Shanghai University

About: Shanghai University is a education organization based out in Shanghai, Shanghai, China. It is known for research contribution in the topics: Microstructure & Graphene. The organization has 59583 authors who have published 56840 publications receiving 753549 citations. The organization is also known as: Shànghǎi Dàxué.

A Secure Charging Scheme for Electric Vehicles With Smart Communities in Energy Blockchain

Abstract: The smart community (SC), as an important part of the Internet of Energy (IoE), can facilitate integration of distributed renewable energy sources and electric vehicles (EVs) in the smart grid. However, due to the potential security and privacy issues caused by untrusted and opaque energy markets, it becomes a great challenge to optimally schedule the charging behaviors of EVs with distinct energy consumption preferences in SC. In this paper, we propose a contract-based energy blockchain for secure EV charging in SC. First, a permissioned energy blockchain system is introduced to implement secure charging services for EVs with the execution of smart contracts. Second, a reputation-based delegated Byzantine fault tolerance consensus algorithm is proposed to efficiently achieve the consensus in the permissioned blockchain. Third, based on the contract theory, the optimal contracts are analyzed and designed to satisfy EVs’ individual needs for energy sources while maximizing the operator’s utility. Furthermore, a novel energy allocation mechanism is proposed to allocate the limited renewable energy for EVs. Finally, extensive numerical results are carried out to evaluate and demonstrate the effectiveness and efficiency of the proposed scheme through comparison with other conventional schemes.

Adaptive Event-Triggering ${H}_{\infty }$ Load Frequency Control for Network-Based Power Systems

Abstract: Load frequency control (LFC) is a very important method to keep the power systems stable and secure. However, due to the introduction of communication networks in multi-area power systems, the traditional LFC method is not effective again. This motivates us to investigate an adaptive event-triggering ${H}_{\infty }$ LFC scheme for multi-area power systems. Compared with the existing time-invariant event-triggering communication scheme, an adaptive event-triggering communication scheme is presented, where the event-triggering threshold can be dynamically adjusted to save more limited network resources, while preserving the desired control performance. Compared with the existing emulation-based method, where the controller must be known a priori , the stability and stabilization criteria derived in this work can provide a tradeoff to balance the required communication resources and the desired control performance. The effectiveness of the proposed method is verified by two numerical examples.

A comparison of power density for axial flux machines based on general purpose sizing equations

Abstract: Based on the concept of the converter fed machine (CFM), an optimal machine design can be considered as the best match of the machine topology, the power electronic converter and the performance specification. To compare power production potential of axial flux machines with various topologies, different waveforms of back EMF and current, general purpose sizing and power density equations for such machines are needed. In this paper, a general approach is presented to develop and to interpret these equations. Sample applications of the sizing and power density equations are the axial flux toroidal permanent magnet utilized to compare the axial flux toroidal permanent magnet (AFTPM) machine and the axial flux two-stator permanent magnet (AF2SPM) machine.