جستجوی مقالات مرتبط با کلیدواژه « extreme event » در نشریات گروه « برق »

Predicting the status of power grid components, especially overhead lines in response to extreme weather event, plays an important role in planning pre-resource allocation, as well as restoring loads more quickly at a faster time which can improve the power grid resilience. In this paper, a Multi-dimensional Support Vector Machine algorithm is proposed to predict outage overhead lines assuming storm paths. In this model, dimensions are based on five distinct features: the distance from building, distance from tree, distance from center of storm, storm speed and cable type. The result of the proposed model is the classification of overhead lines status into two out and operational statuses implemented on the 33-bus IEEE network. The results show that the proposed model predicts outage lines with high accuracy.

Recently, the frequency and severity of natural and man-made disasters (extreme events), which have a high-impact low-frequency (HILF) property, are increased. These disasters can lead to extensive outages, damages, and costs in electric power systems. A power system must be built with “resilience” against disasters, which means its ability to withstand disasters efficiently while ensuring the least possible interruption in the supply of electricity, sustaining critical social services, and enabling a quick recovery and restoration to the normal operation state. Quantifying the power system resilience is a complicated and controversial problem. However, this is necessary for the evaluation and comparison of different resilience enhancement strategies. The resilience metrics are mathematical tools to measure the resilience level of a power system, which are normally employed for resilience cost-benefit in the planning and operation domains. Numerous resilience metrics have been presented in the power system literature. However, there is a lack of a comprehensive conceptual framework regarding the different types of resilience metrics in electric power systems, and existing frameworks have essential shortcomings. In this paper, after introducing and criticizing the existing frameworks, a conceptual framework is suggested to classify different types of resilience metrics in the power system literature. In this conceptual framework, power system resilience metrics are divided into “non-performance-based” and “performance-based” groups. The “performance-based” resilience metrics are also divided into “performance” and “consequence (outcome)” groups. The “performance” resilience metrics consist of five groups including “power”, “duration”, “frequency”, “probability” and “curve”. The “consequence (outcome)” resilience metrics consist of four groups including “economic”, “social”, “geographic” and “safety and health”. In addition, both of the “performance” and “consequence (outcome)” groups have a distinct group naming “general”. In order to verify and validate the comprehensiveness and inclusivity of the proposed conceptual framework, two actions are accomplished. Firstly, the existing power system resilience metrics are allocated to the framework’s groups. Secondly, the proposed conceptual framework is compared with the existing frameworks. These actions show that the proposed conceptual framework can cover and classify different types of power system resilience metrics in the literature, is more comprehensive comparing the existing frameworks, and lacks the essential shortcoming of those frameworks. Thus, the proposed conceptual framework is comprehensive and useful. The proposed conceptual framework can be used by academic and industrial researchers. Academic researchers can concentrate on groups that need further research to propose new resilience metrics, whereas industrial researchers can choose the appropriate resilience metric according to their needs.