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

Chen, Zhiwei; Guo, Wu; Zhao, Ruifeng; Yang, Ling; Xie, Hu

doi:10.1155/2022/2050031

Cited by 5 publications

(3 citation statements)

References 28 publications

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“…Blockchain technology is a decentralized, distributed ledger system that is designed to record transactions in a secure and transparent manner. The technology allows participants to maintain a shared and immutable record of transactions without the need for a central authority or intermediary [25,151,152]. In a blockchain network, transactions are verified and recorded by a network of nodes or computers, which work together to maintain the integrity of the ledger.…”

Section: Blockchain Technologymentioning

confidence: 99%

Digital Transformation of Microgrids: A Review of Design, Operation, Optimization, and Cybersecurity

Irmak

Kabalcı

2023

Energies

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This paper provides a comprehensive review of the future digitalization of microgrids to meet the increasing energy demand. It begins with an overview of the background of microgrids, including their components and configurations, control and management strategies, and optimization techniques. It then discusses the key digital technologies that can be used to improve the performance of microgrids, including distributed energy resources management systems, the Internet of Things, big data analytics, blockchain technology, artificial intelligence, digital twin technology, cloud computing, and augmented reality. The paper also highlights the importance of cybersecurity in microgrids, identifying the potential security vulnerabilities and threats to microgrid cybersecurity, as well as strategies for addressing these challenges. Finally, the paper discusses the barriers and challenges regarding the digitalization of microgrids, including technical complexity, high implementation costs, regulatory barriers, data privacy and security concerns, lack of standardization, interoperability issues, limited technical expertise, and integration with the main grid. Overall, this paper demonstrates the significant potential for digital technologies to transform the future of microgrids. By leveraging advanced technologies and implementing effective cybersecurity measures, microgrids can become more efficient, reliable, and resilient, enabling them to meet the growing demand for energy and contribute to a sustainable energy future.

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Section: Blockchain Technologymentioning

confidence: 99%

Digital Transformation of Microgrids: A Review of Design, Operation, Optimization, and Cybersecurity

Irmak

Kabalcı

2023

Energies

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“…With the development of technology, the value of data will be fully tapped, and data as an asset will become more and more important. For data assets, we have studied data asset management systems, industrial opportunities, data asset credibility assessment models, and data security [20].…”

Section: Introductionmentioning

confidence: 99%

Grid data asset relationship and intelligent classification integrating knowledge graph and Internet of Things

Dou

Hao

2023

Applied Mathematics and Nonlinear Sciences

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With the development of smart grids, power grids have accumulated massive amounts of data in various links such as power generation, transmission, substation, distribution, power consumption, and dispatch. More and more big data applications are beginning to be applied in various professional fields of the power grid. Promote the application and value discovery of smart grid big data through data fusion inside and outside the grid. Grid data has become an important asset for enterprise development, but power grid enterprises lack effective technical means to solve the whole life cycle monitoring and relationship of power grid data assets. Aiming at the relationship between power grid data assets, this paper proposes a set of grid data asset relationship and intelligent classification framework that integrates knowledge graph and Internet of Things. First, the grid knowledge graph extraction relationship is carried out by ProjE algorithm. Then, the relationship between power grid data assets and intelligent classification framework that integrates knowledge graph and Internet is proposed. Finally, the corresponding classification application is proposed by using intelligent classification algorithm. Experimental results show that the intelligent classification accuracy rate can reach 93.12% under the relationship between the knowledge graph and the Internet data assets, which has a new idea for the future development of the relationship between power grid data assets.

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“…In Skolfield and Escobedo (2021), the first and the simplest algorithm for solving OPF problems is presented. Later on, solutions proposed using different conventional optimization techniques, i.e., linear programming, semi-definite programming, interior point method, Lagrangian relaxation, and reduced gradient method in Chen et al (2020); El-Fergany and Hasanien (2020); Li et al (2020); Abd El-sattar et al (2021); Castro et al (2022); Chen et al (2022), are used for solving OPF problems. However, the methods do not obtain optimal solutions as a result of the non-linear features of their objective functions.…”

mentioning

confidence: 99%

An effective solution to the optimal power flow problem using meta-heuristic algorithms

Aurangzeb,

Shafiq,

Alhussein

et al. 2023

Front. Energy Res.

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Financial loss in power systems is an emerging problem that needs to be resolved. To tackle the mentioned problem, energy generated from various generation sources in the power network needs proper scheduling. In order to determine the best settings for the control variables, this study formulates and solves an optimal power flow (OPF) problem. In the proposed work, the bird swarm algorithm (BSA), JAYA, and a hybrid of both algorithms, termed as HJBSA, are used for obtaining the settings of optimum variables. We perform simulations by considering the constraints of voltage stability and line capacity, and generated reactive and active power. In addition, the used algorithms solve the problem of OPF and minimize carbon emission generated from thermal systems, fuel cost, voltage deviations, and losses in generation of active power. The suggested approach is evaluated by putting it into use on two separate IEEE testing systems, one with 30 buses and the other with 57 buses. The simulation results show that for the 30-bus system, the minimization in cost by HJBSA, JAYA, and BSA is 860.54 $/h, 862.31, $/h and 900.01 $/h, respectively, while for the 57-bus system, it is 5506.9 $/h, 6237.4, $/h and 7245.6 $/h for HJBSA, JAYA, and BSA, respectively. Similarly, for the 30-bus system, the power loss by HJBSA, JAYA, and BSA is 9.542 MW, 10.102 MW, and 11.427 MW, respectively, while for the 57-bus system, the value of power loss is 13.473 MW, 20.552, MW and 18.638 MW for HJBSA, JAYA, and BSA, respectively. Moreover, HJBSA, JAYA, and BSA cause reduction in carbon emissions by 4.394 ton/h, 4.524, ton/h and 4.401 ton/h, respectively, with the 30-bus system. With the 57-bus system, HJBSA, JAYA, and BSA cause reduction in carbon emissions by 26.429 ton/h, 27.014, ton/h and 28.568 ton/h, respectively. The results show the outperformance of HJBSA.

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

Cited by 5 publications

References 28 publications

Digital Transformation of Microgrids: A Review of Design, Operation, Optimization, and Cybersecurity

Digital Transformation of Microgrids: A Review of Design, Operation, Optimization, and Cybersecurity

Grid data asset relationship and intelligent classification integrating knowledge graph and Internet of Things

An effective solution to the optimal power flow problem using meta-heuristic algorithms

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