Renewable Energy Integration for Bulk Power Systems: ERCOT and the Texas Interconnection
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cham
Springer International Publishing AG
2023
|
| Ausgabe: | 1st ed |
| Schriftenreihe: | Power Electronics and Power Systems Series
|
| Online-Zugang: | DE-2070s |
| Beschreibung: | Description based on publisher supplied metadata and other sources |
| Beschreibung: | 1 Online-Ressource (293 Seiten) |
| ISBN: | 9783031286391 |
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| 245 | 1 | 0 | |a Renewable Energy Integration for Bulk Power Systems |b ERCOT and the Texas Interconnection |
| 250 | |a 1st ed | ||
| 264 | 1 | |a Cham |b Springer International Publishing AG |c 2023 | |
| 264 | 4 | |c ©2023 | |
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| 490 | 0 | |a Power Electronics and Power Systems Series | |
| 500 | |a Description based on publisher supplied metadata and other sources | ||
| 505 | 8 | |a Intro -- Preface -- Contents -- Chapter 1: Renewable Integration at ERCOT -- 1 Overview -- 1.1 Texas Power System -- 1.2 Wind Generation Development in Texas -- 1.3 Solar Generation Development in Texas -- 1.4 Interconnection Requirements for Generation Resources -- 2 Transmission Development and Capacity Adequacy -- 2.1 Transmission Access -- 2.2 Transmission Reinforcement -- 2.3 Operational Challenges with High Inverter-Based Resource Penetration -- 2.4 Capacity Adequacy and Wind Generation Resources -- 3 ERCOT Energy and Ancillary Services Market -- 3.1 Ancillary Services -- 4 Reliability and Security of Grid Operations -- 4.1 Requirement for Primary Frequency Response -- 4.2 ERCOT Frequency Performance -- 4.3 System Inertia Trend -- 4.4 Renewable Generation Forecasting -- 4.5 Operations Analysis and Studies -- 4.5.1 Day-Ahead Analysis and Studies -- 4.5.2 Real-Time Analysis and Studies -- 4.5.3 Situational Awareness Tools -- 4.5.4 Challenges for the Nearest Future -- 5 Conclusions -- References -- Chapter 2: Overview of Market Operation at ERCOT -- 1 Overview -- 1.1 Network Modeling -- 1.2 Day-Ahead Operations -- 1.3 Adjustment Period Operations -- 1.4 Real-Time Operations -- 2 Day-Ahead Market (DAM) -- 2.1 DAM Overview -- 2.2 ERCOT and QSE Activities in DAM -- 2.2.1 Ancillary Service Plan Posted in DAM -- 2.2.2 QSE Activities -- 2.2.2.1 Report Availability of Must-Run and Black Start Resources -- 2.2.2.2 Submit Bids for PTP Obligations -- 2.2.2.3 Submit Three-Part Supply Offers -- 2.2.2.4 Submit Energy Bids and Energy-Only Offers -- 2.2.2.5 Submit Self-Arranged Ancillary Service -- 2.2.2.6 Submit Ancillary Service Offers -- 2.2.2.7 Update and Submit Current Operating Plan -- 2.3 DAM Engine -- 3 RUC -- 3.1 RUC Process Overview -- 3.2 Input to RUC Process -- 3.2.1 Current Operating Plan (COP) -- 3.2.2 Network Operations Model | |
| 505 | 8 | |a 3.2.3 Generic Transmission Constraints -- 3.2.4 Load Forecast -- 3.2.5 Offers and Proxy Energy Offer -- 3.3 RUC Process -- 3.3.1 RUC Problem Formulation and Solution Algorithm -- 3.4 Energy Offer Curve for RUC-Committed Resource -- 4 Real-Time SCED -- 4.1 SCED: Energy Dispatch -- 4.1.1 Information Flows in SCED -- 4.1.2 Real-Time Network Security Analysis -- 4.1.3 Resource Limit Calculator (RLC) -- 4.1.4 How SCED Functions -- 4.1.4.1 The Texas Two-Step -- 4.1.4.2 SCED Schedule and Output -- 4.2 Load Frequency Control (LFC) -- 5 Conclusions -- References -- Chapter 3: Market Designs to Integrate Renewable Resources -- 1 Overview -- 2 ERCOT Nodal Market -- 3 Short-Term Wind/PVGR Generation Forecasting and Current Operating Plan (COP) -- 4 IRR Scheduling in DAM, RUC, and SCED -- 4.1 IRR Scheduling in DAM -- 4.2 IRR Generation Scheduling in RUC -- 4.3 IRR Generation Scheduling in Real-Time SCED -- 4.4 Base Point Deviation Charge for IRR -- 4.5 Effect on Management of Congestion -- 4.6 Effect on Market Prices -- 5 Management of Generic Transmission Constraints (GTCs) -- 5.1 Management of GTC Limits -- 5.2 Non-to-Exceedance (NTE) Method -- 5.3 Implementation of NTE Concept -- 6 Incorporation of 5-Minute Wind/Solar Ramp into SCED -- 6.1 Generation to Be Dispatched (GTBD) -- 6.2 Forecast of 5-Minute Solar Ramp -- 7 Conclusions -- Chapter 4: Ancillary Services (AS) at ERCOT -- 1 Overview -- 1.1 Responsive Reserve Service (RRS) -- 1.2 Regulation Reserve Service -- 1.3 Non-spinning Reserve Service -- 2 Regulation Services -- 2.1 Short-Term Wind Generation Forecasting -- 2.2 Method to Determine Regulation Services Requirement -- 2.2.1 An ERCOT Dispatch Model for Calculating Regulation Requirement -- 2.2.2 Regulation Service Requirement -- 2.2.3 Including Effect of Wind Generation -- 2.2.4 Adequacy of Regulation Reserves | |
| 505 | 8 | |a 2.3 Procedures to Determine Regulation Service Requirement -- 2.3.1 Regulation Service Requirements -- 2.3.2 Evaluation of Exhaustion Rate -- 2.3.3 Performance Validation -- 3 Responsive Reserve Requirement -- 3.1 Quantification of PFR and FFR Requirement for Inertias -- 3.2 RRS Requirement -- 4 Non-spinning Reserve -- 4.1 Background -- 4.2 Net Load Forecast Error (NLFE) Analysis -- 4.3 Net Load Ramp-Up -- 4.4 Adjustment to Non-Spin Need by Considering Forced Outage -- 4.5 Procedures to Determine Non-Spin Need -- 5 Summary -- References -- Chapter 5: Design of New Primary Frequency Control Market for Hosting Frequency Response Reserve Offers from Both Generators a... -- 1 Introduction of Frequency Control -- 2 Impact of Renewable Resource over Inertia and Primary Frequency Control -- 3 Co-optimization of Energy and FRR in Day-Ahead Market -- 3.1 Day-Ahead Market Co-optimization Model -- 3.2 Solution of Day-Ahead Market Co-optimization -- 3.3 Case Studies -- 4 Stochastic Formulations of Co-optimization of Energy and FRR in Day-Ahead Market -- 4.1 Energy, PFR, and Inertia Scheduling Without Uncertainties -- 4.2 Energy, PFR, and Inertia Scheduling Under Uncertainties -- 4.2.1 Scenario Generation and Reduction -- 4.2.2 Interaction Between Day-Ahead Scheduling and Hour-Ahead Operation -- 4.2.3 An ERCOT Case Study -- 4.2.3.1 Deterministic Scheduling Solution -- 4.2.3.2 Stochastic Scheduling Solution -- 4.2.3.3 Comparison Between Deterministic and Stochastic Scheduling Solutions -- 5 Conclusions -- References -- Chapter 6: New Ancillary Service Market for ERCOT: Fast Frequency Response (FFR) -- 1 Introduction -- 2 Existing Ancillary Service Market at ERCOT -- 2.1 Regulation Service -- 2.2 Responsive Reserve Service (RRS) -- 2.3 Non-spin Reserve Service (NSRS) -- 3 Inertia Trend and Primary Frequency Control at ERCOT -- 3.1 Inertia Trend at ERCOT. | |
| 505 | 8 | |a 3.2 Overview of Frequency Control Coordination at ERCOT -- 3.3 RRS at ERCOT Before Re-design of AS Market -- 4 New Ancillary Service Market -- 5 Fast Frequency Response (FFR) -- 5.1 Qualifications of FFR and Performance Evaluations -- 5.2 Telemetry Data Requirement for Deployment and Recall of FFR -- 6 Maximum Amount of FFR Allowed -- 7 Benefits of FFR -- 7.1 Impact of FFR over Critical Inertia -- 7.2 RRS Cost Saving with FFR Resources -- 8 Conclusions -- References -- Chapter 7: System Inertia Trend and Critical Inertia -- 1 Basics of Synchronous Inertia -- 2 Inertia at ERCOT -- 3 Historical Synchronous Inertia Trends -- 4 Determining Critical Inertia -- 5 ERCOT Tools to Monitor and Forecast System Inertia -- 6 Impact of Parameter Changes on Critical Inertia -- 6.1 ''Faster'' Frequency Response -- 6.2 ''Earlier'' Frequency Response -- 6.3 Lower UFLS Trigger -- 6.4 Reduction of Largest Possible Loss of Generation -- 7 International Review of Inertia-Related Challenges and Mitigation Measures -- 8 Summary of Potential Mitigation Measures to Lower Critical Inertia or Support Minimum Inertia Level -- 9 Conclusions -- References -- Chapter 8: Multiple-Period Reactive Power Coordination for Renewable Integration -- 1 Introduction -- 2 Literature Review -- 3 Renewable Integration and New Transmission Operators -- 4 Reactive Power Coordination (RPC) Tool -- 4.1 Architecture of RPC -- 4.2 Objective Function of RPC -- 4.3 Constraints of RPC -- 4.4 Mathematic Formulations of RPC -- 4.5 Solution Methodology -- 5 Special Considerations -- 5.1 Sensitivity of Reactive Power for a Regulating Bus -- 5.2 Reactive Device's Temporal Constraint -- 5.3 Handling Special Capacitor Banks -- 6 Case Studies -- 6.1 ERCOT Network Model -- 6.2 Verification of Temporal Constraints -- 6.2.1 Initial State of Capacitor Is OFF. | |
| 505 | 8 | |a 6.2.2 Sequence Constraints Between Master and Slave Capacitors -- 6.3 Simulation Results -- 7 Conclusions -- References -- Chapter 9: Renewable Forecast -- 1 Introduction -- 2 Wind Forecasting System -- 2.1 Wind Forecasting System Overview -- 2.2 Data Flow of Wind Forecasting System -- 2.3 Input Data for Wind Forecasting System -- 2.4 Design Approach of Wind Forecasting System -- 3 Solar Forecasting System and Forecast Errors -- 3.1 Solar Forecasting System -- 3.1.1 NWP Data -- 3.1.2 Machine Learning Algorithms Used by Solar Forecasting System -- 3.1.3 Satellite Cloud Tracking Algorithms -- 3.1.4 Plant Output Models -- 3.1.5 Ensemble Optimization Algorithm -- 3.1.6 Solar Forecast Delivery Mechanism -- 3.2 Solar Forecast Error Analysis -- 3.2.1 Source of Data -- 3.2.2 Probability Distribution Function of Solar Forecast Errors -- 3.2.3 Temporal Correlation of SFE -- 4 Summary and Conclusions -- References -- Chapter 10: Ensemble Machine Learning-Based Wind Forecasting to Combine NWP Output with Data from Weather Stations -- 1 Introduction -- 2 Numerical Weather Prediction -- 3 West Texas Mesonet (WTM) -- 3.1 Value of WTM Data: An Example -- 4 Machine Learning-Based Ensemble Method -- 5 Experimental Results -- 5.1 Performance of Three Machine Learning Algorithms -- 5.2 Performance of Base Algorithms for Large Wind Ramp -- 5.3 Performance of Ensemble Method -- 5.4 Robustness of Proposed Method -- 6 Conclusions -- References -- Index | |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |a Du, Pengwei |t Renewable Energy Integration for Bulk Power Systems |d Cham : Springer International Publishing AG,c2023 |z 9783031286384 |
| 912 | |a ZDB-30-PQE | ||
| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-035215559 | |
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Datensatz im Suchindex
| _version_ | 1810687471421227008 |
|---|---|
| adam_text | |
| any_adam_object | |
| author | Du, Pengwei |
| author_facet | Du, Pengwei |
| author_role | aut |
| author_sort | Du, Pengwei |
| author_variant | p d pd |
| building | Verbundindex |
| bvnumber | BV049876109 |
| collection | ZDB-30-PQE |
| contents | Intro -- Preface -- Contents -- Chapter 1: Renewable Integration at ERCOT -- 1 Overview -- 1.1 Texas Power System -- 1.2 Wind Generation Development in Texas -- 1.3 Solar Generation Development in Texas -- 1.4 Interconnection Requirements for Generation Resources -- 2 Transmission Development and Capacity Adequacy -- 2.1 Transmission Access -- 2.2 Transmission Reinforcement -- 2.3 Operational Challenges with High Inverter-Based Resource Penetration -- 2.4 Capacity Adequacy and Wind Generation Resources -- 3 ERCOT Energy and Ancillary Services Market -- 3.1 Ancillary Services -- 4 Reliability and Security of Grid Operations -- 4.1 Requirement for Primary Frequency Response -- 4.2 ERCOT Frequency Performance -- 4.3 System Inertia Trend -- 4.4 Renewable Generation Forecasting -- 4.5 Operations Analysis and Studies -- 4.5.1 Day-Ahead Analysis and Studies -- 4.5.2 Real-Time Analysis and Studies -- 4.5.3 Situational Awareness Tools -- 4.5.4 Challenges for the Nearest Future -- 5 Conclusions -- References -- Chapter 2: Overview of Market Operation at ERCOT -- 1 Overview -- 1.1 Network Modeling -- 1.2 Day-Ahead Operations -- 1.3 Adjustment Period Operations -- 1.4 Real-Time Operations -- 2 Day-Ahead Market (DAM) -- 2.1 DAM Overview -- 2.2 ERCOT and QSE Activities in DAM -- 2.2.1 Ancillary Service Plan Posted in DAM -- 2.2.2 QSE Activities -- 2.2.2.1 Report Availability of Must-Run and Black Start Resources -- 2.2.2.2 Submit Bids for PTP Obligations -- 2.2.2.3 Submit Three-Part Supply Offers -- 2.2.2.4 Submit Energy Bids and Energy-Only Offers -- 2.2.2.5 Submit Self-Arranged Ancillary Service -- 2.2.2.6 Submit Ancillary Service Offers -- 2.2.2.7 Update and Submit Current Operating Plan -- 2.3 DAM Engine -- 3 RUC -- 3.1 RUC Process Overview -- 3.2 Input to RUC Process -- 3.2.1 Current Operating Plan (COP) -- 3.2.2 Network Operations Model 3.2.3 Generic Transmission Constraints -- 3.2.4 Load Forecast -- 3.2.5 Offers and Proxy Energy Offer -- 3.3 RUC Process -- 3.3.1 RUC Problem Formulation and Solution Algorithm -- 3.4 Energy Offer Curve for RUC-Committed Resource -- 4 Real-Time SCED -- 4.1 SCED: Energy Dispatch -- 4.1.1 Information Flows in SCED -- 4.1.2 Real-Time Network Security Analysis -- 4.1.3 Resource Limit Calculator (RLC) -- 4.1.4 How SCED Functions -- 4.1.4.1 The Texas Two-Step -- 4.1.4.2 SCED Schedule and Output -- 4.2 Load Frequency Control (LFC) -- 5 Conclusions -- References -- Chapter 3: Market Designs to Integrate Renewable Resources -- 1 Overview -- 2 ERCOT Nodal Market -- 3 Short-Term Wind/PVGR Generation Forecasting and Current Operating Plan (COP) -- 4 IRR Scheduling in DAM, RUC, and SCED -- 4.1 IRR Scheduling in DAM -- 4.2 IRR Generation Scheduling in RUC -- 4.3 IRR Generation Scheduling in Real-Time SCED -- 4.4 Base Point Deviation Charge for IRR -- 4.5 Effect on Management of Congestion -- 4.6 Effect on Market Prices -- 5 Management of Generic Transmission Constraints (GTCs) -- 5.1 Management of GTC Limits -- 5.2 Non-to-Exceedance (NTE) Method -- 5.3 Implementation of NTE Concept -- 6 Incorporation of 5-Minute Wind/Solar Ramp into SCED -- 6.1 Generation to Be Dispatched (GTBD) -- 6.2 Forecast of 5-Minute Solar Ramp -- 7 Conclusions -- Chapter 4: Ancillary Services (AS) at ERCOT -- 1 Overview -- 1.1 Responsive Reserve Service (RRS) -- 1.2 Regulation Reserve Service -- 1.3 Non-spinning Reserve Service -- 2 Regulation Services -- 2.1 Short-Term Wind Generation Forecasting -- 2.2 Method to Determine Regulation Services Requirement -- 2.2.1 An ERCOT Dispatch Model for Calculating Regulation Requirement -- 2.2.2 Regulation Service Requirement -- 2.2.3 Including Effect of Wind Generation -- 2.2.4 Adequacy of Regulation Reserves 2.3 Procedures to Determine Regulation Service Requirement -- 2.3.1 Regulation Service Requirements -- 2.3.2 Evaluation of Exhaustion Rate -- 2.3.3 Performance Validation -- 3 Responsive Reserve Requirement -- 3.1 Quantification of PFR and FFR Requirement for Inertias -- 3.2 RRS Requirement -- 4 Non-spinning Reserve -- 4.1 Background -- 4.2 Net Load Forecast Error (NLFE) Analysis -- 4.3 Net Load Ramp-Up -- 4.4 Adjustment to Non-Spin Need by Considering Forced Outage -- 4.5 Procedures to Determine Non-Spin Need -- 5 Summary -- References -- Chapter 5: Design of New Primary Frequency Control Market for Hosting Frequency Response Reserve Offers from Both Generators a... -- 1 Introduction of Frequency Control -- 2 Impact of Renewable Resource over Inertia and Primary Frequency Control -- 3 Co-optimization of Energy and FRR in Day-Ahead Market -- 3.1 Day-Ahead Market Co-optimization Model -- 3.2 Solution of Day-Ahead Market Co-optimization -- 3.3 Case Studies -- 4 Stochastic Formulations of Co-optimization of Energy and FRR in Day-Ahead Market -- 4.1 Energy, PFR, and Inertia Scheduling Without Uncertainties -- 4.2 Energy, PFR, and Inertia Scheduling Under Uncertainties -- 4.2.1 Scenario Generation and Reduction -- 4.2.2 Interaction Between Day-Ahead Scheduling and Hour-Ahead Operation -- 4.2.3 An ERCOT Case Study -- 4.2.3.1 Deterministic Scheduling Solution -- 4.2.3.2 Stochastic Scheduling Solution -- 4.2.3.3 Comparison Between Deterministic and Stochastic Scheduling Solutions -- 5 Conclusions -- References -- Chapter 6: New Ancillary Service Market for ERCOT: Fast Frequency Response (FFR) -- 1 Introduction -- 2 Existing Ancillary Service Market at ERCOT -- 2.1 Regulation Service -- 2.2 Responsive Reserve Service (RRS) -- 2.3 Non-spin Reserve Service (NSRS) -- 3 Inertia Trend and Primary Frequency Control at ERCOT -- 3.1 Inertia Trend at ERCOT. 3.2 Overview of Frequency Control Coordination at ERCOT -- 3.3 RRS at ERCOT Before Re-design of AS Market -- 4 New Ancillary Service Market -- 5 Fast Frequency Response (FFR) -- 5.1 Qualifications of FFR and Performance Evaluations -- 5.2 Telemetry Data Requirement for Deployment and Recall of FFR -- 6 Maximum Amount of FFR Allowed -- 7 Benefits of FFR -- 7.1 Impact of FFR over Critical Inertia -- 7.2 RRS Cost Saving with FFR Resources -- 8 Conclusions -- References -- Chapter 7: System Inertia Trend and Critical Inertia -- 1 Basics of Synchronous Inertia -- 2 Inertia at ERCOT -- 3 Historical Synchronous Inertia Trends -- 4 Determining Critical Inertia -- 5 ERCOT Tools to Monitor and Forecast System Inertia -- 6 Impact of Parameter Changes on Critical Inertia -- 6.1 ''Faster'' Frequency Response -- 6.2 ''Earlier'' Frequency Response -- 6.3 Lower UFLS Trigger -- 6.4 Reduction of Largest Possible Loss of Generation -- 7 International Review of Inertia-Related Challenges and Mitigation Measures -- 8 Summary of Potential Mitigation Measures to Lower Critical Inertia or Support Minimum Inertia Level -- 9 Conclusions -- References -- Chapter 8: Multiple-Period Reactive Power Coordination for Renewable Integration -- 1 Introduction -- 2 Literature Review -- 3 Renewable Integration and New Transmission Operators -- 4 Reactive Power Coordination (RPC) Tool -- 4.1 Architecture of RPC -- 4.2 Objective Function of RPC -- 4.3 Constraints of RPC -- 4.4 Mathematic Formulations of RPC -- 4.5 Solution Methodology -- 5 Special Considerations -- 5.1 Sensitivity of Reactive Power for a Regulating Bus -- 5.2 Reactive Device's Temporal Constraint -- 5.3 Handling Special Capacitor Banks -- 6 Case Studies -- 6.1 ERCOT Network Model -- 6.2 Verification of Temporal Constraints -- 6.2.1 Initial State of Capacitor Is OFF. 6.2.2 Sequence Constraints Between Master and Slave Capacitors -- 6.3 Simulation Results -- 7 Conclusions -- References -- Chapter 9: Renewable Forecast -- 1 Introduction -- 2 Wind Forecasting System -- 2.1 Wind Forecasting System Overview -- 2.2 Data Flow of Wind Forecasting System -- 2.3 Input Data for Wind Forecasting System -- 2.4 Design Approach of Wind Forecasting System -- 3 Solar Forecasting System and Forecast Errors -- 3.1 Solar Forecasting System -- 3.1.1 NWP Data -- 3.1.2 Machine Learning Algorithms Used by Solar Forecasting System -- 3.1.3 Satellite Cloud Tracking Algorithms -- 3.1.4 Plant Output Models -- 3.1.5 Ensemble Optimization Algorithm -- 3.1.6 Solar Forecast Delivery Mechanism -- 3.2 Solar Forecast Error Analysis -- 3.2.1 Source of Data -- 3.2.2 Probability Distribution Function of Solar Forecast Errors -- 3.2.3 Temporal Correlation of SFE -- 4 Summary and Conclusions -- References -- Chapter 10: Ensemble Machine Learning-Based Wind Forecasting to Combine NWP Output with Data from Weather Stations -- 1 Introduction -- 2 Numerical Weather Prediction -- 3 West Texas Mesonet (WTM) -- 3.1 Value of WTM Data: An Example -- 4 Machine Learning-Based Ensemble Method -- 5 Experimental Results -- 5.1 Performance of Three Machine Learning Algorithms -- 5.2 Performance of Base Algorithms for Large Wind Ramp -- 5.3 Performance of Ensemble Method -- 5.4 Robustness of Proposed Method -- 6 Conclusions -- References -- Index |
| ctrlnum | (ZDB-30-PQE)EBC7248766 (ZDB-30-PAD)EBC7248766 (ZDB-89-EBL)EBL7248766 (OCoLC)1380019449 (DE-599)BVBBV049876109 |
| dewey-full | 333.79409764 |
| dewey-hundreds | 300 - Social sciences |
| dewey-ones | 333 - Economics of land and energy |
| dewey-raw | 333.79409764 |
| dewey-search | 333.79409764 |
| dewey-sort | 3333.79409764 |
| dewey-tens | 330 - Economics |
| discipline | Wirtschaftswissenschaften |
| edition | 1st ed |
| format | Electronic eBook |
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ind2=" "><subfield code="a">Intro -- Preface -- Contents -- Chapter 1: Renewable Integration at ERCOT -- 1 Overview -- 1.1 Texas Power System -- 1.2 Wind Generation Development in Texas -- 1.3 Solar Generation Development in Texas -- 1.4 Interconnection Requirements for Generation Resources -- 2 Transmission Development and Capacity Adequacy -- 2.1 Transmission Access -- 2.2 Transmission Reinforcement -- 2.3 Operational Challenges with High Inverter-Based Resource Penetration -- 2.4 Capacity Adequacy and Wind Generation Resources -- 3 ERCOT Energy and Ancillary Services Market -- 3.1 Ancillary Services -- 4 Reliability and Security of Grid Operations -- 4.1 Requirement for Primary Frequency Response -- 4.2 ERCOT Frequency Performance -- 4.3 System Inertia Trend -- 4.4 Renewable Generation Forecasting -- 4.5 Operations Analysis and Studies -- 4.5.1 Day-Ahead Analysis and Studies -- 4.5.2 Real-Time Analysis and Studies -- 4.5.3 Situational Awareness Tools -- 4.5.4 Challenges for the 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Constraints -- 3.2.4 Load Forecast -- 3.2.5 Offers and Proxy Energy Offer -- 3.3 RUC Process -- 3.3.1 RUC Problem Formulation and Solution Algorithm -- 3.4 Energy Offer Curve for RUC-Committed Resource -- 4 Real-Time SCED -- 4.1 SCED: Energy Dispatch -- 4.1.1 Information Flows in SCED -- 4.1.2 Real-Time Network Security Analysis -- 4.1.3 Resource Limit Calculator (RLC) -- 4.1.4 How SCED Functions -- 4.1.4.1 The Texas Two-Step -- 4.1.4.2 SCED Schedule and Output -- 4.2 Load Frequency Control (LFC) -- 5 Conclusions -- References -- Chapter 3: Market Designs to Integrate Renewable Resources -- 1 Overview -- 2 ERCOT Nodal Market -- 3 Short-Term Wind/PVGR Generation Forecasting and Current Operating Plan (COP) -- 4 IRR Scheduling in DAM, RUC, and SCED -- 4.1 IRR Scheduling in DAM -- 4.2 IRR Generation Scheduling in RUC -- 4.3 IRR Generation Scheduling in Real-Time SCED -- 4.4 Base Point Deviation Charge for IRR -- 4.5 Effect on Management of Congestion -- 4.6 Effect on Market Prices -- 5 Management of Generic Transmission Constraints (GTCs) -- 5.1 Management of GTC Limits -- 5.2 Non-to-Exceedance (NTE) Method -- 5.3 Implementation of NTE Concept -- 6 Incorporation of 5-Minute Wind/Solar Ramp into SCED -- 6.1 Generation to Be Dispatched (GTBD) -- 6.2 Forecast of 5-Minute Solar Ramp -- 7 Conclusions -- Chapter 4: Ancillary Services (AS) at ERCOT -- 1 Overview -- 1.1 Responsive Reserve Service (RRS) -- 1.2 Regulation Reserve Service -- 1.3 Non-spinning Reserve Service -- 2 Regulation Services -- 2.1 Short-Term Wind Generation Forecasting -- 2.2 Method to Determine Regulation Services Requirement -- 2.2.1 An ERCOT Dispatch Model for Calculating Regulation Requirement -- 2.2.2 Regulation Service Requirement -- 2.2.3 Including Effect of Wind Generation -- 2.2.4 Adequacy of Regulation Reserves</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">2.3 Procedures to Determine Regulation Service Requirement -- 2.3.1 Regulation Service Requirements -- 2.3.2 Evaluation of Exhaustion Rate -- 2.3.3 Performance Validation -- 3 Responsive Reserve Requirement -- 3.1 Quantification of PFR and FFR Requirement for Inertias -- 3.2 RRS Requirement -- 4 Non-spinning Reserve -- 4.1 Background -- 4.2 Net Load Forecast Error (NLFE) Analysis -- 4.3 Net Load Ramp-Up -- 4.4 Adjustment to Non-Spin Need by Considering Forced Outage -- 4.5 Procedures to Determine Non-Spin Need -- 5 Summary -- References -- Chapter 5: Design of New Primary Frequency Control Market for Hosting Frequency Response Reserve Offers from Both Generators a... -- 1 Introduction of Frequency Control -- 2 Impact of Renewable Resource over Inertia and Primary Frequency Control -- 3 Co-optimization of Energy and FRR in Day-Ahead Market -- 3.1 Day-Ahead Market Co-optimization Model -- 3.2 Solution of Day-Ahead Market Co-optimization -- 3.3 Case Studies -- 4 Stochastic Formulations of Co-optimization of Energy and FRR in Day-Ahead Market -- 4.1 Energy, PFR, and Inertia Scheduling Without Uncertainties -- 4.2 Energy, PFR, and Inertia Scheduling Under Uncertainties -- 4.2.1 Scenario Generation and Reduction -- 4.2.2 Interaction Between Day-Ahead Scheduling and Hour-Ahead Operation -- 4.2.3 An ERCOT Case Study -- 4.2.3.1 Deterministic Scheduling Solution -- 4.2.3.2 Stochastic Scheduling Solution -- 4.2.3.3 Comparison Between Deterministic and Stochastic Scheduling Solutions -- 5 Conclusions -- References -- Chapter 6: New Ancillary Service Market for ERCOT: Fast Frequency Response (FFR) -- 1 Introduction -- 2 Existing Ancillary Service Market at ERCOT -- 2.1 Regulation Service -- 2.2 Responsive Reserve Service (RRS) -- 2.3 Non-spin Reserve Service (NSRS) -- 3 Inertia Trend and Primary Frequency Control at ERCOT -- 3.1 Inertia Trend at ERCOT.</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">3.2 Overview of Frequency Control Coordination at ERCOT -- 3.3 RRS at ERCOT Before Re-design of AS Market -- 4 New Ancillary Service Market -- 5 Fast Frequency Response (FFR) -- 5.1 Qualifications of FFR and Performance Evaluations -- 5.2 Telemetry Data Requirement for Deployment and Recall of FFR -- 6 Maximum Amount of FFR Allowed -- 7 Benefits of FFR -- 7.1 Impact of FFR over Critical Inertia -- 7.2 RRS Cost Saving with FFR Resources -- 8 Conclusions -- References -- Chapter 7: System Inertia Trend and Critical Inertia -- 1 Basics of Synchronous Inertia -- 2 Inertia at ERCOT -- 3 Historical Synchronous Inertia Trends -- 4 Determining Critical Inertia -- 5 ERCOT Tools to Monitor and Forecast System Inertia -- 6 Impact of Parameter Changes on Critical Inertia -- 6.1 ''Faster'' Frequency Response -- 6.2 ''Earlier'' Frequency Response -- 6.3 Lower UFLS Trigger -- 6.4 Reduction of Largest Possible Loss of Generation -- 7 International Review of Inertia-Related Challenges and Mitigation Measures -- 8 Summary of Potential Mitigation Measures to Lower Critical Inertia or Support Minimum Inertia Level -- 9 Conclusions -- References -- Chapter 8: Multiple-Period Reactive Power Coordination for Renewable Integration -- 1 Introduction -- 2 Literature Review -- 3 Renewable Integration and New Transmission Operators -- 4 Reactive Power Coordination (RPC) Tool -- 4.1 Architecture of RPC -- 4.2 Objective Function of RPC -- 4.3 Constraints of RPC -- 4.4 Mathematic Formulations of RPC -- 4.5 Solution Methodology -- 5 Special Considerations -- 5.1 Sensitivity of Reactive Power for a Regulating Bus -- 5.2 Reactive Device's Temporal Constraint -- 5.3 Handling Special Capacitor Banks -- 6 Case Studies -- 6.1 ERCOT Network Model -- 6.2 Verification of Temporal Constraints -- 6.2.1 Initial State of Capacitor Is OFF.</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">6.2.2 Sequence Constraints Between Master and Slave Capacitors -- 6.3 Simulation Results -- 7 Conclusions -- References -- Chapter 9: Renewable Forecast -- 1 Introduction -- 2 Wind Forecasting System -- 2.1 Wind Forecasting System Overview -- 2.2 Data Flow of Wind Forecasting System -- 2.3 Input Data for Wind Forecasting System -- 2.4 Design Approach of Wind Forecasting System -- 3 Solar Forecasting System and Forecast Errors -- 3.1 Solar Forecasting System -- 3.1.1 NWP Data -- 3.1.2 Machine Learning Algorithms Used by Solar Forecasting System -- 3.1.3 Satellite Cloud Tracking Algorithms -- 3.1.4 Plant Output Models -- 3.1.5 Ensemble Optimization Algorithm -- 3.1.6 Solar Forecast Delivery Mechanism -- 3.2 Solar Forecast Error Analysis -- 3.2.1 Source of Data -- 3.2.2 Probability Distribution Function of Solar Forecast Errors -- 3.2.3 Temporal Correlation of SFE -- 4 Summary and Conclusions -- References -- Chapter 10: Ensemble Machine Learning-Based Wind Forecasting to Combine NWP Output with Data from Weather Stations -- 1 Introduction -- 2 Numerical Weather Prediction -- 3 West Texas Mesonet (WTM) -- 3.1 Value of WTM Data: An Example -- 4 Machine Learning-Based Ensemble Method -- 5 Experimental Results -- 5.1 Performance of Three Machine Learning Algorithms -- 5.2 Performance of Base Algorithms for Large Wind Ramp -- 5.3 Performance of Ensemble Method -- 5.4 Robustness of Proposed Method -- 6 Conclusions -- References -- Index</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe</subfield><subfield code="a">Du, Pengwei</subfield><subfield code="t">Renewable Energy Integration for Bulk Power Systems</subfield><subfield code="d">Cham : Springer International Publishing AG,c2023</subfield><subfield code="z">9783031286384</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-30-PQE</subfield></datafield><datafield tag="943" ind1="1" ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-035215559</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://ebookcentral.proquest.com/lib/hwr/detail.action?docID=7248766</subfield><subfield code="l">DE-2070s</subfield><subfield code="p">ZDB-30-PQE</subfield><subfield code="q">HWR_PDA_PQE</subfield><subfield code="x">Aggregator</subfield><subfield code="3">Volltext</subfield></datafield></record></collection> |
| id | DE-604.BV049876109 |
| illustrated | Not Illustrated |
| indexdate | 2024-09-20T04:22:16Z |
| institution | BVB |
| isbn | 9783031286391 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-035215559 |
| oclc_num | 1380019449 |
| open_access_boolean | |
| owner | DE-2070s |
| owner_facet | DE-2070s |
| physical | 1 Online-Ressource (293 Seiten) |
| psigel | ZDB-30-PQE ZDB-30-PQE HWR_PDA_PQE |
| publishDate | 2023 |
| publishDateSearch | 2023 |
| publishDateSort | 2023 |
| publisher | Springer International Publishing AG |
| record_format | marc |
| series2 | Power Electronics and Power Systems Series |
| spelling | Du, Pengwei Verfasser aut Renewable Energy Integration for Bulk Power Systems ERCOT and the Texas Interconnection 1st ed Cham Springer International Publishing AG 2023 ©2023 1 Online-Ressource (293 Seiten) txt rdacontent c rdamedia cr rdacarrier Power Electronics and Power Systems Series Description based on publisher supplied metadata and other sources Intro -- Preface -- Contents -- Chapter 1: Renewable Integration at ERCOT -- 1 Overview -- 1.1 Texas Power System -- 1.2 Wind Generation Development in Texas -- 1.3 Solar Generation Development in Texas -- 1.4 Interconnection Requirements for Generation Resources -- 2 Transmission Development and Capacity Adequacy -- 2.1 Transmission Access -- 2.2 Transmission Reinforcement -- 2.3 Operational Challenges with High Inverter-Based Resource Penetration -- 2.4 Capacity Adequacy and Wind Generation Resources -- 3 ERCOT Energy and Ancillary Services Market -- 3.1 Ancillary Services -- 4 Reliability and Security of Grid Operations -- 4.1 Requirement for Primary Frequency Response -- 4.2 ERCOT Frequency Performance -- 4.3 System Inertia Trend -- 4.4 Renewable Generation Forecasting -- 4.5 Operations Analysis and Studies -- 4.5.1 Day-Ahead Analysis and Studies -- 4.5.2 Real-Time Analysis and Studies -- 4.5.3 Situational Awareness Tools -- 4.5.4 Challenges for the Nearest Future -- 5 Conclusions -- References -- Chapter 2: Overview of Market Operation at ERCOT -- 1 Overview -- 1.1 Network Modeling -- 1.2 Day-Ahead Operations -- 1.3 Adjustment Period Operations -- 1.4 Real-Time Operations -- 2 Day-Ahead Market (DAM) -- 2.1 DAM Overview -- 2.2 ERCOT and QSE Activities in DAM -- 2.2.1 Ancillary Service Plan Posted in DAM -- 2.2.2 QSE Activities -- 2.2.2.1 Report Availability of Must-Run and Black Start Resources -- 2.2.2.2 Submit Bids for PTP Obligations -- 2.2.2.3 Submit Three-Part Supply Offers -- 2.2.2.4 Submit Energy Bids and Energy-Only Offers -- 2.2.2.5 Submit Self-Arranged Ancillary Service -- 2.2.2.6 Submit Ancillary Service Offers -- 2.2.2.7 Update and Submit Current Operating Plan -- 2.3 DAM Engine -- 3 RUC -- 3.1 RUC Process Overview -- 3.2 Input to RUC Process -- 3.2.1 Current Operating Plan (COP) -- 3.2.2 Network Operations Model 3.2.3 Generic Transmission Constraints -- 3.2.4 Load Forecast -- 3.2.5 Offers and Proxy Energy Offer -- 3.3 RUC Process -- 3.3.1 RUC Problem Formulation and Solution Algorithm -- 3.4 Energy Offer Curve for RUC-Committed Resource -- 4 Real-Time SCED -- 4.1 SCED: Energy Dispatch -- 4.1.1 Information Flows in SCED -- 4.1.2 Real-Time Network Security Analysis -- 4.1.3 Resource Limit Calculator (RLC) -- 4.1.4 How SCED Functions -- 4.1.4.1 The Texas Two-Step -- 4.1.4.2 SCED Schedule and Output -- 4.2 Load Frequency Control (LFC) -- 5 Conclusions -- References -- Chapter 3: Market Designs to Integrate Renewable Resources -- 1 Overview -- 2 ERCOT Nodal Market -- 3 Short-Term Wind/PVGR Generation Forecasting and Current Operating Plan (COP) -- 4 IRR Scheduling in DAM, RUC, and SCED -- 4.1 IRR Scheduling in DAM -- 4.2 IRR Generation Scheduling in RUC -- 4.3 IRR Generation Scheduling in Real-Time SCED -- 4.4 Base Point Deviation Charge for IRR -- 4.5 Effect on Management of Congestion -- 4.6 Effect on Market Prices -- 5 Management of Generic Transmission Constraints (GTCs) -- 5.1 Management of GTC Limits -- 5.2 Non-to-Exceedance (NTE) Method -- 5.3 Implementation of NTE Concept -- 6 Incorporation of 5-Minute Wind/Solar Ramp into SCED -- 6.1 Generation to Be Dispatched (GTBD) -- 6.2 Forecast of 5-Minute Solar Ramp -- 7 Conclusions -- Chapter 4: Ancillary Services (AS) at ERCOT -- 1 Overview -- 1.1 Responsive Reserve Service (RRS) -- 1.2 Regulation Reserve Service -- 1.3 Non-spinning Reserve Service -- 2 Regulation Services -- 2.1 Short-Term Wind Generation Forecasting -- 2.2 Method to Determine Regulation Services Requirement -- 2.2.1 An ERCOT Dispatch Model for Calculating Regulation Requirement -- 2.2.2 Regulation Service Requirement -- 2.2.3 Including Effect of Wind Generation -- 2.2.4 Adequacy of Regulation Reserves 2.3 Procedures to Determine Regulation Service Requirement -- 2.3.1 Regulation Service Requirements -- 2.3.2 Evaluation of Exhaustion Rate -- 2.3.3 Performance Validation -- 3 Responsive Reserve Requirement -- 3.1 Quantification of PFR and FFR Requirement for Inertias -- 3.2 RRS Requirement -- 4 Non-spinning Reserve -- 4.1 Background -- 4.2 Net Load Forecast Error (NLFE) Analysis -- 4.3 Net Load Ramp-Up -- 4.4 Adjustment to Non-Spin Need by Considering Forced Outage -- 4.5 Procedures to Determine Non-Spin Need -- 5 Summary -- References -- Chapter 5: Design of New Primary Frequency Control Market for Hosting Frequency Response Reserve Offers from Both Generators a... -- 1 Introduction of Frequency Control -- 2 Impact of Renewable Resource over Inertia and Primary Frequency Control -- 3 Co-optimization of Energy and FRR in Day-Ahead Market -- 3.1 Day-Ahead Market Co-optimization Model -- 3.2 Solution of Day-Ahead Market Co-optimization -- 3.3 Case Studies -- 4 Stochastic Formulations of Co-optimization of Energy and FRR in Day-Ahead Market -- 4.1 Energy, PFR, and Inertia Scheduling Without Uncertainties -- 4.2 Energy, PFR, and Inertia Scheduling Under Uncertainties -- 4.2.1 Scenario Generation and Reduction -- 4.2.2 Interaction Between Day-Ahead Scheduling and Hour-Ahead Operation -- 4.2.3 An ERCOT Case Study -- 4.2.3.1 Deterministic Scheduling Solution -- 4.2.3.2 Stochastic Scheduling Solution -- 4.2.3.3 Comparison Between Deterministic and Stochastic Scheduling Solutions -- 5 Conclusions -- References -- Chapter 6: New Ancillary Service Market for ERCOT: Fast Frequency Response (FFR) -- 1 Introduction -- 2 Existing Ancillary Service Market at ERCOT -- 2.1 Regulation Service -- 2.2 Responsive Reserve Service (RRS) -- 2.3 Non-spin Reserve Service (NSRS) -- 3 Inertia Trend and Primary Frequency Control at ERCOT -- 3.1 Inertia Trend at ERCOT. 3.2 Overview of Frequency Control Coordination at ERCOT -- 3.3 RRS at ERCOT Before Re-design of AS Market -- 4 New Ancillary Service Market -- 5 Fast Frequency Response (FFR) -- 5.1 Qualifications of FFR and Performance Evaluations -- 5.2 Telemetry Data Requirement for Deployment and Recall of FFR -- 6 Maximum Amount of FFR Allowed -- 7 Benefits of FFR -- 7.1 Impact of FFR over Critical Inertia -- 7.2 RRS Cost Saving with FFR Resources -- 8 Conclusions -- References -- Chapter 7: System Inertia Trend and Critical Inertia -- 1 Basics of Synchronous Inertia -- 2 Inertia at ERCOT -- 3 Historical Synchronous Inertia Trends -- 4 Determining Critical Inertia -- 5 ERCOT Tools to Monitor and Forecast System Inertia -- 6 Impact of Parameter Changes on Critical Inertia -- 6.1 ''Faster'' Frequency Response -- 6.2 ''Earlier'' Frequency Response -- 6.3 Lower UFLS Trigger -- 6.4 Reduction of Largest Possible Loss of Generation -- 7 International Review of Inertia-Related Challenges and Mitigation Measures -- 8 Summary of Potential Mitigation Measures to Lower Critical Inertia or Support Minimum Inertia Level -- 9 Conclusions -- References -- Chapter 8: Multiple-Period Reactive Power Coordination for Renewable Integration -- 1 Introduction -- 2 Literature Review -- 3 Renewable Integration and New Transmission Operators -- 4 Reactive Power Coordination (RPC) Tool -- 4.1 Architecture of RPC -- 4.2 Objective Function of RPC -- 4.3 Constraints of RPC -- 4.4 Mathematic Formulations of RPC -- 4.5 Solution Methodology -- 5 Special Considerations -- 5.1 Sensitivity of Reactive Power for a Regulating Bus -- 5.2 Reactive Device's Temporal Constraint -- 5.3 Handling Special Capacitor Banks -- 6 Case Studies -- 6.1 ERCOT Network Model -- 6.2 Verification of Temporal Constraints -- 6.2.1 Initial State of Capacitor Is OFF. 6.2.2 Sequence Constraints Between Master and Slave Capacitors -- 6.3 Simulation Results -- 7 Conclusions -- References -- Chapter 9: Renewable Forecast -- 1 Introduction -- 2 Wind Forecasting System -- 2.1 Wind Forecasting System Overview -- 2.2 Data Flow of Wind Forecasting System -- 2.3 Input Data for Wind Forecasting System -- 2.4 Design Approach of Wind Forecasting System -- 3 Solar Forecasting System and Forecast Errors -- 3.1 Solar Forecasting System -- 3.1.1 NWP Data -- 3.1.2 Machine Learning Algorithms Used by Solar Forecasting System -- 3.1.3 Satellite Cloud Tracking Algorithms -- 3.1.4 Plant Output Models -- 3.1.5 Ensemble Optimization Algorithm -- 3.1.6 Solar Forecast Delivery Mechanism -- 3.2 Solar Forecast Error Analysis -- 3.2.1 Source of Data -- 3.2.2 Probability Distribution Function of Solar Forecast Errors -- 3.2.3 Temporal Correlation of SFE -- 4 Summary and Conclusions -- References -- Chapter 10: Ensemble Machine Learning-Based Wind Forecasting to Combine NWP Output with Data from Weather Stations -- 1 Introduction -- 2 Numerical Weather Prediction -- 3 West Texas Mesonet (WTM) -- 3.1 Value of WTM Data: An Example -- 4 Machine Learning-Based Ensemble Method -- 5 Experimental Results -- 5.1 Performance of Three Machine Learning Algorithms -- 5.2 Performance of Base Algorithms for Large Wind Ramp -- 5.3 Performance of Ensemble Method -- 5.4 Robustness of Proposed Method -- 6 Conclusions -- References -- Index Erscheint auch als Druck-Ausgabe Du, Pengwei Renewable Energy Integration for Bulk Power Systems Cham : Springer International Publishing AG,c2023 9783031286384 |
| spellingShingle | Du, Pengwei Renewable Energy Integration for Bulk Power Systems ERCOT and the Texas Interconnection Intro -- Preface -- Contents -- Chapter 1: Renewable Integration at ERCOT -- 1 Overview -- 1.1 Texas Power System -- 1.2 Wind Generation Development in Texas -- 1.3 Solar Generation Development in Texas -- 1.4 Interconnection Requirements for Generation Resources -- 2 Transmission Development and Capacity Adequacy -- 2.1 Transmission Access -- 2.2 Transmission Reinforcement -- 2.3 Operational Challenges with High Inverter-Based Resource Penetration -- 2.4 Capacity Adequacy and Wind Generation Resources -- 3 ERCOT Energy and Ancillary Services Market -- 3.1 Ancillary Services -- 4 Reliability and Security of Grid Operations -- 4.1 Requirement for Primary Frequency Response -- 4.2 ERCOT Frequency Performance -- 4.3 System Inertia Trend -- 4.4 Renewable Generation Forecasting -- 4.5 Operations Analysis and Studies -- 4.5.1 Day-Ahead Analysis and Studies -- 4.5.2 Real-Time Analysis and Studies -- 4.5.3 Situational Awareness Tools -- 4.5.4 Challenges for the Nearest Future -- 5 Conclusions -- References -- Chapter 2: Overview of Market Operation at ERCOT -- 1 Overview -- 1.1 Network Modeling -- 1.2 Day-Ahead Operations -- 1.3 Adjustment Period Operations -- 1.4 Real-Time Operations -- 2 Day-Ahead Market (DAM) -- 2.1 DAM Overview -- 2.2 ERCOT and QSE Activities in DAM -- 2.2.1 Ancillary Service Plan Posted in DAM -- 2.2.2 QSE Activities -- 2.2.2.1 Report Availability of Must-Run and Black Start Resources -- 2.2.2.2 Submit Bids for PTP Obligations -- 2.2.2.3 Submit Three-Part Supply Offers -- 2.2.2.4 Submit Energy Bids and Energy-Only Offers -- 2.2.2.5 Submit Self-Arranged Ancillary Service -- 2.2.2.6 Submit Ancillary Service Offers -- 2.2.2.7 Update and Submit Current Operating Plan -- 2.3 DAM Engine -- 3 RUC -- 3.1 RUC Process Overview -- 3.2 Input to RUC Process -- 3.2.1 Current Operating Plan (COP) -- 3.2.2 Network Operations Model 3.2.3 Generic Transmission Constraints -- 3.2.4 Load Forecast -- 3.2.5 Offers and Proxy Energy Offer -- 3.3 RUC Process -- 3.3.1 RUC Problem Formulation and Solution Algorithm -- 3.4 Energy Offer Curve for RUC-Committed Resource -- 4 Real-Time SCED -- 4.1 SCED: Energy Dispatch -- 4.1.1 Information Flows in SCED -- 4.1.2 Real-Time Network Security Analysis -- 4.1.3 Resource Limit Calculator (RLC) -- 4.1.4 How SCED Functions -- 4.1.4.1 The Texas Two-Step -- 4.1.4.2 SCED Schedule and Output -- 4.2 Load Frequency Control (LFC) -- 5 Conclusions -- References -- Chapter 3: Market Designs to Integrate Renewable Resources -- 1 Overview -- 2 ERCOT Nodal Market -- 3 Short-Term Wind/PVGR Generation Forecasting and Current Operating Plan (COP) -- 4 IRR Scheduling in DAM, RUC, and SCED -- 4.1 IRR Scheduling in DAM -- 4.2 IRR Generation Scheduling in RUC -- 4.3 IRR Generation Scheduling in Real-Time SCED -- 4.4 Base Point Deviation Charge for IRR -- 4.5 Effect on Management of Congestion -- 4.6 Effect on Market Prices -- 5 Management of Generic Transmission Constraints (GTCs) -- 5.1 Management of GTC Limits -- 5.2 Non-to-Exceedance (NTE) Method -- 5.3 Implementation of NTE Concept -- 6 Incorporation of 5-Minute Wind/Solar Ramp into SCED -- 6.1 Generation to Be Dispatched (GTBD) -- 6.2 Forecast of 5-Minute Solar Ramp -- 7 Conclusions -- Chapter 4: Ancillary Services (AS) at ERCOT -- 1 Overview -- 1.1 Responsive Reserve Service (RRS) -- 1.2 Regulation Reserve Service -- 1.3 Non-spinning Reserve Service -- 2 Regulation Services -- 2.1 Short-Term Wind Generation Forecasting -- 2.2 Method to Determine Regulation Services Requirement -- 2.2.1 An ERCOT Dispatch Model for Calculating Regulation Requirement -- 2.2.2 Regulation Service Requirement -- 2.2.3 Including Effect of Wind Generation -- 2.2.4 Adequacy of Regulation Reserves 2.3 Procedures to Determine Regulation Service Requirement -- 2.3.1 Regulation Service Requirements -- 2.3.2 Evaluation of Exhaustion Rate -- 2.3.3 Performance Validation -- 3 Responsive Reserve Requirement -- 3.1 Quantification of PFR and FFR Requirement for Inertias -- 3.2 RRS Requirement -- 4 Non-spinning Reserve -- 4.1 Background -- 4.2 Net Load Forecast Error (NLFE) Analysis -- 4.3 Net Load Ramp-Up -- 4.4 Adjustment to Non-Spin Need by Considering Forced Outage -- 4.5 Procedures to Determine Non-Spin Need -- 5 Summary -- References -- Chapter 5: Design of New Primary Frequency Control Market for Hosting Frequency Response Reserve Offers from Both Generators a... -- 1 Introduction of Frequency Control -- 2 Impact of Renewable Resource over Inertia and Primary Frequency Control -- 3 Co-optimization of Energy and FRR in Day-Ahead Market -- 3.1 Day-Ahead Market Co-optimization Model -- 3.2 Solution of Day-Ahead Market Co-optimization -- 3.3 Case Studies -- 4 Stochastic Formulations of Co-optimization of Energy and FRR in Day-Ahead Market -- 4.1 Energy, PFR, and Inertia Scheduling Without Uncertainties -- 4.2 Energy, PFR, and Inertia Scheduling Under Uncertainties -- 4.2.1 Scenario Generation and Reduction -- 4.2.2 Interaction Between Day-Ahead Scheduling and Hour-Ahead Operation -- 4.2.3 An ERCOT Case Study -- 4.2.3.1 Deterministic Scheduling Solution -- 4.2.3.2 Stochastic Scheduling Solution -- 4.2.3.3 Comparison Between Deterministic and Stochastic Scheduling Solutions -- 5 Conclusions -- References -- Chapter 6: New Ancillary Service Market for ERCOT: Fast Frequency Response (FFR) -- 1 Introduction -- 2 Existing Ancillary Service Market at ERCOT -- 2.1 Regulation Service -- 2.2 Responsive Reserve Service (RRS) -- 2.3 Non-spin Reserve Service (NSRS) -- 3 Inertia Trend and Primary Frequency Control at ERCOT -- 3.1 Inertia Trend at ERCOT. 3.2 Overview of Frequency Control Coordination at ERCOT -- 3.3 RRS at ERCOT Before Re-design of AS Market -- 4 New Ancillary Service Market -- 5 Fast Frequency Response (FFR) -- 5.1 Qualifications of FFR and Performance Evaluations -- 5.2 Telemetry Data Requirement for Deployment and Recall of FFR -- 6 Maximum Amount of FFR Allowed -- 7 Benefits of FFR -- 7.1 Impact of FFR over Critical Inertia -- 7.2 RRS Cost Saving with FFR Resources -- 8 Conclusions -- References -- Chapter 7: System Inertia Trend and Critical Inertia -- 1 Basics of Synchronous Inertia -- 2 Inertia at ERCOT -- 3 Historical Synchronous Inertia Trends -- 4 Determining Critical Inertia -- 5 ERCOT Tools to Monitor and Forecast System Inertia -- 6 Impact of Parameter Changes on Critical Inertia -- 6.1 ''Faster'' Frequency Response -- 6.2 ''Earlier'' Frequency Response -- 6.3 Lower UFLS Trigger -- 6.4 Reduction of Largest Possible Loss of Generation -- 7 International Review of Inertia-Related Challenges and Mitigation Measures -- 8 Summary of Potential Mitigation Measures to Lower Critical Inertia or Support Minimum Inertia Level -- 9 Conclusions -- References -- Chapter 8: Multiple-Period Reactive Power Coordination for Renewable Integration -- 1 Introduction -- 2 Literature Review -- 3 Renewable Integration and New Transmission Operators -- 4 Reactive Power Coordination (RPC) Tool -- 4.1 Architecture of RPC -- 4.2 Objective Function of RPC -- 4.3 Constraints of RPC -- 4.4 Mathematic Formulations of RPC -- 4.5 Solution Methodology -- 5 Special Considerations -- 5.1 Sensitivity of Reactive Power for a Regulating Bus -- 5.2 Reactive Device's Temporal Constraint -- 5.3 Handling Special Capacitor Banks -- 6 Case Studies -- 6.1 ERCOT Network Model -- 6.2 Verification of Temporal Constraints -- 6.2.1 Initial State of Capacitor Is OFF. 6.2.2 Sequence Constraints Between Master and Slave Capacitors -- 6.3 Simulation Results -- 7 Conclusions -- References -- Chapter 9: Renewable Forecast -- 1 Introduction -- 2 Wind Forecasting System -- 2.1 Wind Forecasting System Overview -- 2.2 Data Flow of Wind Forecasting System -- 2.3 Input Data for Wind Forecasting System -- 2.4 Design Approach of Wind Forecasting System -- 3 Solar Forecasting System and Forecast Errors -- 3.1 Solar Forecasting System -- 3.1.1 NWP Data -- 3.1.2 Machine Learning Algorithms Used by Solar Forecasting System -- 3.1.3 Satellite Cloud Tracking Algorithms -- 3.1.4 Plant Output Models -- 3.1.5 Ensemble Optimization Algorithm -- 3.1.6 Solar Forecast Delivery Mechanism -- 3.2 Solar Forecast Error Analysis -- 3.2.1 Source of Data -- 3.2.2 Probability Distribution Function of Solar Forecast Errors -- 3.2.3 Temporal Correlation of SFE -- 4 Summary and Conclusions -- References -- Chapter 10: Ensemble Machine Learning-Based Wind Forecasting to Combine NWP Output with Data from Weather Stations -- 1 Introduction -- 2 Numerical Weather Prediction -- 3 West Texas Mesonet (WTM) -- 3.1 Value of WTM Data: An Example -- 4 Machine Learning-Based Ensemble Method -- 5 Experimental Results -- 5.1 Performance of Three Machine Learning Algorithms -- 5.2 Performance of Base Algorithms for Large Wind Ramp -- 5.3 Performance of Ensemble Method -- 5.4 Robustness of Proposed Method -- 6 Conclusions -- References -- Index |
| title | Renewable Energy Integration for Bulk Power Systems ERCOT and the Texas Interconnection |
| title_auth | Renewable Energy Integration for Bulk Power Systems ERCOT and the Texas Interconnection |
| title_exact_search | Renewable Energy Integration for Bulk Power Systems ERCOT and the Texas Interconnection |
| title_full | Renewable Energy Integration for Bulk Power Systems ERCOT and the Texas Interconnection |
| title_fullStr | Renewable Energy Integration for Bulk Power Systems ERCOT and the Texas Interconnection |
| title_full_unstemmed | Renewable Energy Integration for Bulk Power Systems ERCOT and the Texas Interconnection |
| title_short | Renewable Energy Integration for Bulk Power Systems |
| title_sort | renewable energy integration for bulk power systems ercot and the texas interconnection |
| title_sub | ERCOT and the Texas Interconnection |
| work_keys_str_mv | AT dupengwei renewableenergyintegrationforbulkpowersystemsercotandthetexasinterconnection |