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비만아 부모의 돌봄 경험: q 방법론

Overview of current development in electrical energy storage technologies and the application potential in power system operation

Hydrogen energy, economy and storage: Review and recommendation

Blockchains or distributed ledgers are an emerging technology that has drawn considerable interest from energy supply firms, startups, technology developers, financial institutions, national governments and the academic community. Numerous sources coming from these backgrounds identify blockchains as having the potential to bring significant benefits and innovation. Blockchains promise transparent, tamper-proof and secure systems that can enable novel business solutions, especially when combined with smart contracts. This work provides a comprehensive overview of fundamental principles that underpin blockchain technologies, such as system architectures and distributed consensus algorithms. Next, we focus on blockchain solutions for the energy industry and inform the state-of-the-art by thoroughly reviewing the literature and current business cases. To our knowledge, this is one of the first academic, peer-reviewed works to provide a systematic review of blockchain activities and initiatives in the energy sector. Our study reviews 140 blockchain research projects and startups from which we construct a map of the potential and relevance of blockchains for energy applications. These initiatives were systematically classified into different groups according to the field of activity, implementation platform and consensus strategy used. 1 Opportunities, potential challenges and limitations for a number of use cases are discussed, ranging from emerging peer-to-peer (P2P) energy trading and Internet of Things (IoT) applications, to decentralised marketplaces, electric vehicle charging and e-mobility. For each of these use cases, our contribution is twofold: first, in identifying the technical challenges that blockchain technology can solve for that application as well as its potential drawbacks, and second in briefly presenting the research and industrial projects and startups that are currently applying blockchain technology to that area. The paper ends with a discussion of challenges and market barriers the technology needs to overcome to get past the hype phase, prove its commercial viability and finally be adopted in the mainstream.

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Blockchain technology in the energy sector: A systematic review of challenges and opportunities

Parameter identification of a highly promising cleaner coal power station

The rapid development and the low cost of the communication networks made them a viable alternative to conventional wiring in distributed energy systems. Closing the feedback through a communication network forms a networked control system which is characterized by time delay and packet loss. However, exchanging the control signals over communication networks reduces the complexity in the wiring and enhances the reliability, the induced time delay and data loss could lead to system instability. The most widely approach for modeling the time delay and the packet loss is through using Markov chains. The paper addresses the stability of parallel DC/DC Buck converters over CAN bus. The networked converters system is formulated as standard Markovian Jump System. The stochastic stability of the parallel DC/DC converters controlled through the CAN is investigated in the paper. The resulting stability problem is in the form of Linear Matrix Inequality. The range of the controller parameter that achieve the stochastic stability of the system over the CAN is calculated.

Networked control of parallel DC/DC converters over CAN bus

This paper presents a new approach for deriving a power system aggregate load area model (ALAM). In this approach, an equivalent area load model is derived to represent the load characters for a particular area load of a power system network. The Particle Swarm Optimization (PSO) method is employed to identify the unknown parameters of the generalised system, ALAM, based on the system measurement directly using a one-step scheme. Simulation studies are carried out for an IEEE 14-Bus power system and an IEEE 57-Bus power system. Simulation results show that the ALAM can represent the area load characters accurately under different operational conditions and at different power system states.

Power System Aggregate Load Area Modelling by Particle Swarm Optimization

Convolutional neural-network-based automatic dam-surface seepage defect identification from thermograms collected from UAV-mounted thermal imaging camera

Jihong Wang

Papers

Parameter identification of a highly promising cleaner coal power station

Networked control of parallel DC/DC converters over CAN bus

Power System Aggregate Load Area Modelling by Particle Swarm Optimization

Convolutional neural-network-based automatic dam-surface seepage defect identification from thermograms collected from UAV-mounted thermal imaging camera

Investigation on the Self-Stabilization Feature of HCCI Combustion