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Open research questions in Power System Reliability and Maintenance

71 gap statements mined from Power System Reliability and Maintenance papers in our 4.5M-paper local library, which holds 327 papers on the topic — drawn mostly from each paper's own stated research gap, future-work, challenge and limitation notes, and its abstract. The ones listed below are a selection still marked open; each names the study that raised it, with a DOI link where the paper has one.

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What the literature leaves open

  • The gap is related to the lack of integration of AI-driven Digital Twins and LSS-assisted smart PSAM.

    Impact of artificial intelligence-driven digital twins and lean six sigma-assisted power system asset management on long-term investment planning · 2026 · DOI

  • Trade-offs between precision versus speed (physics-informed DTs requiring domain expertise versus data-driven models risking overfitting) and between centralized versus decentralized control architectures require further research and resolution.

    Impact of artificial intelligence-driven digital twins and lean six sigma-assisted power system asset management on long-term investment planning · 2026 · DOI

  • The lack of effective predictive maintenance approaches for MV/LV distribution substations. The need for data-driven maintenance decisions and optimized asset lifecycle management. The challenge of integrating artificial intelligence with substation condition data.

    AI-Enabled Predictive Maintenance and Asset-Health Analytics for MV/LV Distribution Substations Using Commissioning-Test Data and Condition Monitoring · 2026 · DOI

  • Potential directions for future research include integrating the proposed framework with digital twin frameworks. Further research can focus on applying the framework to other power distribution systems.

    AI-Enabled Predictive Maintenance and Asset-Health Analytics for MV/LV Distribution Substations Using Commissioning-Test Data and Condition Monitoring · 2026 · DOI

  • Rare-event imbalance is a chronic problem that limits cumulative improvements. Benchmarking fragmentation is another limitation that affects the development of data-driven reliability models. Limited cross-domain transferability is also a challenge that needs to be addressed.

    Data-Driven Approaches to Reliability Modeling in Critical Energy Infrastructure: Analytical Perspectives on Early Failure Detection · 2026 · DOI

  • The paper suggests that future research should focus on the development of physics-informed AI and hybrid models. The study recommends the use of federated and edge learning models to improve the transferability of data-driven reliability models. The paper highlights the need for more research on standardized benchmarking data and unlabelled data self-supervised learning.

    Data-Driven Approaches to Reliability Modeling in Critical Energy Infrastructure: Analytical Perspectives on Early Failure Detection · 2026 · DOI

  • Existing optimization methods have not adequately considered the impacts of planned and unplanned outages. There is a need for a new optimization method that explicitly incorporates these outages.

    Optimization for Battery Energy Storage Configuration Considering the Impact of Planned and Unplanned Outages · 2026 · DOI

  • The lack of effective predictive maintenance frameworks for induced draft fan systems in thermal power plants. The need for a methodology that combines reliability engineering and machine learning to improve system dependability and efficiency.

    Reliability Modeling and Predictive Maintenance Integration for an Induced Draft Fan System Using Semi-Markov Process and Machine Learning-Based Predictive Models · 2026 · DOI

  • A current limitation of this study is the absence of an economic analysis; future research should evaluate the system's overall costs alongside the typical 10 to 15-year payback period of PV investments.

    Reliability Assessment of a PV-Integrated 132 kV Power Network Using ETAP · 2026 · DOI

  • Further research can be conducted on the application of Fault Tree Analysis model for availability assessment of other types of power plants. The results can be used for developing more accurate models for predicting the availability of thermal power plants.

    STUDY TO ASSESS ELECTRICITY GENERATION IN A THERMAL POWER PLANT USING FAULT TREE ANALYSIS MODEL · 2026 · DOI

  • The increasing use of distributed energy sources, energy storage systems, and electric vehicles introduces new components to be modelled. The accuracy of calculation results depends strongly on the accuracy of input data. The paper needs to provide a measurement-based evaluation of distribution transformer losses characteristics.

    Measurement-Based Evaluation of Distribution Transformer Losses Characteristics for Sustainable Voltage Regulation · 2026 · DOI

  • The lack of a systematic decision-making framework for high-risk scenarios such as rising energy fluctuations.

    Risk Assessment of Supply and Demand Imbalance in Power Systems with High Proportion of Renewable Energy Under Extreme Operating Scenarios · 2026 · DOI

  • The study highlights the need for a regression model to predict energy consumption limits.

    "Charge avalanche phenomenon" in conditions of stabilization shutdowns · 2026 · DOI

  • Existing clustering methods, such as Z-score and k-means, have limitations. Prior studies used binary ramp event categorization or non-causative classification techniques.

    A novel hybrid clustering approach for robust ramp event characterization · 2026 · DOI

  • Although the proposed ZK-means technique demonstrated effective performance in identifying and classifying wind power variations, several limitations should be acknowledged. The case study was conducted using aggregated national-level wind generation data from Belgium, which may smooth out local variability and extreme ramp events.

    A novel hybrid clustering approach for robust ramp event characterization · 2026 · DOI

  • The study highlights the need for a more effective and efficient method for contingency analysis and ranking.

    Intelligent Contingency Ranking of Nigeria's 330 KV Transmission Network Using Artificial Neural Network · 2026 · DOI

  • There is a lack of precise, longitudinal measurement of distribution system performance in many Sub-Saharan African nations. Robust, evidence-based policy frameworks are required for economic development.

    A Panel-Data Estimation of Power-Distribution System Reliability for Policy Formulation in Senegal (2000–2026) · 2026 · DOI

  • Future research should focus on the development of a digital planning environment for smart grid planning in industrial and commercial facilities. The research should investigate the application of ETAP-based analysis to other industries and regions. The paper suggests that future research should explore the integration of ETAP-based analysis with other technologies, such as IoT and AI.

    ETAP-Based Power System Analysis for Smart Grid Planning in Saudi Industrial and Commercial Facilities · 2026 · DOI

  • The gap is the lack of a digital planning environment that links the design of facilities, operational reliability, safety compliance, asset loading, and future distributed energy integration.

    ETAP-Based Power System Analysis for Smart Grid Planning in Saudi Industrial and Commercial Facilities · 2026 · DOI

  • The limited quantity of labelled fault data results in poor AI model performance. Communication latency or slow internet speed affects the prediction of faults in cloud systems. Changing environmental conditions, including solar radiation and temperature fluctuations, affect the system.

    AI Based Predictive Maintenance and Fault Detection of Solar Based Microgrids · 2026 · DOI

  • The failures of individual components are assumed to be statistically independent. The failure rates are assumed to remain constant within the considered operating period. Common-cause failures and dynamic interactions between components are not explicitly considered.

    STUDY TO ASSESS ELECTRICITY GENERATION IN A THERMAL POWER PLANT USING FAULT TREE ANALYSIS MODEL · 2026 · DOI

  • The study aims to investigate the dynamic risk linkage across the upstream, midstream, and downstream segments of China’s electricity industry chain.

    How Physical Climate Risks Impact the Risk Linkage of the Electricity Industrial Chain · 2026 · DOI

  • Create a reliability review routine in which model predictions are compared with weekly plant outcomes, including boiler failures, availability, average generation, maintenance cost and mean time between maintenance. Strengthen condition monitoring by linking inspection records, operating data, boiler efficiency data and maintenance history into one controlled dataset for model updating.

    Machine learning enabled preventive maintenance strategy for improving boiler reliability of a thermal power station · 2026 · DOI

  • Developing task partitioning between the Edge and the Cloud. Improving the robustness of AI models to changing environmental conditions. Exploring the application of the proposed system to other types of microgrids.

    AI Based Predictive Maintenance and Fault Detection of Solar Based Microgrids · 2026 · DOI

  • The application of the proposed methodology to other industrial infrastructure. The development of more advanced machine learning-based predictive maintenance models.

    Reliability Modeling and Predictive Maintenance Integration for an Induced Draft Fan System Using Semi-Markov Process and Machine Learning-Based Predictive Models · 2026 · DOI

Most-cited papers in Power System Reliability and Maintenance

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Open questions raised by papers listed on this page include: (1) The gap is related to the lack of integration of AI-driven Digital Twins and LSS-assisted smart PSAM (“Impact of artificial intelligence-driven digital twins and lean six…”, 2026); (2) The lack of effective predictive maintenance approaches for MV/LV distribution substations (“AI-Enabled Predictive Maintenance and Asset-Health Analytics for MV/LV…”, 2026); (3) The paper suggests that future research should focus on the development of physics-informed AI and hybrid models (“Data-Driven Approaches to Reliability Modeling in Critical Energy…”, 2026); (4) There is a need for a new optimization method that explicitly incorporates these outages (“Optimization for Battery Energy Storage Configuration Considering the Impact of…”, 2026); (5) The lack of effective predictive maintenance frameworks for induced draft fan systems in thermal power plants (“Reliability Modeling and Predictive Maintenance Integration for an Induced…”, 2026). 71 gap statements have been mined from Power System Reliability and Maintenance papers in our 4.5M-paper local library, which holds 327 papers on the topic; the gaps come from whichever of those papers state one. They are mostly the research gaps the authors state and the papers' abstracts, plus future-work, limitations and challenges passages. The ones listed below are a selection still marked open; each names the study that raised it, with a DOI link where the paper has one, so you can read the original claim in context.

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