Data Mining Integration of Power Grid Companies Enterprise Asset Management

2019 ◽  
pp. 39-49
Author(s):  
Oleg Protalinskiy ◽  
Nikita Savchenko ◽  
Anna Khanova
Keyword(s):  
Data Mining ◽  
Asset Management ◽  
Power Grid

scholarly journals Life-cycle Asset Management in Residential Developments Building on Transport System Critical Attributes via a Data-mining Algorithm

Buildings ◽  
2018 ◽  
Vol 9 (1) ◽  
pp. 1 ◽  
Author(s):  
Umair Hasan ◽  
Andrew Whyte ◽  
Hamad Al Jassmi
Keyword(s):  
Data Mining ◽  
Life Cycle ◽  
Built Environment ◽  
Transport System ◽  
Asset Management ◽  
Public Transport ◽  
Categorical Variables ◽  
Data Mining Algorithm ◽  
Large Set ◽  
Mining Algorithm

Public transport can discourage individual car usage as a life-cycle asset management strategy towards carbon neutrality. An effective public transport system contributes greatly to the wider goal of a sustainable built environment, provided the critical transit system attributes are measured and addressed to (continue to) improve commuter uptake of public systems by residents living and working in local communities. Travel data from intra-city travellers can advise discrete policy recommendations based on a residential area or development’s public transport demand. Commuter segments related to travelling frequency, satisfaction from service level, and its value for money are evaluated to extract econometric models/association rules. A data mining algorithm with minimum confidence, support, interest, syntactic constraints and meaningfulness measure as inputs is designed to exploit a large set of 31 variables collected for 1,520 respondents, generating 72 models. This methodology presents an alternative to multivariate analyses to find correlations in bigger databases of categorical variables. Results here augment literature by highlighting traveller perceptions related to frequency of buses, journey time, and capacity, as a net positive effect of frequent buses operating on rapid transit routes. Policymakers can address public transport uptake through service frequency variation during peak-hours with resultant reduced car dependence apt to reduce induced life-cycle environmental burdens of buildings by altering residents’ mode choices, and a potential design change of buildings towards a public transit-based, compact, and shared space urban built environment.

Application of Data Mining in Smart Grid Technology

2021 ◽  
pp. 815-827
Author(s):  
Lipi Chhaya ◽  
Paawan Sharma ◽  
Adesh Kumar ◽  
Govind Bhagwatikar
Keyword(s):  
Data Mining ◽  
Smart Grid ◽  
Power Grid ◽  
Analysis Data ◽  
Consumer Participation ◽  
Distribution Automation ◽  
Grid Technology ◽  
Self Healing ◽  
Grid Operation ◽  
Smart Grid Technology

Smart grid technology is a radical approach for improvisation in existing power grid. Some of the significant features of smart grid technology are bidirectional communication, AMI, SCADA, renewable integration, active consumer participation, distribution automation, and complete management of entire grid through wireless communication standards and technologies. Management of complex, hierarchical, and heterogeneous smart grid infrastructure requires data collection, storage, processing, analysis, retrieval, and communication for self-healing and complete automation. Data mining techniques can be an effective solution for smart grid operation and management. Data mining is a computational process for data analysis. Data scrutiny is unavoidable for unambiguous knowledge discovery as well as decision making practices. Data mining is inevitable for analysis of various statistics associated with power generation, distribution automation, data communications, billing, consumer participation, and fault diagnosis in smart power grid.

Association Rules Mining Techniques Used for Relevance Analysis of 500kV EHV Power Grid Off-Limit

2013 ◽  
Vol 333-335 ◽  
pp. 698-701
Author(s):  
Hai Wei Lu ◽  
Gang Wu ◽  
Ming Chun Liu
Keyword(s):  
Data Mining ◽  
Decision Support ◽  
Correlation Analysis ◽  
Association Rules ◽  
Power Grid ◽  
Scada System ◽  
Relevance Analysis ◽  
The Law ◽  
Mining Tools ◽  
Data Level

In the long-running process, SCADA system have accumulated a mass of the grid off-limit information, if we idle this information, will lead to so called resources deserted, at the data level, through data mining tools, we can have a correlation analysis of the off-limit information accumulated in the grid fault history library, to dig out the law, in a certain sense, the law can be the criterion for the grid Warning Decision Support.

scholarly journals Penerapan Algoritma Apriori Untuk Menentukan Persediaan Peralatan Dan Mesin

2020 ◽  
Vol 6 (2) ◽  
pp. 195-203
Author(s):  
Debora Kesia Batubara ◽  
Nining Suryani ◽  
Duwi Cahaya Putri Buani
Keyword(s):  
Data Mining ◽  
Asset Management ◽  
A Priori ◽  
State Agency ◽  
Management Agency ◽  
Mining Methods ◽  
Local Budget ◽  
Case Data

Abstract: The DKI Jakarta Regional Asset Management Agency (BPAD) is a State Agency that regulates budget costs for many types of assets in the DKI Jakarta area. One type of budget is for equipment and machinery that are needed annually. The local budget so far has not focused on the equipment and machinery needed. This is needed in order to be able to minimize the budget and focus on the equipment and machinery needed each year. In this case Data Mining can be applied to find information from the dataset. In order to know the Equipment and Machines that are most needed each year, searching for information on the dataset can be done by one of the Data Mining methods, namely the A priori Algorithm by looking for patterns of relationships in a dataset. If you know the equipment and machinery that are most needed each year, BPAD can focus the budget on the goods most needed and can find out which SKPD need more equipment and machinery each year.Keywords: BPAD, Data Mining, Algoritma Apriori.Abstraksi: Badan Pengelolaan Aset Daerah (BPAD) DKI Jakarta adalah Instansi Negara yang mengatur biaya anggaran untuk banyak jenis aset di daerah DKI Jakarta. Salah satu jenis anggaran yang ada ialah untuk Peralatan dan Mesin yang tiap tahunnya dibutuhkan. Anggaran daerah sejauh ini belum berfokus pada Peralatan dan Mesin yang dibutuhkan. Hal ini diperlukan agar dapat lebih meminimalisir anggaran dan berfokus kepada Peralatan dan Mesin yang dibutuhkan tiap tahunnya. Dalam hal ini Data Mining dapat diterapkan untuk mencari informasi dari dataset. Agar dapat mengetahui Peralatan dan Mesin yang paling dibutuhkan tiap tahunnya, pencarian informasi pada dataset dapat dilakukan dengan salah satu metode Data Mining yaitu Algoritma Apriori dengan mencari pola hubungan dalam sebuah dataset. Jika mengetahui Peralatan dan Mesin yang paling dibutuhkan tiap tahunnya maka BPAD dapat memfokuskan anggaran pada barang yang paling dibutuhkan dan dapat mengetahui SKPD mana yang lebih membutuhkan Peralatan dan Mesin setiap tahunnya..Kata Kunci: BPAD, Data Mining, Algoritma Apriori.

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