Regional Power Grid AGC Control Strategy Research Based on Q-Learning Algorithm Under WACPB Mode

Zhao, Xiangyu; Yao, Gang; Nianjie, Tian; Jiang, Dai; Su, Huaying

doi:10.1109/isgt-asia.2019.8881102

Cited by 6 publications

(1 citation statement)

References 14 publications

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“…are being integrated with electrical network or grids for different applications such as Substation Automation (SA), transmission/distribution line monitoring, outage management, wide-area situational awareness (WASA), demand response, Advanced Metering Infrastructure (AMI), home energy management (HEM), PHEV, distributed energy resource (DER), power storage system, Blockchains and Asset management (AM) [25]. In this regard, several major objectives toward energy issues can be addressed such as energy saving, green [42], [43], [44], [45], [46], [47], [48], [49], [50], [51], [52], [53].…”

Section: B Concept and Perspectives Of Electrical Utility Industry 40mentioning

confidence: 99%

Intelligent Computing in Electrical Utility Industry 4.0: Concept, Key Technologies, Applications and Future Directions

et al. 2022

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Industry 4.0 (I-4.0) is referred to as 'fourth industrial revolution' towards incorporation of artificial intelligence and digitalization of industrial systems. It is meticulously associated with the development and advancement of evolving technologies such as: Internet of Things, Cyber-Physical System, Information and Communications Technology, Enterprise Architecture, and Enterprise Integration. Power systems of today face several challenges that need to be addressed and application of these technologies can make the modern power systems become more effective, reliable, secure, and cost-effective. Therefore, a widespread analysis of I-4.0 is performed in this paper and a summary of the outcomes, future scope, and real-world application of I-4.0 on the electrical utility industry (EUI) is reported by reviewing the existing literature. This report will be helpful to the investigators interested in the area of I-4.0 and for application in EUI. INDEX TERMSDigitalization, electrical utility industry, Industry 4.0, smart grid, the Internet of Things, communication infrastructure, cyber physical system. NOMENCLATURE 13 AI Artificial Intelligence. AM Asset Management. AMI Advanced Metering Infrastructure. BAN Building Area Network. CC Cloud Computing. CPPS Cyber-Physical Power System. CPS Cyber Physical System. DL Deep Learning. DMC Data Matrix Codes. Electrical industry has no relation with the first industrial18 revolution (Industry-1.0 or I-1.0). However, the second indus-19 trial revolution (I-2.0) was initiated in the 19th century after 20 the developments in the domain of electricity. The third 21 industrial revolution (I-3.0) started in the 1970's via limited 22 automation using memory-programmable controls and com-23 puters. Recently, the fourth industrial revolution (Industry-24 4.0 or I-4.0) is taking place. I-4.0 is generally characterized 25 by the application of Information and Communication Tech-26 nologies (ICTs), Internet of Things (IoT) and Cyber-Physical 27 Systems (CPS) to the industry. Several key components of 28 I-4.0 are shown in Fig. 1. 29 Proper integration of the traditional electric power system 30 with advanced information, communication, protection and 31 control technologies is one of the important developments 32 in making the modern power systems smarter. These tech-33 nologies help in providing effective solution to the challenges 34 of automation, monitoring, optimizing, and managing each 35 component of the power system [1], [2], [3]. The environ-36 mental concerns about generating electricity using fossil fuels 37 and global warming have motivated the Electrical Utility 38 Industry (EUI) towards renewable energy sources (RES).39 The main purpose of incorporating new technologies is to 40 achieve cost-effective performance of power systems with 41 good efficiency, high reliability, better flexibility, improved 42 resiliency, and high security in the presence of demand 43 response, demand-side management, plug-in hybrid electric 44 vehicles (PHEVs), RES, and plug-in electric vehicles (...

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Section: B Concept and Perspectives Of Electrical Utility Industry 40mentioning

confidence: 99%

Intelligent Computing in Electrical Utility Industry 4.0: Concept, Key Technologies, Applications and Future Directions

et al. 2022

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Review and outlook on reinforcement learning: Its application in agricultural energy internet

Fu,

Zhang,

Bai

et al. 2024

IET Renewable Power Gen

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Agricultural Energy Internet (AEI), representing a key evolutionary direction in the integrated energy landscape of rural regions, holds a vital position in advancing the electrification of agricultural sectors. However, the disjointed control between agricultural loads and grid operations hinders the collaborative development of agriculture and energy. Addressing these issues, this paper investigates the current applications of artificial intelligence in the fields of agriculture and energy. The authors examine the evolutionary path of AEI, particularly emphasizing the critical technologies emerging from the intersection of agriculture, energy, and digital networks. Furthermore, the authors examine the critical technologies of reinforcement learning in the context of smart grid applications. In response to the challenges posed by low energy efficiency in rural areas, a reinforcement learning framework is proposed for coordinating fisheries, agriculture, livestock farming, and rural distribution networks. This framework provides a clear pathway for the application of reinforcement learning in AEI. This research acts as a conduit, merging agricultural and energy domains to promote a cohesive progression that markedly aids in the enhancement of rural electrification and the adoption of sustainable energy methodologies through reinforcement learning.

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Frequency control for islanded AC microgrid based on deep reinforcement learning

Liu

Chi

et al. 2022

Cyber-Physical Systems

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Regional Power Grid AGC Control Strategy Research Based on Q-Learning Algorithm Under WACPB Mode

Cited by 6 publications

References 14 publications

Intelligent Computing in Electrical Utility Industry 4.0: Concept, Key Technologies, Applications and Future Directions

Intelligent Computing in Electrical Utility Industry 4.0: Concept, Key Technologies, Applications and Future Directions

Review and outlook on reinforcement learning: Its application in agricultural energy internet

Frequency control for islanded AC microgrid based on deep reinforcement learning

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