Table 1
Overview of recent reviewed literature sources.
| Paper, Year | Methodology | Key findings and conclusion | Research gaps identified |
|---|---|---|---|
| [5], 2020 | WSN | Implemented cutting edge WSN communication system in the electric grid infrastructure to enable smart monitoring. This integration aimed to enhance the grid’s ability to efficiently share power among its components. | Despite the potential of integrating WSN communication systems in electric grids for enhanced smart monitoring and efficient power sharing, critical research gaps like scalability, grid sizes, optimizing energy efficiency and reliability, cyber security concerns, and assessing economic feasibility. |
| [6], 2021 | ANFIS, IoT | The proposed approach leverages IoT technology and Neuro-Fuzzy concepts for power monitoring, using Simulink software for implementation. It captures key parameters such as power, current, and voltage of the load. | Several future research areas need explorations such as grid sizes and complexities, optimizing Neuro-Fuzzy algorithms for real-time efficiency, ensuring interoperability with existing grid infrastructures and protocols. |
| [7], 2017 | IoT | They developed a specialized smart grid framework for smart homes, utilizing Internet of Things (IoT) capabilities. Their focus was on exploring IoT’s dual potential in supporting smart home and grid technologies. | Research new methods for optimizing the integration of renewable energy sources into smart grids, addressing challenges such as intermittency, grid stability, and regulatory compliance. |
| [8], 2019 | IoT | They proposed an approach for IoT-assisted energy management, emphasizing its extensive applications within smart cities and the rising energy demands from these IoT applications. | Research advanced real-time data analytics and machine learning techniques tailored to the specific needs of IoT energy management. |
| [9], 2019 | IoT | They utilized deep reinforcement learning within edge computing to develop an IoT-based energy management system. Beginning with an exploration of IoT energy management in smart cities, they leveraged edge computing to integrate an IoT-based software model and architecture. | Research methods to effectively incorporate renewable energy into the edge computing infrastructure, ensuring reliable and efficient energy management. |
| [10], 2016 | DES | Presented a control strategy that incorporates Distributed Energy Storage (DES) systems into MGs. Managing MGs with numerous small-scale DES systems necessitated the development of scalable control strategies capable of handling disturbances in both communication and power networks. | The integration of DES into power networks introduces longer time-scale dynamics associated with the charge levels of storage systems, which complicates the control challenges of the network due to increased complexity. |
| [11], 2020. | IoT | Proposed an energy management strategy that uses an IoT-assisted system to optimize renewable energy generation. Their approach monitors and controls various aspects of solar and wind power generation using IoT technology. | Investigate methods to effectively integrate and manage diverse renewable energy sources within a single IoT-assisted system, ensuring optimal performance and stability. |
| [12], 2019 | EMS | Conducted an inquiry into the complexities and constraints of energy management in the distribution system. They explored limitations such as technological constraints, regulatory barriers, and economic considerations in implementing effective energy management strategies. | Explore real-time monitoring technologies and control algorithms that can enhance the responsiveness and reliability of energy management systems. |
| [13], 2021 | IoT | Investigated the utilization, prototype development, and architectural framework of IoT-assisted SG. Explored IoT-enabled devices, communication protocols, data analytics methodologies, and control strategies within Smart Grid infrastructures. | Investigate and develop standardized communication protocols and interoperable frameworks to ensure seamless integration and communication across diverse IoT devices and platforms in Smart Grid infrastructures. |
| [14], 2018. | ACL, WSN | Developed a real-time flow control mechanism for a Photovoltaic (PV) system using Maximum Power Point Tracking (MPPT) technology, by integrating advanced control algorithms, sensors, and communication interfaces for monitoring and adjusting the PV system’s performance in real time. | Develop standardized communication protocols and interfaces that enable seamless integration and interoperability between PV systems and external monitoring/control devices. |
| [15], 2018 | FLC | Implemented fuzzy logic control to optimize power generation in a PV system under varying environmental conditions, including temperature and irradiation levels. | Develop advanced fuzzy logic algorithms that can adaptively adjust to varying environmental parameters such as temperature, irradiation levels, and weather conditions to maximize power output. |
| [16], 2024 | FLC, ANN, FACTS devices | Integrating renewable energy sources into traditional models, addressing constraints, exploring deregulated load frequency control and developing tailored strategies for micro grids. | Future research focus on modern systems like micro grids, nano-grids, and IoT enabled smart grids require real-time implementation via software like opal-RT or RTDS. |
| [17], 2024 | GWO-ANN, IoT | Solar power maximums are tracked using a Grey Wolf Optimized Artificial Neural Network (GWO-ANN). Sensors are used to monitor temperature, intensity, converter voltage and current, with data stored on an IoT webpage for analysis. | A future research gap could focus on advancing machine learning techniques for optimizing renewable energy converters in micro grid and smart grid settings by exploring complex neural network architectures/hybrid models. |
| [18], 2024 | PI, ANFIS | Integrates a PI controller and an ANFIS-based MPPT algorithm to dynamically adjust the duty cycle, improving power output. This results in an 18.09% increase in power generation. | The comparative performance benefits and practical implementation challenges of ANFIS- based MPPT over conventional methods need to be quantified and should be validated. |
| [19], 2022 | PI, ANFIS, VSC. | A permanent magnet synchronous generator is used to maximize wind power, while back-to-back voltage source converters with an intelligent ANFIS controller optimize overall power generation. | Research gap focus on the impact of higher power outputs on grid dynamics, including voltage regulation, power quality, incorporating real-time data monitoring techniques with the integration of RESs. |
| [20], 2022 | PI, ANFIS | This work demonstrates the effectiveness of using intelligent techniques to tune conventional PI controllers for simultaneously addressing multiple power quality issues. | The scalability of intelligent techniques for tuning PI controllers in large-scale power systems and their practical implementation in real-world scenarios need further investigation. |
| [21], 2023 | IoT | The proposed study utilizes IoT technology for power monitoring in substations and smart grids to enhance load management, energy consumption tracking, load pattern analysis, real-time monitoring, and active decision-making. | Addressing the integration challenges of RESs into smart grids is a critical research gap. Studies should focus on mitigating grid instability, and improving power quality. |
| [22], 2023 | IoT, WSN, Aurdino | This research article implements an IoT-enabled micro grid system utilizing Wireless Sensor Networks to measure temperature, voltage, and current by enabling remote monitoring and control of grid components, facilitated by an Arduino controller. | Further research is needed to integrate RESs into IoT-enabled micro grid systems, optimizing their integration to enhance grid stability, maximize energy efficiency. |
| [23], 2023 | GRFO-ITSA | Improves active power management in grid-connected PV-PEV systems. | Integration of multiple renewable sources beyond PV (e.g., wind, hydro) needs further exploration. |
| [24], 2023 | MPPT | The effectiveness of the multi-port converter in MPPT operation, improvements in performance metrics and system efficiency. | Potential limitations in the current design need improvements and approaches that could be explored be used for RES integration. |
| [25], 2022 | IoT, Smart Meter | The research integrates an IoT module and Smart Meters for efficient energy management and data analysis. It collects and transmits data to a Cloud Analytics layer, providing daily/hourly energy consumption using IoT protocols. | To devise and assess various Demand Response and Demand Side Management strategies in the future including Arduino-based intelligent system to autonomously control HVAC units efficiently, while also integrating RESs. |
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.