Maintenance Tools applied to Electric Generators to Improve Energy Efficiency and Power Quality of Thermoelectric Power Plants

被引:11
|
作者
Fonseca Junior, Milton [1 ]
Bezerra, Ubiratan Holanda [2 ]
Leite, Jandecy Cabral [1 ]
Moya Rodriguez, Jorge Laureano [1 ]
机构
[1] Inst Manaus, Galileo Inst Technol & Educ Amazon, BR-69020030 Manaus, Amazonas, Brazil
[2] Fed Univ Para, Dept Elect Engn CEAMAZON, BR-66075110 Belem, Para, Brazil
来源
ENERGIES | 2017年 / 10卷 / 08期
关键词
maintenance management engineering; electric generators; power quality; thermoelectric power plants; PREVENTIVE MAINTENANCE; OPTIMIZATION; RELIABILITY; SYSTEMS; REPLACEMENT; STRATEGIES; FRAMEWORK; WARRANTY; MODEL; COST;
D O I
10.3390/en10081091
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
This paper presents a specific method to improve the reliability of the equipment and the quality of power supplied to the electrical systems with the frequency and voltage control of a thermoelectric plant, to guarantee a more stable system. The method has the novelty of combining Total Productive Maintenance (TPM) using only four pillars, with Electrical Predictive Maintenance based in failure analysis and diagnostic. It prevents voltage drops caused by excessive reactive consumption, thus guaranteeing the company a perfect functioning of its equipment and providing a longer life of them. The Maintenance Management Program (MMP) seeks to prevent failures from causing the equipment to be shut down from the electrical system, which means large financial losses, either by reducing billing or by paying fines to the regulatory agency, in addition to prejudice the reliability of the system. Using management tools, but applying only four TPM pillars, it was possible to achieve innovation in power plants with internal combustion engines. This study aims to provide maintenance with a more reliable process, through the implantation of measurement, control and diagnostic devices, thus allowing the management to reduce breakdown of plant equipment. Some results have been achieved after the implementation, such as reduction of annual maintenance cost, reduction of corrective maintenance, increase of MTBF (Mean Time between Failures) and reduction of MTTR (Mean Time to Repair) in all areas. Probabilistic models able to describe real processes in a more realistic way, and facilitate the optimization at maximum reliability or minimum costs are presented. Such results are reflected in more reliable and continual power generation.
引用
收藏
页数:21
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