- ホーム
- > 洋書
- > ドイツ書
- > Mathematics, Sciences & Technology
- > Technology
- > heat engineering, energy engineering, nuclear engineering
Full Description
The book covers practical applications and experimental results of integrating renewable energy technologies, energy storage facilities, and intelligent control and operation techniques into building energy systems. It introduces practical approaches to improving the energy systems of buildings in order to reduce energy consumption and cost. Renewable Energy for Buildings is suitable for retrofit engineers, energy engineers, and professionals, as well as researchers and developers in electrical engineering, architectural engineering, and mechanical engineering. Moreover, it can be used by undergraduate and graduate students to become familiar with the most recent developments in building energy systems.
Examines the most recent developments in building energy systems;
Looks at practical applications and theoretical aspects;
Includes case studies.
Contents
Integrating Solar Panels, Solar Thermal Systems and Small-Scale Roof-Mounted Wind Turbines in Buildings.- Introduction and Literature Review of Bioenergy and Geothermal Systems in Buildings.- Introduction and Literature Review of Building Components With Integrated Renewable Energy Generation Systems.- Risk Modeling in Operation of Renewable Energy Generation Systems.- Challenges and Advantages of Bidirectional Energy Transfer Between Building Energy System and Main Grid.- The Role of Energy Storage Systems in Mitigating the Intermittency of Renewable Energy Resources in Buildings.- Introduction and Literature Review of Building Components With Passive Thermal Energy Storage Systems.- Optimal Design and Financial Analysis of Implementing Thermal and Battery Energy Storage Systems in Buildings.- The Role of Energy Storage Capacity of Electric Vehicles (EVs) in Increasing the Flexibility of Building Energy Management Systems.- Optimal Scheduling and Operation of Building Energy Generation and Storage Systems.- Introduction and Literature Review of Home Energy Management Systems.- Optimal Operation of Thermostatic Loads Based on Predicting Residents' Preferences.- Application of Machine Learning for the Intelligent Operation of Building Energy System.- Residential Load Pattern Recognition and Prediction Based on User's Activity Pattern.- Intelligent Data-driven Techniques in Optimizing the Energy Consumption in Buildings.
