FL is a machine learning approach that allows knowledge sharing with privacy maintenance and cost reduction. FL has the potential to revolutionize the smart agriculture sector by enabling farmers to train and deploy m...
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This paper deals with the power allocation and state-of-charge (SoC) balancing problem of battery energy storage systems (BESSs). Firstly, the improved asymptotic state and power observer are designed for parameter es...
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ISBN:
(纸本)9798350375145;9798350375138
This paper deals with the power allocation and state-of-charge (SoC) balancing problem of battery energy storage systems (BESSs). Firstly, the improved asymptotic state and power observer are designed for parameter estimation using the dynamic average consensus (DAC) mechanism. In contrast to current findings, the observers converge at an exponential rate and independent of the initial states of BESSs. Then, a observer-based distributed control strategy conforming to the SoC variation rules is further proposed, which enables BESSs to meet the power needs of microgrids rapidly and avoids overcharging or overdischarging of battery units effectively. Simulation results are given to confirm the effectiveness of proposed control strategy.
This project introduces a significant enhancement to the Rocker-Bogie system. By integrating advanced sensors, including day and night vision cameras, temperature and humidity sensors, and GPS technology, our innovati...
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A Cutting edge modern day technology for the existing conventional power system is the idea of smart grid. To eradicate climate changes, market variations and security of power supply in near future smart grids help i...
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This paper proposes a new load model for inverter-interfaced distributed generator with grid-forming control. The model is described by piecewise functions and easily integrates with synthesis load model. Various dist...
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ISBN:
(纸本)9798350375145;9798350375138
This paper proposes a new load model for inverter-interfaced distributed generator with grid-forming control. The model is described by piecewise functions and easily integrates with synthesis load model. Various disturbances and grid impedances are considered to establish the generic range of model parameters. The model's accuracy was validated in various scenarios.
The smart grid benefits greatly from advanced data processing and communications technology. But security threats continue to interfere with information systems and they also affect smart grids. The smart grid39;s e...
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With a large number of distributed Generation (DG) connected to the distribution network, the distribution network can be reconstructed and isolated island partition for self-healing. In this paper, the two-layer conf...
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ISBN:
(纸本)9798350375145;9798350375138
With a large number of distributed Generation (DG) connected to the distribution network, the distribution network can be reconstructed and isolated island partition for self-healing. In this paper, the two-layer configuration DG operation-planning joint optimization model for improving self-healing ability of distribution network is established to achieve economy and self-healing ability of the system. ieee33-node system is used to verify the proposed model. The results show that the two-layer model can effectively coordinate the economy and self-healing ability of distribution network through interactive decision-making of DG allocation scheme.
As the problem of population aging becomes increasingly prominent, smart home robots are gradually gaining attention as intelligent assistants for the elderly. However, although there are already many smart home robot...
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Integration complexity and intermittency of distributed energy resources (DERs) raise concerns about grid stability, security, and control of microgrids in various operating modes. MGs sustain reliability due to their...
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The widespread integration of distributed generators (DG) in modern distribution networks poses new challenges for reactive power optimization, with traditional algorithms gradually showing insufficient accuracy in th...
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ISBN:
(纸本)9798350375145;9798350375138
The widespread integration of distributed generators (DG) in modern distribution networks poses new challenges for reactive power optimization, with traditional algorithms gradually showing insufficient accuracy in the solution process. To address this, this paper proposes a reactive power optimization method for distribution networks based on an improved Chernobyl Disaster Optimizer (ICDO). The initial population is optimized using the K-means++ algorithm to enhance the quality of initial solutions, and a local search strategy is integrated into the optimization process to improve the efficiency and accuracy of the algorithm. Finally, through algorithm testing and simulation on the ieee33-node system, the significant advantages of the proposed improved algorithm in terms of optimization performance are validated, showcasing its potential application in the field of reactive power optimization in active distribution networks.
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