Closed-loop home energy management system with renewable energy sources in a smart grid: A comprehensive review

Ali, Abdelrahman O.; Elmarghany, Mohamed R.; Abdelsalam, Mohamed M.; Sabry, Mohamed; Hamed, Ahmed M.

doi:10.1016/j.est.2022.104609

Cited by 52 publications

(11 citation statements)

References 93 publications

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“…This literature emphasizes the need for sophisticated and adaptable energy management systems that can efficiently use the potential of renewable sources within the dynamic structure of smart grids. [16][17][18][19][20] Renewable Energy Management Challenges: The sporadic nature of renewable energy production presents obstacles for traditional energy management systems. Complex control methods are necessary to effectively use solar radiation, wind speed, and biomass supply, which might vary.…”

Section: Literature Reviewmentioning

confidence: 99%

Fuzzy Logic-Based Energy Management in Smart Grids for Renewable Integration

Sharma,

Raju,

Dhall

et al. 2024

E3S Web Conf.

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This study presents a novel Fuzzy Logic-Based Energy Management model that aims to optimize the incorporation of renewable energy sources into smart grids. The research used simulated data to evaluate the model’s performance in important metrics, revealing significant improvements in the consumption of renewable energy, stability of the grid, dependability of energy storage, and overall efficiency of the system. The Fuzzy Logic Controller adjusts energy distribution in response to current inputs, leading to a significant 20% improvement in the usage of renewable energy. The capacity to adapt is crucial in dealing with the inherent fluctuation of solar, wind, and biomass sources. The approach greatly improves grid stability, as shown by a 15% decrease in grid frequency variations, highlighting its efficacy in assuring a more regulated and steady electricity supply. Furthermore, the dependability of energy storage systems exhibits a notable 25% enhancement in the state of charge, suggesting optimal cycles of charging and discharging. This increased dependability enhances the stability of the energy supply during times of high demand and variations in the power system. The Fuzzy Logic-Based Energy Management model exhibits a significant 22% improvement in total system efficiency when compared to conventional management systems. This indicator encompasses the model’s combined effect on the usage of renewable energy, the stability of the power grid, and the optimization of energy storage. Comparative analyses conducted against traditional control strategies, such as proportional-integralderivative controllers, consistently demonstrate the superiority of the fuzzy logic approach. This approach results in a 10% decrease in grid frequency deviations, a 15% enhancement in energy storage state of charge, and a 12% boost in overall system efficiency. The resilience of the Fuzzy Logic Controller is highlighted by sensitivity analysis, since it demonstrates consistent performance even when parameters vary significantly. The model’s practical usefulness and adherence to ethical principles are further confirmed by validation using real-world data from operational smart grid installations. This study provides valuable insights, establishing the Fuzzy Logic-Based Energy Management model as an innovative method for addressing the difficulties associated with integrating renewable energy into smart grids. This model promotes a more sustainable and efficient energy environment for the future.

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Section: Literature Reviewmentioning

confidence: 99%

Fuzzy Logic-Based Energy Management in Smart Grids for Renewable Integration

Sharma,

Raju,

Dhall

et al. 2024

E3S Web Conf.

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“…The essential flexibility of the PEVs in both performance modes of electrical source/load has recently absorbed the attention of academic and industrial individuals to more investigate and exploit the operational advantages of such technology in modern power systems [1,2]. At the same context, the extensive potential of RESs such as photovoltaic (PV) units, wind turbine (WT) units, fuel cells, geothermal energy, battery energy storage system (BESS), etc., as supportive low-emission cost power sources has been growingly taken into consideration in smart distribution grids [3][4][5]. In this way, the helpful role of PV/WT units in charging a PEV battery specifically in off-peak electrical energy prices can potentially lead to reduction in operation costs.…”

Section: Introductionmentioning

confidence: 99%

A Robust Renewable Energy Source-oriented Strategy for Smart Charging of Plug-in Electric Vehicles Considering Diverse Uncertainty Resources

Ahmadigorji

Mehrasa

2023

IJE

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“…Thus, distribution networks face difficulties in supporting power system frequency during faults in case of large-scale integration of RESs such as distributed generators (DGs) [2]. Another challenge is that the RESs have intermittency in power generation, further exasperating frequency control [3].…”

Section: Introductionmentioning

confidence: 99%

Frequency Stabilization of AC Microgrid Clusters: An Efficient Fractional Order Supercapacitor Controller Approach

et al. 2022

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An autonomous microgrid is often formed by incorporating distributed generators into the distribution system. However, distributed generators have less inertia compared to traditional synchronous generators, and can cause the system frequency to become unstable. Additionally, as more clusters are integrated into the distribution microgrid, frequency instability increases. To resolve frequency instability in the microgrid cluster, this study proposes a supercapacitor control approach. The microgrid consists of several clusters which integrate wind power generators, solar PV, STP, fuel cells, aqua electrolyzers, and diesel generators. Initially, a small signal model is developed to facilitate the control design. A fractional-order supercapacitor controller is augmented with the developed small-signal model to stabilize the frequency of the microgrid. Furthermore, the controller parameters are optimized to guarantee robust controller performance. The proposed fractional-order supercapacitor controller provides more degrees of freedom compared to the conventional controller. Time-domain simulations were carried out considering several real-time scenarios to test the performance of the proposed controller. We observed that the presented approach is capable of stabilizing the system frequency in all cases. Furthermore, the proposed approach outperforms existing approaches in stabilizing the frequency of the microgrid cluster.

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Closed-loop home energy management system with renewable energy sources in a smart grid: A comprehensive review

Cited by 52 publications

References 93 publications

Fuzzy Logic-Based Energy Management in Smart Grids for Renewable Integration

Fuzzy Logic-Based Energy Management in Smart Grids for Renewable Integration

A Robust Renewable Energy Source-oriented Strategy for Smart Charging of Plug-in Electric Vehicles Considering Diverse Uncertainty Resources

Frequency Stabilization of AC Microgrid Clusters: An Efficient Fractional Order Supercapacitor Controller Approach

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