Challenges of blockchain in new generation energy systems and future outlooks

2022 ◽  
Vol 135 ◽  
pp. 107499
Author(s):  
Tonghe Wang ◽  
Haochen Hua ◽  
Zhiqian Wei ◽  
Junwei Cao
Keyword(s):  
Energy Systems ◽  
New Generation

scholarly journals Conceptualization of a new generation of smart energy systems and the transition toward them using anticipatory systems

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Zahra Heidari Darani ◽  
Mohsen Taheri Demne ◽  
Darush Mohammadi Zanjirani ◽  
Ali Zackery
Keyword(s):  
Energy Systems ◽  
Energy System ◽  
Distributed Management ◽  
Common Pool ◽  
Smart Energy Systems ◽  
Anticipatory System ◽  
Anticipatory Systems ◽  
New Generation ◽  
Technical Considerations

AbstractEmerging energy systems are inherently different from their conventional counter-parts. To address all issues of these systems, comprehensive approaches of transdisciplinary and post-normal sciences are needed. This article tries to re-conceptualize emerging energy systems using Robert Rosen’s theory of anticipatory system and introduces the concept of the anticipatory smart energy system (ASES). Three important features of an ASES are described and socio-technical considerations for realization of these features are discussed. The article also considers realization of such systems under society 5.0 paradigm and spime techno-culture. In ASESs, the identity of users evolves and new identities are created for energy users, based on the production, consumption, storage, and distributed management of energy. An Anticipatory energy system can manage a common pool of prosumaging.

scholarly journals Task 39 Exhibition – Assembly of Polymeric Components for a New Generation of Solar Thermal Energy Systems

2014 ◽  
Vol 48 ◽  
pp. 130-136 ◽  
Author(s):  
Michael Koehl ◽  
Sandrin Saile ◽  
Andreas Piekarczyk ◽  
Stephan Fischer
Keyword(s):  
Thermal Energy ◽  
Energy Systems ◽  
Solar Thermal ◽  
Solar Thermal Energy ◽  
New Generation

Fusion of Gaussian Process Kernel Regressors for Fault Prediction in Intelligent Energy Systems

2016 ◽  
Vol 25 (04) ◽  
pp. 1650023 ◽  
Author(s):  
Miltiadis Alamaniotis ◽  
Lefteri H. Tsoukalas
Keyword(s):  
Gaussian Process ◽  
Energy Systems ◽  
Predictive Distribution ◽  
Machine Intelligence ◽  
Fault Prediction ◽  
Linear Predictor ◽  
Statistical Measures ◽  
Data Points ◽  
Fault State ◽  
New Generation

Integration of energy systems with machine intelligence technologies advances the new generation of intelligent energy systems. One feature of intelligent energy systems is their ability to predict a future fault state (prognosis), and thus support control actions. This paper introduces a prognostic framework based on concepts originating from the machine learning universe and proceeds to assess the performance of the prognostics algorithms with statistical methods aiming to formulate a linear predictor whose coefficients are the solution of a multi-objective optimization problem. Prediction is achieved through independent Gaussian process kernel regressors put together as terms of a linear forecaster. In this novel framework the available data is used to train the regression models whose degradation predictions cover a predetermined time period and have the form of a predictive distribution whose mean and variance values are computed for future moments. Thus, given the observed data points one may search for the most probable values of other quantities of interest, or the values at different points from those measured. The feasibility of the cascading prognostics methodology is demonstrated via a turbine blade degradation example. This implementation is characterized by advantages that include the utilization of an optimization process that simultaneously determines the lowest possible values in a set of different statistical measures and the employment of a set of kernels for modeling various data features and capturing the system dynamics.

scholarly journals Recent Advance and Future Progress of GaN Power Semiconductor Devices Used in PV Module Integrated Converters

2018 ◽  
Author(s):  
Oscar Miguel Rodríguez-Benítez ◽  
Mario Ponce Silva ◽  
Leobardo Hernández González ◽  
Juan Antonio Aqui-Tapia ◽  
Abraham Claudio Sánchez ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Semiconductor Devices ◽  
Energy Systems ◽  
Basic Structure ◽  
Superior Performance ◽  
Renewable Energy Systems ◽  
Power Semiconductor ◽  
Power Semiconductor Devices ◽  
Switching Losses ◽  
New Generation

Power semiconductor devices are essential from the operation point of view, size, efficiency and cost, these components are used in a myriad of applications, providing features that make them an important part of the system in which they are operating. This document analyzes and compares the basic structure, properties, design aspects, as well as temperature performance, stability and switching losses, present in devices on silicon (Si), silicon carbide (SiC) and new generation devices fabricated in gallium nitride (GaN) applied in renewable energy systems. The main objective is determinate the viability of the new generation components, which present a superior performance in view of an increase in efficiency, conductivity, decreases in switching losses, lower resistances and parasitic capacitances as well as higher operating frequency range. Therefore demonstrating the GaN components are a strong and viable candidate to solve some of the problems present in renewable energy systems.

Computer Simulations of Solar Energy Systems

2013 ◽  
pp. 320-337 ◽  
Author(s):  
Akram Gasmelseed
Keyword(s):  
Computer Simulation ◽  
Solar Energy ◽  
Fdtd Method ◽  
Energy Systems ◽  
Photonic Devices ◽  
Standard Tool ◽  
New Directions ◽  
Fundamental Research ◽  
New Generation ◽  
Difference Time

In recent years, computer simulation has become a standard tool for analyzing solar energy systems. The interaction of light with nanoscale matter can provide greater functionality for photonic devices and render unique information about their structural and dynamical properties. As the field of nanophotonics continues to experience phenomenal growth at both the fundamental research and applications level, computational modeling is essential both for interpreting experiments and for suggesting new directions – for example, in designing of thin-film photovoltaic cells. The demand for computer simulation continues to increase as researchers and developers tackle the tough challenges of designing new generation devices and optimizing current generation devices. This chapter is devoted to the development and application of the Finite-Difference Time-Domain (FDTD) method to solar energy systems. In addition, new models covering the latest advances in nanophotonics technologies, as well as key improvements to the numeric solvers and new usability features, are introduced in this chapter.

scholarly journals There is need in new generation smart grid for the space and ground energy systems

2018 ◽  
Vol 158 ◽  
pp. 01001
Author(s):  
Alexander Ageev ◽  
Svetlana Bortalevich ◽  
Evgeny Loginov ◽  
Alexander Shkuta ◽  
Dmitry Sorokin
Keyword(s):  
Smart Grid ◽  
Electric Power ◽  
Energy Systems ◽  
Energy System ◽  
Transfer Energy ◽  
New Generation ◽  
Ground Energy ◽  
Made In ◽  
Ground Systems ◽  
Dynamic Indicators

The aim of the article is to considerate the opportunities of synchronization of the space and ground systems that generate and transfer energy on the basis of new generation smart grid using. The authors substantiate the necessity of new intellectual monitoring services that assess the processes took place in "generation-transportation-distribution-consumption" space and ground systems. This is made in order to improve the dynamic indicators of the energy system and to avoid the emergencies. The authors also give a prognosis of the dynamic indicators of the electric power super-system in analyzing metastable conditions in different energy modes.

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