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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

The paper presents the progress of our study of the whole process mathematical model for a supercritical coal-fired power plant. The modelling procedure is rooted from thermodynamic and engineering principles with reference to the previously published literatures. Model unknown parameters are identified using Genetic Algorithms (GAs) with 600MW supercritical power plant on-site measurement data. The identified parameters are verified with different sets of measured plant data. Although some assumptions are made in the modelling process to simplify the model structure at a certain level, the supercritical coal-fired power plant model reported in the paper can represent the main features of the real plant once-through unit operation and the simulation results show that the main variation trends of the process have good agreement with the measured dynamic responses from the power plants.

Mathematical Modelling for Coal Fired Supercritical Power Plants and Model Parameter Identification Using Genetic Algorithms

Pneumatic actuators exhibit highly nonlinear characteristics due to air compressibility, significant friction presence and the nonlinearities of control valves. The unknown nonlinear parameters can not be directly measured once the actuators have been manufactured and assembled, which causes a great difficulty in pneumatic system modeling and control. A learning algorithm has been developed in this paper to identify the unknown pneumatic system parameters. The algorithm is initially developed and tested using the data generated by simulations. Then the algorithm has been extended onto the parameter identification using the data obtained from the real system measurement. The results revealed the characteristics of uneven distribution of friction parameters which are position, velocity, moving direction dependent. The results obtained in the paper can provide the manufacturers with the observation to the characteristics inside pneumatic cylinders.

Parameter identification for nonlinear pneumatic cylinder actuators

The paper considers two models of induction machines accounting for magnetic saturation. The first is a systematically-designed model based on fundamental principles, while the second is a simplified model that neglects certain terms in the first model. The paper shows that both models predict the same responses in the linear region, as well as in the nonlinear region but only for steady-state operation. To investigate the possible superiority of one model over the other, the paper considers the measurement of transient responses where the models predict different behaviors. Experimental conditions are planned by computing the eigenvalues of the linearized systems and selecting conditions with maximal differences in settling time. Surprisingly, however, the experimental data shows relatively little differences between the predictions of the models and fails to favor one model over the other.

Comparison of two magnetic saturation models of induction machines

Compressed-air energy storage (CAES) plants operate by using motors to drive compressors, which compress air to be stored in suitable storage vessels. The energy stored in the compressed air can be released to drive an expander, which in turn drives a generator to produce electricity. Compared with other energy storage (ES) technologies, CAES plants have a very large power rating and storage capacity, low self-discharge, and a long lifetime. These attributes make it the most promising and cost-effective method for bulk ES grid services. Conventional CAES plants have a relatively low roundtrip efficiency; however, research studies into more advanced CAES concepts, such as adiabatic and isothermal CAES, seek to improve this. The world has a large capacity for storing compressed air underground, meaning that CAES could provide a significant amount of the world's future ES needs. This chapter gives the working principals of CAES, compares CAES with other ES technologies, lists the grid services that CAES is most suited to, introduces advanced CAES designs and current projects, examines the exergy analysis of CAES plants and components, reports the global potential for CAES, and offers future research directions and challenges.

Compressed-Air Energy Storage

As the number of renewable energy sources connected to the grid has increased, the need to address the intermittency of these sources becomes essential. One solution to this problem is to install energy storage technologies on the grid to provide a buffer between supply and demand. One such energy storage technology is Compressed Air Energy Storage (CAES), which is suited to large-scale, long-term energy storage. Large scale CAES requires underground storage caverns, such as the salt caverns situated in the Cheshire Basin, UK. This study uses cavern data from the Cheshire Basin as a basis for performing an energy and exergy analysis of 10 simulated CAES systems to determine the exergy storage potential of the caverns in the Cheshire Basin and the associated work and power input and output. The analysis revealed that a full charge of all 10 caverns could store 25.32 GWh of exergy, which can be converted to 23.19 GWh of work, which requires 43.27 GWh of work to produce, giving a round trip efficiency of around 54%. This corresponds to an input power of 670.07 GW and an output power of 402.74 GW. The Cheshire Basin could support around 100 such CAES plants, giving a potential total exergy storage capacity of 2.53 TWh and a power output of 40 TW. This is a significant amount of storage which could be used to support the UK grid. The total exergy destroyed during a full charge, store, and discharge cycle for each cavern ranged from 299.02 MWh to 1600.00 MWh.

https://www.mdpi.com/1099-4300/21/11/1065/pdf

Jihong Wang

Papers

Mathematical Modelling for Coal Fired Supercritical Power Plants and Model Parameter Identification Using Genetic Algorithms

Parameter identification for nonlinear pneumatic cylinder actuators

Comparison of two magnetic saturation models of induction machines

Compressed-Air Energy Storage

Potential Exergy Storage Capacity of Salt Caverns in the Cheshire Basin Using Adiabatic Compressed Air Energy Storage