Digitalisation and CI technologies do not replace conventional methods , but with the availability of digitalisation and CI analyses , better plans can be made with regard to fault diagnosis of power transformers .
Policy makers , business executives and other stakeholders are encouraged to embrace digitalisation and CI methods in their business operations to promote the digital economy and transformation , in line with the long-term goals as outlined in Wawasan Kemakmuran Bersama 2030 ( WKB 2030 ) and the Malaysia Digital Economy Blueprint , at the same time realising the aspirations of International Sustainable Development Goals ( SDGs ) advocated by the United Nations , primarily SDG7 : Clean and Affordable Energy and SDG9 : Industry , Innovation and Infrastructure . This article seeks to provide greater clarity to industry stakeholders and decision-makers in Government on how digitalisation revolutionises the way maintenance can be carried out for equipment in the electrical power system using digital tools and technology in the decades to come , besides offering insights into the transformational potential of CI that can help drive strategic initiatives for smart condition monitoring and fault diagnosis to propel the country towards a more sustainable , secure and smarter energy future .
REFERENCE
[ 1 ] IEA , Worldwide cost savings from enhanced digitalisation in power plants and electricity networks over 2016-2040 , IEA , Paris .
[ 2 ] A . Jahromi , R . Piercy , S . Cress , J . R . R . Service , and W . Fan , An Approach to Power Transformer Asset Management using Health Index , IEEE Electrical Insulation Magazine , vol . 25 , no . 2 ,( 2009 ), pp . 20-34 .
[ 3 ] H . d . Faria , J . G . S . Costa , and J . L . M . Olivas , A review of monitoring methods for predictive maintenance of electric power transformers based on dissolved gas analysis , Renewable and Sustainable Energy Reviews , vol . 46 , ( Feb . 2015 ), 201-209 .
[ 4 ] B . P . Das and J . C . Leicht , Digital Power Transformers - An Intelligent Approach to Smart Asset Management , in : CIGRE AORC Technical Meeting 2019 , Bali , Indonesia , ( 2019 ), 1-8 .
[ 5 ] Y . Wang , D . Chang , Y . Fan , G . Zhang , J . Zhan , X . Shao , and W . He , Acoustic localization of partial discharge sources in power transformers using a particle-swarm-optimization-route-searching algorithm , IEEE Transactions on Dielectrics and Electrical Insulation , vol . 24 , no . 6 , ( Dec . 2017 ), 3647-3656 .
[ 6 ] A . Y . Alqudsi and A . H . ElHag , A cost effective artificial intelligence based transformer insulation health index , in : 2017 3rd International Conference on Condition Assessment Techniques in Electrical Systems ( CATCON ), Rupnagar , India , ( 2017 ), 108- 111 .
[ 7 ] S . Y . Wong , X . Ye , F . Guo , H . H . Goh , “ Computational Intelligence for Preventive Maintenance of Power Transformers ,” Applied Soft Computing , 2021 . DOI :
10.1016 / j . asoc . 2021.108129
[ 8 ] S . Santoso , E . J . Powers , W . M . Grady and A . C . Parsons , Power quality disturbance waveform recognition using a wavelet-based neural classifier . I . Theoretical foundation , in IEEE Transactions on Power Delivery , vol . 15 , no . 1 , ( 2000 ), 222-228 .
13