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Table of Contents
Intro; Contents; Sustainable Energy: What, Why, and How?; 1 What?; 2 Why?; 3 How?; References; A Review of Wind Energy Resource Assessment in the Urban Environment; 1 Introduction; 2 Wind Speed in the Built Environment; 2.1 Urban Wind Shear; 2.2 Wind Speed Profile; 3 Wind Energy Converters for the Built Environment; 3.1 Examples of Urban Wind Turbines; 3.2 Site Specific Wind Turbine Performance; 4 Wind Resource in the Built Environment; 4.1 Measurement of Wind Speed in the Field; 4.2 Computational Assessment of Wind Resources; 4.3 Most Used Turbulence Models for Urban Wind Flow Assessment
4.4 Urban Wind Assessment Using CFD5 Conclusion; References; Advances in Wind Power Forecasting; 1 Introduction; 2 Background; 3 Time Scales; 4 Model Assessment Methods; 5 Wind Forecasting Methods; 5.1 Persistence Method; 5.2 Physical Models; 5.3 Statistical Methods; 5.4 Machine Learning Methods; 5.5 Hybrid Methods; 6 Conclusion; References; Lean Energy Buildings: Applications of Machine Learning, Optimal Central Chilled-Water Systems, and Hybrid Solar-Ground Source Heat Pump Systems; 1 Introduction: Overview and Scope; 2 Energy Informatics and Data Classes
2.1 Data Measurement and Acquisition2.2 Data Organization, Warehousing, and Visualization; 2.3 Data Analytics; 2.4 Actionable Information and Control; 3 Examples of Advanced Data Analytics for Improved Control of Central HVAC Systems in Buildings; 3.1 Scheduling and Demand Profiles; 3.2 Outdoor Air Control; 3.3 Variable Flow Fan/Pump Control; 4 Optimal Unitary HVAC Systems: Ground Source Heat Pumps with Solar Hybrid Option; 4.1 Overview of Ground-Source Heat Pump Systems; 4.2 The Hybrid Ground-Source Heat Pump System Concept; 4.3 Hybrid Solar Ground-Source Heat Pump Systems; 5 Chapter Summary
4.4 Urban Wind Assessment Using CFD5 Conclusion; References; Advances in Wind Power Forecasting; 1 Introduction; 2 Background; 3 Time Scales; 4 Model Assessment Methods; 5 Wind Forecasting Methods; 5.1 Persistence Method; 5.2 Physical Models; 5.3 Statistical Methods; 5.4 Machine Learning Methods; 5.5 Hybrid Methods; 6 Conclusion; References; Lean Energy Buildings: Applications of Machine Learning, Optimal Central Chilled-Water Systems, and Hybrid Solar-Ground Source Heat Pump Systems; 1 Introduction: Overview and Scope; 2 Energy Informatics and Data Classes
2.1 Data Measurement and Acquisition2.2 Data Organization, Warehousing, and Visualization; 2.3 Data Analytics; 2.4 Actionable Information and Control; 3 Examples of Advanced Data Analytics for Improved Control of Central HVAC Systems in Buildings; 3.1 Scheduling and Demand Profiles; 3.2 Outdoor Air Control; 3.3 Variable Flow Fan/Pump Control; 4 Optimal Unitary HVAC Systems: Ground Source Heat Pumps with Solar Hybrid Option; 4.1 Overview of Ground-Source Heat Pump Systems; 4.2 The Hybrid Ground-Source Heat Pump System Concept; 4.3 Hybrid Solar Ground-Source Heat Pump Systems; 5 Chapter Summary