Science AI Journal
Engineering · Research topic

Open research questions in Smart Grid Energy Management

54 unresolved questions extracted from the limitations and future-work sections of 324 Smart Grid Energy Management papers in our library. Each links back to the study that raised it.

What the literature leaves open

  • Operational and management challenges for REC-based systems. Technical barriers related to the integration of DERs into existing distribution networks. Regulatory and legal barriers, including uncertainty in governance structures and unclear definitions of community ownership.

    Energy Management and Optimization of Renewable Energy Communities with Flexible Load Coordination and Shared Energy Utilization · 2026 · DOI

  • Variations in resource allocation and energy consumption behavior among prosumers. Limited adaptability of traditional model-based methods in uncertain environments.

    Multi-Agent Reinforcement Learning-Driven P2P Energy Trading Strategy for Community Prosumers · 2026 · DOI

  • The inherent intermittency, rapid variability, and stochastic uncertainty of renewable energy sources. The need for high-fidelity forecasting models to support reliable VPP operations. The complexity of optimal distributed generation planning and battery energy storage system scheduling.

    Integrated machine learning forecasting and grey wolf optimization for optimal operation of virtual power plants in smart distribution networks · 2026 · DOI

  • The lack of integrated management frameworks that synthesize neural network-based forecasting with Grey Wolf Optimization. The need for high-fidelity forecasting models to support reliable VPP operations.

    Integrated machine learning forecasting and grey wolf optimization for optimal operation of virtual power plants in smart distribution networks · 2026 · DOI

  • High computation times for online mixed-integer optimization problems. Lack of scalability for large problem sizes. Uncertain generation and load profiles.

    Approximate model predictive control for microgrid energy management via imitation learning · 2026 · DOI

  • The need for efficient energy management in microgrids. The limitations of existing EMS methods, including high computation times and lack of scalability.

    Approximate model predictive control for microgrid energy management via imitation learning · 2026 · DOI

  • Traditional demand-side management methods consider load forecasting and scheduling as separate tasks. The integration of renewable energy has become one of the most urgent issues in modern power systems. There is a need for a framework that integrates the temporal learning capability of LSTM and the global optimization capability of PSO.

    Multi-Objective Intelligent Demand-Side Management Using Explainable PSO-Optimized LSTM in Renewable Energy-Based Smart Grids · 2026 · DOI

  • The gap between announced and deliverable AI power demand. The lack of accurate forecasts of AI-driven electricity demand.

    Announced vs. Deliverable AI Power Demand · 2026 · DOI

  • The influence of less drastic price signals is more difficult to evaluate. The study aims to fill this gap by exploring the influence of price and attitude on shifting residential electricity consumption.

    The influence of price and attitude on shifting residential electricity consumption from on- to off-peak periods · 1983 · DOI

  • Lack of comparison with other emerging AI/ML approaches for power factor correction or discussion of why TinyML was specifically chosen over alternative edge computing solutions.

    An Edge AI-Driven IOT Framework for Automatic Power Factor Correction in Smart Industrial Power Systems · 2026 · DOI

  • No analysis of how the Edge AI system performs under extreme load conditions, sudden transient events, or edge cases that may occur in diverse industrial settings.

    An Edge AI-Driven IOT Framework for Automatic Power Factor Correction in Smart Industrial Power Systems · 2026 · DOI

  • Traditional VPPs face challenges such as high latency, cybersecurity vulnerabilities, and low user engagement. The need for a novel framework that integrates edge-fog computing, blockchain-secured communication, and AI-driven market mechanisms.

    IoT-Enhanced virtual power plants with edge computing and blockchain security for sustainable smart grid management · 2026 · DOI

  • The primary challenge in current microgrids is the integration with conventional systems. The variability and uncertainty in microgrids stem from dynamic load profiles and renewable energy sources.

    Multi-agent Reinforcement Learning with Clustering and Forecasting for Optimized Energy Sharing in Microgrids · 2026 · DOI

  • The methodology part fails to include the core PPO training parameters needed for reproducibility in experiments. Missing values in the dataset may introduce bias or discontinuity into the state representation.

    Deep Reinforcement Learning-Based Intelligent Control for Efficiency Enhancement in Thermal Power Plant Fuel Management · 2026 · DOI

  • To extend the proposed approach to other types of power plants and industrial processes. To investigate the application of other machine learning algorithms and techniques to thermal power plant fuel management. To develop more advanced and sophisticated reward functions and optimization strategies.

    Deep Reinforcement Learning-Based Intelligent Control for Efficiency Enhancement in Thermal Power Plant Fuel Management · 2026 · DOI

  • Despite the widespread deployment of combined PV–BESS systems in community buildings, the distinct contributions of each technology to energy consumption reduction and electricity cost savings remain poorly quantified under real operational conditions.

    Distinct Contributions of Building-Integrated PV and BESS to Energy and Cost Reduction Using Measured Operational Data · 2026 · DOI

  • The integration of distributed energy resources, flexible electrical loads, and energy sharing mechanisms creates operational and management challenges for REC-based systems. There is a need for advanced tools and methodologies for planning and identifying operational strategies to maximize benefits while ensuring user comfort and avoiding increased energy costs.

    Energy Management and Optimization of Renewable Energy Communities with Flexible Load Coordination and Shared Energy Utilization · 2026 · DOI

  • Future research can focus on testing the framework using real-world data. Future research can focus on comparing the framework with existing methods. Future research can focus on improving the scalability of the framework.

    Knowledge enhanced framework for managing electricity generation and consumption in micro smart grids using Heronian mean MCDM approach · 2026 · DOI

  • The existing methods have limitations in handling uncertain and complex decision-making problems. There is a need for a robust and efficient method for managing electricity generation and consumption in micro smart grids. The paper aims to address this research gap.

    Knowledge enhanced framework for managing electricity generation and consumption in micro smart grids using Heronian mean MCDM approach · 2026 · DOI

  • Existing approaches lack behavioral adaptivity and scalability under dynamic market conditions. There is a need for a novel framework that can optimize load-shifting or consumption strategies in electricity markets.

    Evolutionary game-theoretic modeling of electricity market dynamics for elastic load optimization · 2026 · DOI

  • Future research can focus on improving the development model using more advanced artificial intelligence methods. The study's results can be used as a basis for further research on the National Power System in Poland.

    Selection of Data for Modeling the Development of the Power System Using a Recurrent Artificial Neural Network · 2026 · DOI

  • There is a research gap in obtaining development models of the National Power System using artificial intelligence methods. The gap exists between the need for development models and the possibilities of obtaining such models using artificial intelligence methods.

    Selection of Data for Modeling the Development of the Power System Using a Recurrent Artificial Neural Network · 2026 · DOI

  • The lack of effective management of energy resources in aggregated microgrids. The need for a two-tier DERMS architecture to optimize energy production and consumption.

    Situational Aspect of Power Supply Management in Aggregated Microgrids · 2026 · DOI

  • Existing smart charging approaches typically optimize grid constraints, cost, or user preferences in isolation. There is a need for an integrated approach that considers multiple objectives simultaneously.

    DAM Price-Based Model Predictive Control for Smart EV Charging under Grid and User Constraints · 2026 · DOI

  • Additionally, the demonstrated system scale is limited to a small number of chargers, and further validation is required for larger deployments. This study addressed the challenge of integrating grid constraints, cost optimization, and user preferences within a unified smart EV charging framework, which is insufficiently explored in existing literature.

    DAM Price-Based Model Predictive Control for Smart EV Charging under Grid and User Constraints · 2026 · DOI

Most-cited papers in Smart Grid Energy Management

Most recent work

Find a gap in your own Smart Grid Energy Management sub-topic

This page shows what the Smart Grid Energy Management literature already flags as unresolved. To narrow it to your specific question, run the guided finder — it searches the gap library on demand and checks candidates against 250M+ OpenAlex works.

Open the Research Gap Finder →

Related topics in Engineering

Traffic and Road Safety
237 open questions
Concrete and Cement Materials Research
196 open questions
Digital Transformation in Industry
190 open questions
Design Education and Practice
167 open questions
Machine Fault Diagnosis Techniques
165 open questions
Smart Cities and Technologies
152 open questions
Spatial Cognition and Navigation
149 open questions
BIM and Construction Integration
145 open questions
54 open questions have been extracted from the limitations and future-work passages of 324 Smart Grid Energy Management papers in our library. Each one below links back to the study that raised it, so you can read the original claim in context.

Tools for your next paper

Gaps & Literature SearchFind open questions in any field — 120,000+ open gaps mined from our own library.Pre-CheckIs your paper ready? A Tier 1–5 acceptance probability in seconds.Journal FinderA ranked shortlist of target journals from a 17,500-venue index.Duplicate Publication CheckerCheck prior-publication & salami-slicing risk across 8 sources.Citation GeneratorFreeA DOI or title → APA, MLA, Vancouver, Chicago, BibTeX, RIS. No signup.Graphical Abstract MakerFreeTurn your findings into a colorblind-safe graphical abstract.

Compare the category — Honest roundups of the AI research tools, ours listed alongside the alternatives.

Command palette

Jump anywhere, run any action.