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Development of data reconciliation system for billing process at PT Perusahaan Gas Negara

R Hadianti, A Ihsan, A Mujiyanto, S. Uttunggadewa
2019 IOP Conference Series: Materials Science and Engineering  
Perusahaan Gas Negara (abbreviated as PGN),  ...  Acknowledgement We are grateful to our research assistant Muhammad Ridwan Reza Nugraha and Nita Ratnawati who have implemented the anomaly detection procedure and the forecast method in R.  ...  We also thank to Luthfi Pratama for developing the graphical user interface.  ... 
doi:10.1088/1757-899x/567/1/012002 fatcat:a7b62wczirbpfge6jzhiaytqui

Data Improving in Time Series Using ARX and ANN Models

Hermine N. Akouemo, Richard J. Povinelli
2017 IEEE Transactions on Power Systems  
This paper presents two approaches for the detection and imputation of anomalies in time series data.  ...  The ARX and ANN data cleaning models are evaluated on natural gas time series data. This paper demonstrates that the proposed approaches are able to identify and impute anomalous data points.  ...  To the best of our knowledge the model we use for natural gas forecasting is state-of-the-art [41] . Many techniques have been developed for data cleaning.  ... 
doi:10.1109/tpwrs.2017.2656939 fatcat:gk7ivs4jjjcpxlk67rqw2cdp6i

A review of the day-ahead natural gas consumption in Denmark: starting point towards forecasting accuracy improvement

Orhan Altuğ Karabiber, George Xydis
2020 International Journal of Coal Science & Technology  
Natural gas consumption forecasting is crucial for transmission system operators, distribution system operators, traders, and other players in the market.  ...  This work collects natural gas forecasting scientific works in accordance with the forecasting tool used by Energinet, the Danish transmission system operator.  ...  Acknowledgements Energinet, the Danish TSO, should be thanked for their support throughout the literature review process because they provided data for this work to be implemented.  ... 
doi:10.1007/s40789-020-00331-2 fatcat:pql3s7nfq5cr7pfy6pkhgft7g4

The Impacts of the Applications of Artificial Intelligence in Maritime Logistics

Batin Latif AYLAK
2022 European Journal of Science and Technology  
A comprehensive assessment is also presented, which highlights research gaps and forecasts future research orientations.  ...  This study aims to identify current approaches in the usage of Artificial Intelligence (AI) methods for solving shipping problems.  ...  Despite a well-developed literature on anomaly detection, future research should focus on real-time anomaly detection of vessels and the application of advanced ML techniques.  ... 
doi:10.31590/ejosat.1079206 fatcat:upag27kgwbd6badkbqluuak4ne

Review of Smart Meter Data Analytics: Applications, Methodologies, and Challenges

Yi Wang, Qixin Chen, Tao Hong, Chongqing Kang
2018 IEEE Transactions on Smart Grid  
The widespread popularity of smart meters enables an immense amount of fine-grained electricity consumption data to be collected.  ...  To provide a comprehensive overview of the current research and to identify challenges for future research, this paper conducts an application-oriented review of smart meter data analytics.  ...  Several open load datasets are summarized in Table I . • Customer Behavior Trials: The Commission for Energy Regulation (CER), the regulator for the electricity and natural gas sectors in Ireland, launched  ... 
doi:10.1109/tsg.2018.2818167 fatcat:yacc5fol6vhydkw2azgy4mpfai

Things2People Interaction toward Energy Savings in Shared Spaces Using BIM

Bruno Mataloto, Hugo Mendes, Joao C. Ferreira
2020 Applied Sciences  
This information is essential for sustainability actions in shared spaces, where this information can have an important role.  ...  People in shared building space have an important role in energy consumption because they can turn on/off equipment and heat/cooling systems.  ...  of the day for a week of repeating the same behaviour, using the average light Besides the referred views, the system uses predicted energy consumption data to detect anomalies before closing hours,  ... 
doi:10.3390/app10165709 fatcat:5ioczfdigva45eh352hmlx7szi

Introduction to data mining for sustainability

Katharina Morik, Kanishka Bhaduri, Hillol Kargupta
2011 Data mining and knowledge discovery  
An overview of methods for anomaly detection is Chandola et al. (2009) . Prediction and forecast Prediction and forecast in the earth sciences is often based on simulations.  ...  Sometimes, these unsupervised methods are a prerequisite for anomaly detection.  ... 
doi:10.1007/s10618-011-0239-5 fatcat:ifitak6a75bf3jqbe2udr2x7ea

Carbon dioxide fluctuations

Peter D. Moore
1975 Nature  
Climatic cycles may eventually prove of great value in climatic forecasting but until a physical reason for their continued existence is established, such forecasts can only be tentative.  ...  conditions during the accumulation of the organic detritus which is now coal, oil and gas.  ... 
doi:10.1038/255108a0 fatcat:rl6gvyp2tncb7kwl65maesbs7i

Smart Grid: A Survey of Architectural Elements, Machine Learning and Deep Learning Applications and Future Directions [article]

Navod Neranjan Thilakarathne, Mohan Krishna Kagita, Dr. Surekha Lanka, Hussain Ahmad
2020 arXiv   pre-print
The Smart grid (SG), generally known as the next-generation power grid emerged as a replacement for ill-suited power systems in the 21st century.  ...  With the massive infrastructure it holds and the underlying communication network in the system, it introduced a large volume of data that demands various techniques for proper analysis and decision making  ...  Energy consumption 4. Fault detection 5. Sizing 6. Network anomaly detection 7. Security breach detection 8. Fraud detection 9. Optimum schedule 10.  ... 
arXiv:2010.08094v1 fatcat:b63nrnsg2bepvokxujhlxkx2tu

Real-time anomaly detection for very short-term load forecasting

Jian LUO, Tao HONG, Meng YUE
2018 Journal of Modern Power Systems and Clean Energy  
Finally, a general anomaly detection framework is proposed for the future research.  ...  Although the recent load information is critical to very short-term load forecasting (VSTLF), power companies often have difficulties in collecting the most recent load values accurately and timely for  ...  The work was supported in part by the National Natural Science Foundation of China (No. 71701035), and the US Department of Energy, Cybersecurity for Energy Delivery Systems (CEDS) Program (No.  ... 
doi:10.1007/s40565-017-0351-7 fatcat:ksdpv6n2cbbgzanlbnv7h6zfpa

Bad Data Detection and Data Filtering in Power System

Dhaval Bhatti, Anuradha Deshpande
2018 International Journal of Computer Applications  
Data smoothing is necessary for some application ex. Load forecasting in power system.  ...  Bad Data detection and data cleaning is helpful to get over this risk. With use of MATLAB Bad Data can be easily detected.  ...  Paper [5] , has discussed real time anomaly detection for short term load forecasting. In VSTLF (Very Short Term Load Forecasting) most recent load information is used.  ... 
doi:10.5120/ijca2018918263 fatcat:r7hnsdmqyzd3rl3yxbscekk43q

ARIMA-Based Modeling and Validation of Consumption Readings in Power Grids [chapter]

Varun Badrinath Krishna, Ravishankar K. Iyer, William H. Sanders
2016 Lecture Notes in Computer Science  
First, we show that the ARMA model proposed in the anomaly detection literature is unsuitable for electricity consumption as most consumers exhibit non-stationary consumption behavior.  ...  Thus, we propose the use of ARIMA forecasting methods for validating consumption readings.  ...  We thank Jenny Applequist, Jeremy Jones and Timothy Yardley for their support, and Prof. Douglas L. Jones for his feedback.  ... 
doi:10.1007/978-3-319-33331-1_16 fatcat:v4sqgktarrahvpl3t2yus6jqxe

A survey of research progress and hot front of natural gas load forecasting from technical perspective

Huibin Zeng, Bilin Shao, Genqing Bian, Dan Song, Xiaojun Li
2020 IEEE Access  
As an important part of natural gas industry planning, load forecasting plays a vital role in the optimal dispatching and operation of the natural gas network.  ...  As a clean energy, natural gas is favored by many countries all over the world.  ...  ACKNOWLEDGEMENT This work was supported by The National Natural Science Foundation of China(No. 62072363). The authors are grateful for the help in writing this article by Yu Zhao and Hongbin Dai.  ... 
doi:10.1109/access.2020.3044052 fatcat:635dluiv5rg3dgyo3fvdqyyxzq

A Novel Approach for Detecting Anomalous Energy Consumption Based on Micro-Moments and Deep Neural Networks

Yassine Himeur, Abdullah Alsalemi, Faycal Bensaali, Abbes Amira
2020 Cognitive Computation  
This paper introduces a new solution to detect energy consumption anomalies based on extracting micro-moment features using a rule-based model.  ...  These promising results establish the efficacy of the proposed deep micro-moment solution for detecting abnormal energy consumption, promoting energy efficiency behaviors, and reducing wasted energy.  ...  In [23] , Yan proposes a deep anomaly detection to identify gas turbine combustor anomalies based on two principal stages: (i) it uses a DNN for learning characteristic representations extracted from  ... 
doi:10.1007/s12559-020-09764-y fatcat:op4ochnzizdvbmhczeroopxt7q

Smart Grid: A Survey of Architectural Elements, Machine Learning and Deep Learning Applications and Future Directions

Machine Learning and Deep Learning Applications and Future Directions Smart Grid: A Survey of Architectural Elements
2021 Zenodo  
• Energy generation • Price • Energy consumption • Fault detection • Sizing • Network anomaly detection • Security breach detection • Fraud detection • Optimum schedule • Stability of the SG A.  ...  We also found that currently ML and DL based models are used in various aspects of SG such as fault detection, anomaly detection, energy forecasting, fraud detection and etc.  ... 
doi:10.5281/zenodo.5202740 fatcat:pmd4sdasgjgczluc53nc6xmyuy
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