mlsanityData to 7 Oct 2026

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

arXiv 1802.04117 ↗First posted 9 Feb 2018cs.CYcited by 47

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Abstract (arXiv)

The widespread popularity of smart meters enables an immense amount of fine-grained electricity consumption data to be collected. Meanwhile, the deregulation of the power industry, particularly on the delivery side, has continuously been moving forward worldwide. How to employ massive smart meter data to promote and enhance the efficiency and sustainability of the power grid is a pressing issue. To date, substantial works have been conducted on smart meter data analytics. 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. Following the three stages of analytics, namely, descriptive, predictive and prescriptive analytics, we identify the key application areas as load analysis, load forecasting, and load management. We also review the techniques and methodologies adopted or developed to address each application. In addition, we also discuss some research trends, such as big data issues, novel machine learning technologies, new business models, the transition of energy systems, and data privacy and security.

Key facts. Cited by 47 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Feb 2018.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 9; 2022: 4; 2023: 7; 2024: 2; 2025: 18; 2026: 7.

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  1. 2021Review of Low Voltage Load Forecasting: Methods, Applications, and Recommendationscited by 17
  2. 2023Short-Term Electricity Load Forecasting Using the Temporal Fusion Transformer: Effect of Grid Hierarchies and Data Sourcescited by 13
  3. 2023Customized Load Profiles Synthesis for Electricity Customers Based on Conditional Diffusion Modelscited by 7
  4. 2022Short-Term Density Forecasting of Low-Voltage Load using Bernstein-Polynomial Normalizing Flowscited by 6
  5. 2023A Machine Learning-Based Framework for Clustering Residential Electricity Load Profiles to Enhance Demand Response Programscited by 5
  6. 2025PowerGrow: Feasible Co-Growth of Structures and Dynamics for Power Grid Synthesiscited by 5
  7. 2021Machine Learning Approach to Uncovering Residential Energy Consumption Patterns Based on Socioeconomic and Smart Meter Datacited by 4
  8. 2021Hierarchical transfer learning with applications for electricity load forecastingcited by 4
  9. 2021Privacy-preserving Federated Learning for Residential Short Term Load Forecastingcited by 4
  10. 2025Temporal Encoding Strategies for Energy Time Series Predictioncited by 4
  11. 2021Data-Driven Copy-Paste Imputation for Energy Time Seriescited by 3
  12. 2024CommonPower: A Framework for Safe Data-Driven Smart Grid Controlcited by 3
35 more
  1. 2025PowerGNN: A Topology-Aware Graph Neural Network for Electricity Gridscited by 3
  2. 2025External Data-Enhanced Meta-Representation for Adaptive Probabilistic Load Forecastingcited by 3
  3. 2021AMI-FML: A Privacy-Preserving Federated Machine Learning Framework for AMIcited by 2
  4. 2025Bridging Smart Meter Gaps: A Benchmark of Statistical, Machine Learning and Time Series Foundation Models for Data Imputationcited by 2
  5. 2025Electricity Demand Forecasting in Future Grid States: A Digital Twin-Based Simulation Studycited by 2
  6. 2022A Bayesian Deep Learning Technique for Multi-Step Ahead Solar Generation Forecastingcited by 1
  7. 2022Agglomerative Hierarchical Clustering with Dynamic Time Warping for Household Load Curve Clusteringcited by 1
  8. 2023Meta-Regression Analysis of Errors in Short-Term Electricity Load Forecastingcited by 1
  9. 2025From Dense to Sparse: Event Response for Enhanced Residential Load Forecastingcited by 1
  10. 2025Multi-task Online Learning for Probabilistic Load Forecastingcited by 1
  11. 2025Leveraging External Factors in Household-Level Electrical Consumption Forecasting using Hypernetworkscited by 1
  12. 2025Scalable Cloud-Native Architectures for Intelligent PMU Data Processingcited by 1
  13. 2026SEA-TS: Self-Evolving Agent for Autonomous Code Generation of Time Series Forecasting Algorithmscited by 1
  14. 2021Appliance Operation Modes Identification Using Cycles Clusteringcited by 0
  15. 2021Investigating Underlying Drivers of Variability in Residential Energy Usage Patterns with Daily Load Shape Clustering of Smart Meter Datacited by 0
  16. 2021Prediction of Energy Consumption for Variable Customer Portfolios Including Aleatoric Uncertainty Estimationcited by 0
  17. 2022On Designing Data Models for Energy Feature Storescited by 0
  18. 2023Cybersecurity Challenges of Power Transformerscited by 0
  19. 2023The Energy Prediction Smart-Meter Dataset: Analysis of Previous Competitions and Beyondcited by 0
  20. 2023Local Differential Privacy for Smart Meter Data Sharingcited by 0
  21. 2024A Novel Combined Data-Driven Approach for Electricity Theft Detectioncited by 0
  22. 2025HOPS: High-order Polynomials with Self-supervised Dimension Reduction for Load Forecastingcited by 0
  23. 2025Time and Frequency Domain-based Anomaly Detection in Smart Meter Data for Distribution Network Studiescited by 0
  24. 2025IISE PG&E Energy Analytics Challenge 2025: Hourly-Binned Regression Models Beat Transformers in Load Forecastingcited by 0
  25. 2025Data Model Design for Explainable Machine Learning-based Electricity Applicationscited by 0
  26. 2025Quantum Learning and Estimation for Coordinated Operation between Distribution Networks and Energy Communitiescited by 0
  27. 2025Water Demand Forecasting of District Metered Areas through Learned Consumer Representationscited by 0
  28. 2025Extending Load Forecasting from Zonal Aggregates to Individual Nodes for Transmission System Operatorscited by 0
  29. 2025Adaptive Multi-task Learning for Probabilistic Load Forecastingcited by 0
  30. 2026Reliable Grid Forecasting: State Space Models for Safety-Critical Energy Systemscited by 0
  31. 2026CROCS: A Two-Stage Clustering Framework for Behaviour-Centric Consumer Segmentation with Smart Meter Datacited by 0
  32. 2026SmartMeterFM: Unifying Smart Meter Data Generative Tasks Using Flow Matching Modelscited by 0
  33. 2026A Unified Generative-AI Framework for Smart Energy Infrastructure: Intelligent Gas Distribution, Utility Billing, Carbon Analytics, and Quantum-Inspired Optimisationcited by 0
  34. 2026Inpainting-Style Conditional Diffusion for Multivariable Time Series Forecastingcited by 0
  35. 2026MBDiff: Multi-view Behavior-aware Diffusion Model for Probabilistic Utility Data Imputationcited by 0