Comprehensive overview of how to ensure adequate power resources in a decarbonized world powered by renewable energy
Power System Resource Adequacy for Clean Energy explores and addresses the challenges and solutions associated with ensuring adequate power resources as power grids transition toward a decarbonized and renewable energy future, discussing assumptions, methodologies, modeling frameworks, detailed inputs, and result analysis. The book illustrates the methodology, approaches, and nuances of resource adequacy studies to determine seasonal planning reserve margins as well as resource peak capacity contributions to meet peak demand. The saturation effects of renewable resources and energy-limited resources are highlighted, and importance of resource adequacy verification is emphasized.
Written by an expert with a wealth of real-world experience in the field, Power System Resource Adequacy for Clean Energy includes information on:
The impact of climate change, seasonal planning reserve margins, multi-metric criteria for resource adequacy Wind and solar generation profiles, energy storage and thermal generation modeling, and the flexibility of hydroelectric generation Operating and balancing reserve, effective load carrying capability, saturation effects, and marginal and average ELCC Resource adequacy verification, a critical concept in ensuring that the peak demands are truly met by built resources
Power System Resource Adequacy for Clean Energy is an excellent reference on the subject for power system planners, federal and state energy policy makers and commissioners, and professors, researchers, and graduate students in Electrical & Computer Engineering.
About the Author ix Preface xi 1 Introduction 1 1.1 Demand Forecast 2 1.2 Reliability Metrics 3 1.3 Resource Adequacy Evaluation Method 3 1.4 Regional and Local Resource Adequacy Coordination 4 1.5 Resource Adequacy Verification 5 References 6 2 Resource Adequacy Study Overview 9 2.1 Resource Adequacy Metrics 18 2.1.1 Loss-of-load Probability 19 2.1.2 Loss-of-load Hours 19 2.1.3 Loss-of-load Expectation 19 2.1.4 Expected Unserved Energy 19 2.1.5 Value at Risk 20 2.1.6 Multi-metric 21 2.1.7 Reliability Metric Threshold 22 2.2 Regulatory Policy and Impact 23 References 25 3 Load Forecast 27 3.1 Methodology 28 3.1.1 Regression Methods 28 3.1.2 Time-series Methods 30 3.1.3 Machine Learning Model 31 3.1.3.1 Feedforward Network 32 3.1.3.2 Recurrent Neural Network 33 3.2 Input Assumptions 34 3.3 Climate Change 35 3.4 Demand-side Resources Impacts 38 3.5 Stochastic Scenarios 39 References 40 4 Planning Reserve Margin 43 4.1 Operating Reserves 44 4.1.1 Contingency Reserve 45 4.1.2 Regulation Reserve 47 4.2 Balancing Reserve 50 4.2.1 Three-standard-deviation Rule 51 4.2.2 Stochastic Economic Dispatch 52 4.3 Reliability Target 53 4.4 Seasonal PRM 54 References 63 5 Resource Adequacy Modeling 65 5.1 Wind Power Generation 65 5.1.1 Wind Turbine Aerodynamics 65 5.1.2 Drivetrain Model 68 5.1.3 Pitch Control Model 69 5.1.4 Power Curve 69 5.1.5 Wind Velocity 73 5.1.5.1 Meteorological Model 73 5.1.5.2 Statistical Model 77 5.2 Solar Photovoltaic Power Generation 82 5.2.1 PV Cell Simplified Model 82 5.2.2 PV Cell Practical Model 84 5.2.3 Cell Temperature 86 5.2.4 PV Cell Power Generation 87 5.2.5 PV Efficiency 87 5.2.6 Solar Irradiation and Ambient Temperature 87 5.3 Energy Storage 91 5.3.1 Battery Storage 91 5.3.2 Pumped Hydroelectric Energy Storage 92 5.3.3 Compressed Air Energy Storage 93 5.3.3.1 Thermodynamics of CAES 94 5.3.3.2 CAES Model 96 5.4 Hydroelectric Generation 99 5.4.1 Conventional Hydroelectric Power Plants 100 5.4.2 Run-of-the-river Hydroelectric Plant 101 5.4.3 River Discharge 101 5.4.4 Numerical Examples 102 5.4.4.1 Run-of-the-River Hydroelectric Power Plant 104 5.4.4.2 Conventional Hydroelectric Power Plant 104 5.5 Thermal Generation 104 References 109 6 Resource Adequacy Methodology 113 6.1 Reliability Metric Evaluation 113 6.1.1 Thermal and Hydro Unit Dispatch 114 6.1.2 Hydro Unit Flexibility 117 6.1.3 Energy Storage Dispatch 118 6.1.4 Demand Response Logic 119 6.2 PRM Calculation 120 6.3 Effective Load Carrying Capability 120 6.3.1 Seasonal ELCC 121 6.3.2 Non-dispatchable Resource ELCC Saturation 121 6.3.3 Energy-Limited Resource ELCC Saturation 124 6.3.4 Hybrid Resource ELCC Saturation 127 References 135 7 Regional and Local Resource Adequacy Coordination 137 7.1 Regional Resource Adequacy 137 7.1.1 Load Diversity Benefit 138 7.1.2 Renewable Power Generation Diversity Benefit 139 7.2 Regional Resource Sharing Program 141 7.3 Market Purchases 141 References 142 8 Resource Adequacy Verification 143 8.1 Long-Term Capacity Expansion Model 144 8.1.1 Wind and Solar Generation 146 8.1.2 Resource Cost Structure 147 8.2 Wind and Solar Resource Grouping 148 8.3 Resource Adequacy Verification 149 8.4 Resource Adequacy Adjustment 150 8.5 Numerical Case Study 150 8.5.1 Generic Resource Technology 151 8.5.2 Generic Resource Cost 151 8.5.3 Generic Resource Marginal and Average ELCC 152 8.5.4 Levelized Peak Capacity Cost 154 8.5.5 Resource Adequacy and Long-term Capacity Expansion Iteration 159 References 163 9 Conclusions 165 Index 167
Renchang Dai, PhD, is a Principal Engineer and Project Manager with Puget Sound Energy. He manages resource adequacy analysis projects and conducts long-term transmission and resource planning.