Maintenance (RCM) has been used to develop maintenance strategies that provide an acceptable level of reliability in a cost-effective manner [4]. The RCM technique is a structured framework for analyzing the functions and potential failures of a transmission component, with a focus on preserving reliability. Thus, RCM must consider not only the condition of a piece of equipment, but also its importance in the power transmission system. The RCM concept and its application to power system facilities have been described in numerous studies [5], [6], [7], [8] and [9]. In [5], an RCM-based maintenance strategy for circuit breakers was presented. In [6], the RCM model was used to determine the optimal maintenance interval in distribution protection systems. The RCM approach for transmission systems was introduced in [7]. However, this study does not provide a method for quantifying the impact of maintenance on reliability. In [8], an RCM strategy for substations was developed. Although this approach takes into account the importance of a substation in the system, the evaluation criteria are not discussed in detail. The quantified impact of planned transmission outages on overall system reliability was studied in detail in [9]. However, this article did not consider the state of a component, which varies over time. The main objective of this work was to develop a comprehensive RCM model for a transmission system that focuses on preserving system functions and system reliability. The RCM model consists of a component state model and an impact model. The component state model represents levels of degradation, allowing aging transmission components to be handled, and the impact model analyzes the impact of component states and maintenance on the overall system. Using this RCM model, the optimal maintenance strategy can be determined via Particle Swarm Optimization (PSO). To develop an RCM-based maintenance strategy from a large class of possible maintenance scenarios, a heuristic approach is useful to find a feasible solution close to the optimal solution. Particle Swarm Optimization (PSO) is one of these heuristic approaches and is applied in the present research to efficiently find optimal maintenance strategies. The remainder of the paper is organized as follows: The proposed RCM model is introduced in Section 2. Section 3 describes the PSO process used to determine the optimal maintenance strategy. In Section 4, a numerical example is presented, using an IEEE 30-bus system. The results obtained from the proposed maintenance strategy, including the PSO-based RCM model, are compared with Time-Based Maintenance (TBM) and Conditional-Based Maintenance (CBM). Conclusions are given in Section 5.

In this paper, we proposed an RCM model, based on a component state model and an impact model, to find the optimal maintenance strategy for various kinds of aging components in a transmission system. The notable characteristics of this model are as follows: The handling of aging components in a transmission system via a component state model.  Adaptability to different components by adjusting the number of degradation states in the component state model.  Use of the impact model to analyze the effects of component states or maintenance on transmission systems. The failure patterns of components were simulated via a sequential Monte Carlo method. PSO was applied to efficiently find an RCM-based maintenance strategy for all components under consideration. Consequently, the maintenance strategy based on the RCM model was proven to be cost-effective in comparison to conventional TBM and CBM.