Droop‐based consensus control scheme for economic dispatch in islanded microgrids

Zheng, Shunwei; Liao, Kai; Yang, Jianwei; He, Zhengyou

doi:10.1049/iet-gtd.2020.0507

Cited by 13 publications

(7 citation statements)

References 35 publications

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“…It contains all the information of all nodes registered in the block body within a period of time. The information usually includes status information, transaction information, and code [11]. It is hashed in the form of a Merkle tree and stored on the blockchain, which helps to quickly summarize and verify the accuracy and integrity of the data in the block.…”

Section: Methodsmentioning

confidence: 99%

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Deep Learning Optimization of Microgrid Economic Dispatch and Wireless Power Transmission Using Blockchain

Chen

Guo

Zhao

et al. 2022

Wireless Communications and Mobile Computing

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The purpose is to realize the decentralized microgrid economic dispatch, improve the information transparency and security of microgrid systems, and make the power grid move towards a clean, safe, efficient, and reliable development path. Deep learning optimization of microgrid economic dispatch and wireless power transmission based on blockchain technology are studied. First, the related theories and methods of microgrid systems, wireless power transmission, and deep learning optimization based on blockchain technology are introduced. Next, the microgrid economic dispatch is simulated and analyzed on a large scale. Finally, the comparison results between microgrid economic dispatch and common radio energy transmission technologies are analyzed. The results show that daily planning can better coordinate the state of distributed generation, energy storage system, and public connection. The operation results of the previous day correspond to the long-term operation economy of the microgrid. The total operation cost of the microgrid is 4668 yuan/day, and the remaining power is maintained between 500 and 600 kW, which helps to prevent excessive battery discharge, prolong battery life, and reduce operation cost. The simulation results show that the total power imbalance of the microgrid can reduce the output fluctuation of controllable load shedding of distributed generation. When the load characteristics are not important, the output fluctuation of controllable distributed generation can be reduced. The proposed economic dispatch model can optimize the data security, information storage, and information release of the microgrid and has a certain guiding role for the development of the national power grid and power industry.

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Section: Methodsmentioning

confidence: 99%

“…If the input of Softmax is z, the output is b, and the loss function is loss, (10) and (11) are the back propagation equations:…”

mentioning

confidence: 99%

Deep Learning Optimization of Microgrid Economic Dispatch and Wireless Power Transmission Using Blockchain

Chen

Guo

Zhao

et al. 2022

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

show abstract

“…This control strategy ensures economic dispatch and frequency recovery control while bridging the time gap between AC microgrids and reducing the operation cost. The literature [11] proposes a consistent algorithm scheduling scheme under droop control, which realizes the fully distributed economic dispatch of microgrids that does not rely on the central processor, but their convergence speed is usually slow. The authors in Ref.…”

Section: Introductionmentioning

confidence: 99%

Economic Dispatch of Microgrid Based on Load Prediction of Back Propagation Neural Network–Local Mean Decomposition–Long Short-Term Memory

Zhang

Ma³

et al. 2022

Electronics

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To plan the work of power generation equipment, it is necessary to ensure that the power supply is sufficient and to achieve the minimum cost to ensure the safety and economy of the microgrid. Based on back propagation neural network–local mean decomposition–long short-term memory (BPNN–LMD–LSTM) load prediction, the design is based on a fixed-time consistency algorithm with random delay to predict the economic dispatch of microgrids. Firstly, the initial power load prediction sequence is obtained by continuous training of the back propagation neural network (BPNN); the residual sequence with other influencing factors is decomposed by local mean decomposition (LMD); and the long short-term memory neural network (LSTM) is used to predict the output prediction residual sequence, and the final short-term power load prediction is obtained. Based on predicting load, the fixed-time consistency algorithm with random delay is used to add supply and demand balance constraints to optimize the power distribution of the power generation units of the distributed microgrid and reduce the power generation cost of the microgrid. The results show that the prediction model has better prediction accuracy, and the scheduling algorithm based on the prediction model has a faster convergence rate to reach the lowest power generation cost.

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“…However, the above literature are only based on the structure of the physical layer and do not consider the security of the information layer, which is extremely vulnerable to malicious attacks on the network. [20][21][22] References [6,12] construct an information-physical collaborative hierarchical control structure and solves random communication problems by designing corresponding observers, controllers, and predictive compensators. In References [23,24], aiming at the insufficient tolerance of MG to DoS attacks when edge routers in microgrid suffer from DoS attacks, a consensus-based secondary frequency controller with dynamic P-f droop control is proposed and its stability is analyzed.…”

Section: Introductionmentioning

confidence: 99%

A Consensus-Based Distributed Two-Layer Control Strategy with Predictive Compensation for Islanded Microgrid CPS against DoS Attack

Liu

Hou

Yang³

et al. 2022

International Transactions on Electrical Energy Systems

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Summary.Aiming at the problems of insufficient scalability and slow response speed of the traditional three-layer control structure based on the time scale, this study proposes a distributed two-layer control structure. The primary control uses traditional power-frequency droop control, and the second-level control adopts a consensus protocol to simultaneously achieve the goals of frequency synchronization, frequency non-difference, and power optimization in a distributed manner, which can effectively improve the performance of microgrid frequency adjustment and power optimization. The cyber layer of the AC microgrid cyber-physical system (CPS) is extremely vulnerable to denial-of-service (DoS) attacks, resulting in the inability to achieve control objectives. For this reason, this paper designs a consensus algorithm based on event-triggered and a predictive compensation control link that combines empirical mode decomposition (EMD) and extreme learning machine (ELM) on the basis of the two-layer control structure. Finally, a 4-node islanded microgrid simulation example is used to verify the effectiveness of the proposed strategy. The simulation results show that the two-layer control strategy can achieve microgrid frequency recovery and power optimization while effectively responding to different degrees of DoS attacks.

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Droop‐based consensus control scheme for economic dispatch in islanded microgrids

Cited by 13 publications

References 35 publications

Deep Learning Optimization of Microgrid Economic Dispatch and Wireless Power Transmission Using Blockchain

Deep Learning Optimization of Microgrid Economic Dispatch and Wireless Power Transmission Using Blockchain

Economic Dispatch of Microgrid Based on Load Prediction of Back Propagation Neural Network–Local Mean Decomposition–Long Short-Term Memory

A Consensus-Based Distributed Two-Layer Control Strategy with Predictive Compensation for Islanded Microgrid CPS against DoS Attack

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