Predictive Reliability Assessment of Generation System

Martin Onyeka Okoye, Junyou Yang, Zhenjiang Lei, Jingwei Yuan, Huichao Ji, Haixin Wang, Jiawei Feng, Tunmise Ayode Otitoju and Weidong Li
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Martin Onyeka Okoye: School of Electrical Engineering, Shenyang University of Technology, Shenyang 110870, China
Junyou Yang: School of Electrical Engineering, Shenyang University of Technology, Shenyang 110870, China
Zhenjiang Lei: Science and Technology Communication Department, State Grid Liaoning Electric Power Co. Ltd., Shenyang 110006, China
Jingwei Yuan: Science and Technology Communication Department, State Grid Liaoning Electric Power Co. Ltd., Shenyang 110006, China
Huichao Ji: School of Electrical Engineering, Shenyang University of Technology, Shenyang 110870, China
Haixin Wang: School of Electrical Engineering, Shenyang University of Technology, Shenyang 110870, China
Jiawei Feng: School of Electrical Engineering, Shenyang University of Technology, Shenyang 110870, China
Tunmise Ayode Otitoju: School of Electrical Engineering, Shenyang University of Technology, Shenyang 110870, China
Weidong Li: School of Electrical Engineering, Shenyang University of Technology, Shenyang 110870, China

Energies, 2020, vol. 13, issue 17, 1-13

Abstract: Due to increasing load and characteristic stagnation and fluctuations of existing generation systems capacity, the reliability assessment of generation systems is crucial to system adequacy. Furthermore, a rapid load increase could amount to a consequent sudden deficit in the generation supply before the next scheduled assessment. Hence, a reliability assessment is conducted at regular and close intervals to ensure adequacy. This study simulates and establishes the relationship between the load growth and generation capacity using the generation and load data of the IEEE reliability test system (IEEE RTS ‘96 standard). The generation capacity states and the risk model were obtained using the sequential Monte Carlo simulation (MCS) method. The load was gradually increased stepwise and is simulated against the constant generation capacity. In each case, the reliability index was recorded in terms of loss-of-load evaluation (LOLE). The recorded reliability index was thereafter fitted with the load-growth trend by the linear regression approach. A predictive assessment approach is thereafter proffered through the obtained fitting equation. In addition, a reliability threshold is effectively determined at a yield point for a reliability benchmark.

Keywords: generation system; load increment; Monte Carlo simulation; reliability assessment; reliability index (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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