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Artificial Intelligence Based Smart Energy Community management: A Reinforcement Learning Approach

CSEE Journal of Power and Energy Systems 2019年第1期5卷 1-10页

作者： Suyang Zhou Zijian Hu Wei Gu Meng Jiang Xiao-Ping Zhang School of Electrical Engineering Southeast UniversityNanjingChina Department of Computer Science and Engineering University of Notre DameUSA School of Electronic Electrical and System EngineeringUniversity of BirminghamU.K.

This paper presents a smart energy community management approach which is capable of implementing P2P trading and managing household energy storage systems.A smart residential community concept is proposed consisting of domestic users and a local energy pool,in which users are free to trade with the local energy pool and enjoy cheap renewable energy while avoiding the installation of new energy generation *** local energy pool could harvest surplus energy from users and renewable resources,at the same time it sells energy at a higher price than Feed-in-Tariff(FIT)but lower than the retail *** order to encourage the participation in local energy trading,the electricity price of the energy pool is determined by a real-time demand/supply *** this pricing mechanism,retail price,users and renewable energy could all affect the electricity price which leads to higher consumers’profits and more optimized utilization of renewable *** proposed energy trading process was modeled as a Markov Decision Process(MDP)and a reinforcement learning algorithm was adopted to find the optimal decision in the MDP because of its excellent performance in on-going and model-free *** addition,the fuzzy inference system makes it possible to use Q-learning in continuous state-space problems(Fuzzy Q-learning)considering the infinite possibilities in the energy trading *** evaluate the performance of the proposed demand side management system,a numerical analysis is conducted in a community comparing the electricity costs before and after using the proposed energy management system.

关键词： Artificial intelligence distributed management fuzzy Q-learning microgrid reinforcement learning

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An Efficient SDFRM Security System for Blockchain Based Internet of Things

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Intelligent Automation & Soft Computing 2023年第2期35卷 1545-1563页

作者： Vivekraj Mannayee Thirumalai Ramanathan Faculty of Mechanical Engineering Anna UniversityChennai600025Tamil NaduIndia Department of Mechanical Engineering Dr.N.G.P.Institute of Technology641048Tamil NaduIndia

Blockchain has recently sparked interest in both the technological and businessﬁ*** Internet of Things's(IoT)core principle emerged due to the connectivity of several new technologies,including wireless technology,the Inter-net,embedded automation systems,and micro-electromechanical ***-facturing environments and operations have been successfully converted by implementing recent advanced technology like Cloud Computing(CC),Cyber-Physical System(CSP),Information and Communication Technologies(ICT)and Enterprise Model,and other technological innovations into the fourth indus-trial revolution referred to as Industry *** management is deﬁned as the pro-cess of accumulation in order to make better business decisions,and process,secure and store information about a *** the incipient model,there are interconnected contrivances and Machine-to-Machine(M2M)interactions,and transaction data are stored on the *** is a challenging aspect that must be punctiliously considered during the design and development phases of a *** this research article,we proposed a Secure and distributed Framework for Resource management(SDFRM)in Industry 4.0 environments within a distribu-ted and collaborative Industry 4.0 system,the dynamic and trust-based distributed management Framework(DMF)of shared resource *** issues are focused by taking into account of the traditional characteristics of IoT/Industrial Internet of Things’(IIoT)-predicated environments,an SDFRM in Industry 4.0 environments within a distributed and collaborative Industry 4.0 ***,to ensure strong privacy over the procedures associated with Access Control(AC),a privacy-preserving method is proposed and integrated into the *** proposed DMF,based on blockchain technology and peer-to-peer networks,allows dynamic access management and system governance without using third parties who could be *** worked hard to design and implement the pro-posal to demonstrate its

关键词： Internet of things blockchain data privacy security system distributed management IIoT

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