scholarly journals Smart Building: Decision Making Architecture for Thermal Energy Management

2020 ◽  
Author(s):  
Oscar Hernández Uribe ◽  
Juan Pablo San Martin ◽  
María C Garcia-Alegre ◽  
Matilde Santos ◽  
Domingo Guinea
Keyword(s):  
Decision Making ◽  
Energy Management ◽  
Thermal Energy ◽  
Smart Building

scholarly journals Smart Building: Decision Making Architecture for Thermal Energy Management

Sensors ◽  
2015 ◽  
Vol 15 (11) ◽  
pp. 27543-27568 ◽  
Author(s):  
Oscar Uribe ◽  
Juan Martin ◽  
María Garcia-Alegre ◽  
Matilde Santos ◽  
Domingo Guinea
Keyword(s):  
Decision Making ◽  
Energy Management ◽  
Thermal Energy ◽  
Smart Building

scholarly journals A Review on Thermal Energy Modelling for Optimal Microgrids Management

Thermo ◽  
2021 ◽  
Vol 1 (1) ◽  
pp. 63-76
Author(s):  
Mengxuan Yan ◽  
Dongxiao Wang ◽  
Chun Sing Lai ◽  
Loi Lei Lai
Keyword(s):  
Energy Management ◽  
Thermal Energy ◽  
Critical Role ◽  
Distribution Networks ◽  
Energy Resources ◽  
Future Research ◽  
Renewable Energy Resources ◽  
Energy Modelling ◽  
Microgrid Energy Management ◽  
Combined Cooling

Microgrids have become increasingly popular in recent years due to technological improvements, growing recognition of their benefits, and diminishing costs. By clustering distributed energy resources, microgrids can effectively integrate renewable energy resources in distribution networks and satisfy end-user demands, thus playing a critical role in transforming the existing power grid to a future smart grid. There are many existing research and review works on microgrids. However, the thermal energy modelling in optimal microgrid management is seldom discussed in the current literature. To address this research gap, this paper presents a detailed review on the thermal energy modelling application on the optimal energy management for microgrids. This review firstly presents microgrid characteristics. Afterwards, the existing thermal energy modeling utilized in microgrids will be discussed, including the application of a combined cooling, heating and power (CCHP) and thermal comfort model to form virtual energy storage systems. Current trial programs of thermal energy modelling for microgrid energy management are analyzed and some challenges and future research directions are discussed at the end. This paper serves as a comprehensive review to the most up-to-date thermal energy modelling applications on microgrid energy management.

Hierarchically Organized Biomimetic Architectured Silk Fibroin–Ceramic-Based Anisotropic Hybrid Aerogels for Thermal Energy Management

2021 ◽  
Vol 22 (4) ◽  
pp. 1739-1751
Author(s):  
Hajar Maleki ◽  
Thomas Fischer ◽  
Christoph Bohr ◽  
Jaqueline Auer ◽  
Sanjay Mathur ◽  
...  
Keyword(s):  
Energy Management ◽  
Silk Fibroin ◽  
Thermal Energy ◽  
Hybrid Aerogels

Joint Maintenance and Energy Management of Sustainable Manufacturing Systems

2015 ◽  
Author(s):  
Xufeng Yao ◽  
Zeyi Sun ◽  
Lin Li ◽  
Hua Shao
Keyword(s):  
Decision Making ◽  
Energy Management ◽  
Energy Cost ◽  
Manufacturing Systems ◽  
Sustainable Manufacturing ◽  
Manufacturing Plants ◽  
Machine Reliability ◽  
Automotive Assembly ◽  
Maintenance Decision ◽  
Joint Maintenance

The expenses associated with maintenance activities and energy consumption account for a large portion of the total operation cost in manufacturing plants. Therefore, effective methods that can be used for smart maintenance decision-making and energy management to reduce the costs of these two sections and improve the competitiveness of manufacturing enterprise are of high interests to industry. Many efforts focusing on maintenance decision-making and energy management have been dedicated. However, most of the existing research focusing on these two topics has been conducted separately, very little work has been done from a joint perspective that considers the benefits from both manufacturing machine reliability improvement and energy cost reduction. In this paper, a joint maintenance and energy management method is proposed to identify the maintenance actions considering energy cost as well as other equipment health metrics. A numerical case based on a section of an automotive assembly line is used to illustrate the potential benefits of the proposed approach.

scholarly journals Modeling and Optimization of Smart Building Energy Management System Considering Both Electrical and Thermal Load

Energies ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 574
Author(s):  
Muhammad Hilal Khan ◽  
Azzam Ul Asar ◽  
Nasim Ullah ◽  
Fahad R. Albogamy ◽  
Muhammad Kashif Rafique
Keyword(s):  
Energy Management ◽  
Management System ◽  
Energy Demand ◽  
Storage System ◽  
Building Energy ◽  
Energy Management System ◽  
Smart Building ◽  
Building Energy Management ◽  
Real Coded Genetic Algorithm ◽  
The Impact

Energy consumption in buildings is expected to increase by 40% over the next 20 years. Electricity remains the largest source of energy used by buildings, and the demand for it is growing. Building energy improvement strategies is needed to mitigate the impact of growing energy demand. Introducing a smart energy management system in buildings is an ambitious yet increasingly achievable goal that is gaining momentum across geographic regions and corporate markets in the world due to its potential in saving energy costs consumed by the buildings. This paper presents a Smart Building Energy Management system (SBEMS), which is connected to a bidirectional power network. The smart building has both thermal and electrical power loops. Renewable energy from wind and photo-voltaic, battery storage system, auxiliary boiler, a fuel cell-based combined heat and power system, heat sharing from neighboring buildings, and heat storage tank are among the main components of the smart building. A constraint optimization model has been developed for the proposed SBEMS and the state-of-the-art real coded genetic algorithm is used to solve the optimization problem. The main characteristics of the proposed SBEMS are emphasized through eight simulation cases, taking into account the various configurations of the smart building components. In addition, EV charging is also scheduled and the outcomes are compared to the unscheduled mode of charging which shows that scheduling of Electric Vehicle charging further enhances the cost-effectiveness of smart building operation.

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