Soft Computing Applications in Thermal Energy Systems

2011 ◽  
pp. 1-35 ◽  
Author(s):  
Arturo Pacheco-Vega
Keyword(s):  
Soft Computing ◽  
Thermal Energy ◽  
Energy Systems

scholarly journals Self-Sufficiency and Energy Savings of Renewable Thermal Energy Systems for an Energy-Sharing Community

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4284
Author(s):  
Min-Hwi Kim ◽  
Youngsub An ◽  
Hong-Jin Joo ◽  
Dong-Won Lee ◽  
Jae-Ho Yun
Keyword(s):  
Renewable Energy ◽  
Energy Storage ◽  
Thermal Energy ◽  
Thermal Energy Storage ◽  
Energy Systems ◽  
Hot Water ◽  
Pump System ◽  
Ground Source Heat Pumps ◽  
Self Sufficiency ◽  
Energy Sharing

Due to increased grid problems caused by renewable energy systems being used to realize zero energy buildings and communities, the importance of energy sharing and self-sufficiency of renewable energy also increased. In this study, the energy performance of an energy-sharing community was investigated to improve its energy efficiency and renewable energy self-sufficiency. For a case study, a smart village was selected via detailed simulation. In this study, the thermal energy for cooling, heating, and domestic hot water was produced by ground source heat pumps, which were integrated with thermal energy storage (TES) with solar energy systems. We observed that the ST system integrated with TES showed higher self-sufficiency with grid interaction than the PV and PVT systems. This was due to the heat pump system being connected to thermal energy storage, which was operated as an energy storage system. Consequently, we also found that the ST system had a lower operating energy, CO2 emissions, and operating costs compared with the PV and PVT systems.

Design and Optimization of Integrated Distributed Energy Systems for Off-grid Buildings

2021 ◽  
pp. 1-27
Author(s):  
Jian Zhang ◽  
Heejin Cho ◽  
Pedro Mago
Keyword(s):  
Energy Storage ◽  
Optimal Design ◽  
Power Systems ◽  
Thermal Energy ◽  
Waste Heat ◽  
Carbon Dioxide Emission ◽  
Energy Systems ◽  
Solar Thermal ◽  
Solar Thermal Energy ◽  
Distributed Energy

Abstract Off-grid concepts for homes and buildings have been a fast-growing trend worldwide in the last few years because of the rapidly dropping cost of renewable energy systems and their self-sufficient nature. Off-grid homes/buildings can be enabled with various energy generation and storage technologies, however, design optimization and integration issues have not been explored sufficiently. This paper applies a multi-objective genetic algorithm (MOGA) optimization to obtain an optimal design of integrated distributed energy systems for off-grid homes in various climate regions. Distributed energy systems consisting of renewable and non-renewable power generation technologies with energy storage are employed to enable off-grid homes/buildings and meet required building electricity demands. In this study, the building types under investigation are residential homes. Multiple distributed energy resources are considered such as combined heat and power systems (CHP), solar photovoltaic (PV), solar thermal collector (STC), wind turbine (WT), as well as battery energy storage (BES) and thermal energy storage (TES). Among those technologies, CHP, PV, and WT are used to generate electricity, which satisfies the building's electric load, including electricity consumed for space heating and cooling. Solar thermal energy and waste heat recovered from CHP are used to partly supply the building's thermal load. Excess electricity and thermal energy can be stored in the BES and TES for later use. The MOGA is applied to determine the best combination of DERs and each component's size to reduce the system cost and carbon dioxide emission for different locations. Results show that the proposed optimization method can be effectively and widely applied to design integrated distributed energy systems for off-grid homes resulting in an optimal design and operation based on a trade-off between economic and environmental performance.

scholarly journals Development and Analysis of a Multi-Node Dynamic Model for the Simulation of Stratified Thermal Energy Storage

Energies ◽  
2019 ◽  
Vol 12 (22) ◽  
pp. 4275 ◽  
Author(s):  
Nora Cadau ◽  
Andrea De Lorenzi ◽  
Agostino Gambarotta ◽  
Mirko Morini ◽  
Michele Rossi
Keyword(s):  
Energy Storage ◽  
Thermal Energy ◽  
Thermal Energy Storage ◽  
Supply And Demand ◽  
District Heating ◽  
Energy Systems ◽  
High Flow ◽  
Market Penetration ◽  
Flow Rates ◽  
Smart Energy Systems

To overcome non-programmability issues that limit the market penetration of renewable energies, the use of thermal energy storage has become more and more significant in several applications where there is a need for decoupling between energy supply and demand. The aim of this paper is to present a multi-node physics-based model for the simulation of stratified thermal energy storage, which allows the required level of detail in temperature vertical distribution to be varied simply by choosing the number of nodes and their relative dimensions. Thanks to the chosen causality structure, this model can be implemented into a library of components for the dynamic simulation of smart energy systems. Hence, unlike most of the solutions proposed in the literature, thermal energy storage can be considered not only as a stand-alone component, but also as an important part of a more complex system. Moreover, the model behavior has been analyzed with reference to the experimental results from the literature. The results make it possible to conclude that the model is able to accurately predict the temperature distribution within a stratified storage tank typically used in a district heating network with limitations when dealing with small storage volumes and high flow rates.

New bounds for the thermal energy storage process with stationary input

1982 ◽  
Vol 19 (04) ◽  
pp. 894-899 ◽  
Author(s):  
J. Haslett
Keyword(s):  
Energy Storage ◽  
Thermal Energy ◽  
Thermal Energy Storage ◽  
Energy Systems ◽  
Solar Thermal ◽  
Solar Thermal Energy ◽  
Storage Process

The process {Xn }, defined by Xn + 1 = max{Yn + 1 + αßX n, ßX n}, with αand ß in [0, 1) and {Yn } stationary, arises in studies of solar thermal energy systems. Bounds for the stationary mean EX are given, which are more general and in some cases tighter, than those previously available.

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