Economically Enabled Energy Management: Interplay Between Control Engineering and Economics
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| Format: | Electronic eBook |
| Language: | English |
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Singapore
Springer Singapore Pte. Limited
2020
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| Subjects: | |
| Item Description: | Description based on publisher supplied metadata and other sources |
| Physical Description: | 1 Online-Ressource (347 pages) |
| ISBN: | 9789811535765 |
Staff View
MARC
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| 245 | 1 | 0 | |a Economically Enabled Energy Management |b Interplay Between Control Engineering and Economics |
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| 505 | 8 | |a Intro -- Preface -- Contents -- 1 Economically Enabled Energy Management: Overview and Research Opportunities -- 1.1 Introduction -- 1.2 Background of Japanese Power System and Power Markets -- 1.2.1 Structure of Power Industry in Japan -- 1.2.2 Renewable Energy Integration in Japan -- 1.2.3 Power Markets in Japan -- 1.3 Perspectives Toward Economically Enabled Energy Management -- 1.3.1 Power Perspective -- 1.3.2 Economic Perspective -- 1.3.3 Control and Optimization Perspective -- 1.3.4 Interdisciplinary Viewpoint -- 1.4 Organization of the Book -- 1.5 Further Research Opportunities -- 1.5.1 Long-Term Economic Models -- 1.5.2 Systems and Control Analysis for Multi-agent Systems -- References -- 2 Supply and Demand Balance Control Based on Balancing Power Market -- 2.1 Introduction -- 2.2 Power Trade and Locational Marginal Price -- 2.3 Supply and Demand Balance Control Considering Power Flow Congestion -- 2.4 Asymmetric Procurement of Balancing Control Reserves -- 2.4.1 Balancing Control Reserves by VRE -- 2.4.2 Simulation Model and Results -- 2.5 Conclusion -- References -- 3 Resolving Discrepancies in Problem Formulations for Electricity Pricing by Control Engineers and Economists -- 3.1 Introduction -- 3.2 Motivating Examples -- 3.2.1 Control Problems -- 3.2.2 Posing Problems -- 3.2.3 The Economist's Approach -- 3.2.4 Budget Constraints -- 3.2.5 Improved Formulations of the Control Problem -- 3.3 Pricing Problems Between Two Connected Areas -- 3.3.1 Problem Formulation -- 3.3.2 Examples -- 3.4 Conclusion -- References -- 4 Effectiveness of Feed-In Tariff and Renewable Portfolio Standard Under Strategic Pricing in Network Access -- 4.1 Introduction -- 4.2 The Model -- 4.2.1 Outline -- 4.2.2 Vertical Integration -- 4.2.3 Vertical Separation -- 4.3 Comparison of Vertical Integration and Separation -- 4.4 Conclusion -- References | |
| 505 | 8 | |a 5 The Welfare Effects of Environmental Taxation and Subsidization on Renewable Energy Sources in an Oligopolistic Electricity Market -- 5.1 Introduction -- 5.2 Merit Order Effects of Renewable Energy Sources -- 5.3 The Model -- 5.3.1 Conventional Generation -- 5.3.2 Forward Contracts on Electricity -- 5.3.3 Investment in Renewable Energy Sources and Effects of Taxation/Subsidization -- 5.3.4 Second-Best Taxation and Subsidization -- 5.4 Welfare Comparison: Numerical Example of Duopoly -- 5.4.1 Assumptions -- 5.4.2 Results of the Basic Scenario -- 5.4.3 Sensitivity Analysis -- 5.5 Conclusion -- Appendix: Derivation of Key Variables in Equilibrium -- A.1. Derivation of the Equilibrium Production by Conventional Generation in (5.2) -- A.2. Derivation of the Equilibrium Forward Contracts in (5.3) -- A.3. Derivation of the Equilibrium Capacity of Renewable Power Plants in (5.9)-(5.12) -- References -- 6 Behavioral Study of Demand Response: Web-Based Survey, Field Experiment, and Laboratory Experiment -- 6.1 Introduction -- 6.2 Web-Based Survey of Residential Electricity Plan Choice -- 6.2.1 Motivation -- 6.2.2 Method -- 6.2.3 Main Results -- 6.3 Field Experiment on Residential Electricity Plan Choice -- 6.3.1 Motivation -- 6.3.2 Method -- 6.3.3 Main Results -- 6.4 Laboratory Experiment on Residential Energy Conservation -- 6.4.1 Motivation -- 6.4.2 Method -- 6.4.3 Main Results -- 6.5 Field Experiment on Building Electricity Conservation -- 6.5.1 Motivation -- 6.5.2 Method -- 6.5.3 Main Results -- 6.6 Conclusion -- References -- 7 Economic Impact and Market Power of Strategic Aggregators in Energy Demand Networks -- 7.1 Introduction -- 7.2 Three-Layered Optimization Model of Energy Demand Network -- 7.2.1 Utility Company -- 7.2.2 Aggregators -- 7.2.3 Consumers -- 7.2.4 Optimization of Three-Layered Energy Demand Network | |
| 505 | 8 | |a 7.3 Optimization Processes Through Pricing -- 7.3.1 Supply Function Bidding Process -- 7.3.2 Tâtonnement Process -- 7.3.3 Information Exchange via Aggregators -- 7.4 Strategic Behavior of Aggregator -- 7.4.1 Market Power Optimization -- 7.4.2 Battery Storage Operation -- 7.5 Case Studies: Strategic Optimization of Market Power-Related Cost Function -- 7.5.1 Optimization of Market Power-Related Cost Function -- 7.5.2 Optimal Strategy and the Number of Holding Consumers -- 7.6 Case Studies: Strategic Operation of Battery Storage -- 7.7 Conclusion -- References -- 8 Incentive-Based Economic and Physical Integration for Dynamic Power Networks -- 8.1 Introduction -- 8.2 Problem Formulation -- 8.2.1 Grid Model and Information Exchange -- 8.2.2 Control Objectives and Market Model -- 8.3 Lessons from Non-incentive Strategic Bidding for LQG Models -- 8.3.1 LQG Model and Optimal Control Policy -- 8.3.2 Drawbacks in Non-incentive Strategic Bidding Through Examples -- 8.4 Incentivizing Market Design -- 8.4.1 Moral Hazard Incentivizing Market -- 8.4.2 Adverse Selection Incentivizing Market -- 8.5 Simulation -- 8.6 Conclusion -- References -- 9 Distributed Dynamic Pricing in Electricity Market with Information Privacy -- 9.1 Introduction -- 9.2 Distributed Dynamic Pricing with Alternating Decision Making of Market Players Considering Power Flow -- 9.2.1 Problem Formulations Regarding Electricity Market and Power Grid -- 9.2.2 Distributed Maximization of Social Welfare Based on Alternating Decision Making in Market Trading -- 9.2.3 Simulation Verification -- 9.3 Optimal Demand Adjustment of Consumers with Various Electric Appliances Using Dynamic Pricing by Aggregator -- 9.3.1 Problem Formulations of Electricity Market with Aggregator -- 9.3.2 Distributed Maximization of Social Welfare by Adjusting Power Demand of Consumers in a Day-Ahead Market | |
| 505 | 8 | |a 9.3.3 Simulation Verification -- 9.4 Conclusion -- References -- 10 Real-Time Pricing for Electric Power Systems by Nonlinear Model Predictive Control -- 10.1 Introduction -- 10.2 Maximization of Social Welfare -- 10.2.1 Objective -- 10.2.2 Power System Model -- 10.2.3 Real-Time Price Optimization -- 10.2.4 Numerical Simulations -- 10.3 Online Estimation of Consumers' Characteristics -- 10.3.1 Objective -- 10.3.2 Power System Model -- 10.3.3 Control Schemes -- 10.3.4 Numerical Simulations -- 10.4 Stochastic Optimization for High Penetration of Renewable Energy -- 10.4.1 Objective -- 10.4.2 Power System Model -- 10.4.3 Controller -- 10.4.4 Numerical Simulations -- 10.5 Conclusions -- References -- 11 Distributed Multi-Agent Optimization Protocol over Energy Management Networks -- 11.1 Introduction -- 11.2 Problem Formulation -- 11.2.1 Multi-agent Pareto Optimization Problem -- 11.2.2 Penalized Objective Function and Its Exactness -- 11.2.3 Radial Unboundedness of Constraint Functions -- 11.3 Distributed Optimization Protocol -- 11.4 Proofs -- 11.4.1 Preliminaries -- 11.4.2 Proof of the Consensus -- 11.4.3 Proof of the Boundedness -- 11.4.4 Proof of the Convergence -- 11.5 Numerical Examples -- 11.5.1 Minimax Optimization over Unbalanced Network -- 11.5.2 Application to Energy Management Systems -- 11.6 Conclusion -- References -- 12 A Passivity-Based Design of Cyber-Physical Building HVAC Energy Management Integrating Optimization and Physical Dynamics -- 12.1 Introduction -- 12.2 Preliminary -- 12.3 Physical Dynamics and Set Point Optimization -- 12.3.1 Physical Dynamics -- 12.3.2 Set Point Optimization -- 12.4 CPS Design -- 12.4.1 Optimization Dynamics -- 12.4.2 Physical Dynamics with Local HVAC Control -- 12.4.3 CPS Design -- 12.5 Passivity, Optimality, and Stability -- 12.5.1 Equivalent Transformation of Building Dynamics | |
| 505 | 8 | |a 12.5.2 Passivity in Optimization and Physical Dynamics -- 12.5.3 Asymptotic Optimality and Stability -- 12.6 Extension to Co-Optimization of Multiple Buildings -- 12.7 Simulation -- 12.7.1 Development of Real-Time Building Control Simulator -- 12.7.2 Algorithm Design -- 12.7.3 Demonstration -- 12.8 Conclusion -- References | |
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| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |a Hatanaka, Takeshi |t Economically Enabled Energy Management |d Singapore : Springer Singapore Pte. Limited,c2020 |z 9789811535758 |
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| contents | Intro -- Preface -- Contents -- 1 Economically Enabled Energy Management: Overview and Research Opportunities -- 1.1 Introduction -- 1.2 Background of Japanese Power System and Power Markets -- 1.2.1 Structure of Power Industry in Japan -- 1.2.2 Renewable Energy Integration in Japan -- 1.2.3 Power Markets in Japan -- 1.3 Perspectives Toward Economically Enabled Energy Management -- 1.3.1 Power Perspective -- 1.3.2 Economic Perspective -- 1.3.3 Control and Optimization Perspective -- 1.3.4 Interdisciplinary Viewpoint -- 1.4 Organization of the Book -- 1.5 Further Research Opportunities -- 1.5.1 Long-Term Economic Models -- 1.5.2 Systems and Control Analysis for Multi-agent Systems -- References -- 2 Supply and Demand Balance Control Based on Balancing Power Market -- 2.1 Introduction -- 2.2 Power Trade and Locational Marginal Price -- 2.3 Supply and Demand Balance Control Considering Power Flow Congestion -- 2.4 Asymmetric Procurement of Balancing Control Reserves -- 2.4.1 Balancing Control Reserves by VRE -- 2.4.2 Simulation Model and Results -- 2.5 Conclusion -- References -- 3 Resolving Discrepancies in Problem Formulations for Electricity Pricing by Control Engineers and Economists -- 3.1 Introduction -- 3.2 Motivating Examples -- 3.2.1 Control Problems -- 3.2.2 Posing Problems -- 3.2.3 The Economist's Approach -- 3.2.4 Budget Constraints -- 3.2.5 Improved Formulations of the Control Problem -- 3.3 Pricing Problems Between Two Connected Areas -- 3.3.1 Problem Formulation -- 3.3.2 Examples -- 3.4 Conclusion -- References -- 4 Effectiveness of Feed-In Tariff and Renewable Portfolio Standard Under Strategic Pricing in Network Access -- 4.1 Introduction -- 4.2 The Model -- 4.2.1 Outline -- 4.2.2 Vertical Integration -- 4.2.3 Vertical Separation -- 4.3 Comparison of Vertical Integration and Separation -- 4.4 Conclusion -- References 5 The Welfare Effects of Environmental Taxation and Subsidization on Renewable Energy Sources in an Oligopolistic Electricity Market -- 5.1 Introduction -- 5.2 Merit Order Effects of Renewable Energy Sources -- 5.3 The Model -- 5.3.1 Conventional Generation -- 5.3.2 Forward Contracts on Electricity -- 5.3.3 Investment in Renewable Energy Sources and Effects of Taxation/Subsidization -- 5.3.4 Second-Best Taxation and Subsidization -- 5.4 Welfare Comparison: Numerical Example of Duopoly -- 5.4.1 Assumptions -- 5.4.2 Results of the Basic Scenario -- 5.4.3 Sensitivity Analysis -- 5.5 Conclusion -- Appendix: Derivation of Key Variables in Equilibrium -- A.1. Derivation of the Equilibrium Production by Conventional Generation in (5.2) -- A.2. Derivation of the Equilibrium Forward Contracts in (5.3) -- A.3. Derivation of the Equilibrium Capacity of Renewable Power Plants in (5.9)-(5.12) -- References -- 6 Behavioral Study of Demand Response: Web-Based Survey, Field Experiment, and Laboratory Experiment -- 6.1 Introduction -- 6.2 Web-Based Survey of Residential Electricity Plan Choice -- 6.2.1 Motivation -- 6.2.2 Method -- 6.2.3 Main Results -- 6.3 Field Experiment on Residential Electricity Plan Choice -- 6.3.1 Motivation -- 6.3.2 Method -- 6.3.3 Main Results -- 6.4 Laboratory Experiment on Residential Energy Conservation -- 6.4.1 Motivation -- 6.4.2 Method -- 6.4.3 Main Results -- 6.5 Field Experiment on Building Electricity Conservation -- 6.5.1 Motivation -- 6.5.2 Method -- 6.5.3 Main Results -- 6.6 Conclusion -- References -- 7 Economic Impact and Market Power of Strategic Aggregators in Energy Demand Networks -- 7.1 Introduction -- 7.2 Three-Layered Optimization Model of Energy Demand Network -- 7.2.1 Utility Company -- 7.2.2 Aggregators -- 7.2.3 Consumers -- 7.2.4 Optimization of Three-Layered Energy Demand Network 7.3 Optimization Processes Through Pricing -- 7.3.1 Supply Function Bidding Process -- 7.3.2 Tâtonnement Process -- 7.3.3 Information Exchange via Aggregators -- 7.4 Strategic Behavior of Aggregator -- 7.4.1 Market Power Optimization -- 7.4.2 Battery Storage Operation -- 7.5 Case Studies: Strategic Optimization of Market Power-Related Cost Function -- 7.5.1 Optimization of Market Power-Related Cost Function -- 7.5.2 Optimal Strategy and the Number of Holding Consumers -- 7.6 Case Studies: Strategic Operation of Battery Storage -- 7.7 Conclusion -- References -- 8 Incentive-Based Economic and Physical Integration for Dynamic Power Networks -- 8.1 Introduction -- 8.2 Problem Formulation -- 8.2.1 Grid Model and Information Exchange -- 8.2.2 Control Objectives and Market Model -- 8.3 Lessons from Non-incentive Strategic Bidding for LQG Models -- 8.3.1 LQG Model and Optimal Control Policy -- 8.3.2 Drawbacks in Non-incentive Strategic Bidding Through Examples -- 8.4 Incentivizing Market Design -- 8.4.1 Moral Hazard Incentivizing Market -- 8.4.2 Adverse Selection Incentivizing Market -- 8.5 Simulation -- 8.6 Conclusion -- References -- 9 Distributed Dynamic Pricing in Electricity Market with Information Privacy -- 9.1 Introduction -- 9.2 Distributed Dynamic Pricing with Alternating Decision Making of Market Players Considering Power Flow -- 9.2.1 Problem Formulations Regarding Electricity Market and Power Grid -- 9.2.2 Distributed Maximization of Social Welfare Based on Alternating Decision Making in Market Trading -- 9.2.3 Simulation Verification -- 9.3 Optimal Demand Adjustment of Consumers with Various Electric Appliances Using Dynamic Pricing by Aggregator -- 9.3.1 Problem Formulations of Electricity Market with Aggregator -- 9.3.2 Distributed Maximization of Social Welfare by Adjusting Power Demand of Consumers in a Day-Ahead Market 9.3.3 Simulation Verification -- 9.4 Conclusion -- References -- 10 Real-Time Pricing for Electric Power Systems by Nonlinear Model Predictive Control -- 10.1 Introduction -- 10.2 Maximization of Social Welfare -- 10.2.1 Objective -- 10.2.2 Power System Model -- 10.2.3 Real-Time Price Optimization -- 10.2.4 Numerical Simulations -- 10.3 Online Estimation of Consumers' Characteristics -- 10.3.1 Objective -- 10.3.2 Power System Model -- 10.3.3 Control Schemes -- 10.3.4 Numerical Simulations -- 10.4 Stochastic Optimization for High Penetration of Renewable Energy -- 10.4.1 Objective -- 10.4.2 Power System Model -- 10.4.3 Controller -- 10.4.4 Numerical Simulations -- 10.5 Conclusions -- References -- 11 Distributed Multi-Agent Optimization Protocol over Energy Management Networks -- 11.1 Introduction -- 11.2 Problem Formulation -- 11.2.1 Multi-agent Pareto Optimization Problem -- 11.2.2 Penalized Objective Function and Its Exactness -- 11.2.3 Radial Unboundedness of Constraint Functions -- 11.3 Distributed Optimization Protocol -- 11.4 Proofs -- 11.4.1 Preliminaries -- 11.4.2 Proof of the Consensus -- 11.4.3 Proof of the Boundedness -- 11.4.4 Proof of the Convergence -- 11.5 Numerical Examples -- 11.5.1 Minimax Optimization over Unbalanced Network -- 11.5.2 Application to Energy Management Systems -- 11.6 Conclusion -- References -- 12 A Passivity-Based Design of Cyber-Physical Building HVAC Energy Management Integrating Optimization and Physical Dynamics -- 12.1 Introduction -- 12.2 Preliminary -- 12.3 Physical Dynamics and Set Point Optimization -- 12.3.1 Physical Dynamics -- 12.3.2 Set Point Optimization -- 12.4 CPS Design -- 12.4.1 Optimization Dynamics -- 12.4.2 Physical Dynamics with Local HVAC Control -- 12.4.3 CPS Design -- 12.5 Passivity, Optimality, and Stability -- 12.5.1 Equivalent Transformation of Building Dynamics 12.5.2 Passivity in Optimization and Physical Dynamics -- 12.5.3 Asymptotic Optimality and Stability -- 12.6 Extension to Co-Optimization of Multiple Buildings -- 12.7 Simulation -- 12.7.1 Development of Real-Time Building Control Simulator -- 12.7.2 Algorithm Design -- 12.7.3 Demonstration -- 12.8 Conclusion -- References |
| ctrlnum | (ZDB-30-PQE)EBC6181577 (ZDB-30-PAD)EBC6181577 (ZDB-89-EBL)EBL6181577 (OCoLC)1152051987 (DE-599)BVBBV048222660 |
| dewey-full | 333.790952 |
| dewey-hundreds | 300 - Social sciences |
| dewey-ones | 333 - Economics of land and energy |
| dewey-raw | 333.790952 |
| dewey-search | 333.790952 |
| dewey-sort | 3333.790952 |
| dewey-tens | 330 - Economics |
| discipline | Wirtschaftswissenschaften |
| discipline_str_mv | Wirtschaftswissenschaften |
| format | Electronic eBook |
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Limited</subfield><subfield code="c">2020</subfield></datafield><datafield tag="264" ind1=" " ind2="4"><subfield code="c">©2020</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (347 pages)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Description based on publisher supplied metadata and other sources</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">Intro -- Preface -- Contents -- 1 Economically Enabled Energy Management: Overview and Research Opportunities -- 1.1 Introduction -- 1.2 Background of Japanese Power System and Power Markets -- 1.2.1 Structure of Power Industry in Japan -- 1.2.2 Renewable Energy Integration in Japan -- 1.2.3 Power Markets in Japan -- 1.3 Perspectives Toward Economically Enabled Energy Management -- 1.3.1 Power Perspective -- 1.3.2 Economic Perspective -- 1.3.3 Control and Optimization Perspective -- 1.3.4 Interdisciplinary Viewpoint -- 1.4 Organization of the Book -- 1.5 Further Research Opportunities -- 1.5.1 Long-Term Economic Models -- 1.5.2 Systems and Control Analysis for Multi-agent Systems -- References -- 2 Supply and Demand Balance Control Based on Balancing Power Market -- 2.1 Introduction -- 2.2 Power Trade and Locational Marginal Price -- 2.3 Supply and Demand Balance Control Considering Power Flow Congestion -- 2.4 Asymmetric Procurement of Balancing Control Reserves -- 2.4.1 Balancing Control Reserves by VRE -- 2.4.2 Simulation Model and Results -- 2.5 Conclusion -- References -- 3 Resolving Discrepancies in Problem Formulations for Electricity Pricing by Control Engineers and Economists -- 3.1 Introduction -- 3.2 Motivating Examples -- 3.2.1 Control Problems -- 3.2.2 Posing Problems -- 3.2.3 The Economist's Approach -- 3.2.4 Budget Constraints -- 3.2.5 Improved Formulations of the Control Problem -- 3.3 Pricing Problems Between Two Connected Areas -- 3.3.1 Problem Formulation -- 3.3.2 Examples -- 3.4 Conclusion -- References -- 4 Effectiveness of Feed-In Tariff and Renewable Portfolio Standard Under Strategic Pricing in Network Access -- 4.1 Introduction -- 4.2 The Model -- 4.2.1 Outline -- 4.2.2 Vertical Integration -- 4.2.3 Vertical Separation -- 4.3 Comparison of Vertical Integration and Separation -- 4.4 Conclusion -- References</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">5 The Welfare Effects of Environmental Taxation and Subsidization on Renewable Energy Sources in an Oligopolistic Electricity Market -- 5.1 Introduction -- 5.2 Merit Order Effects of Renewable Energy Sources -- 5.3 The Model -- 5.3.1 Conventional Generation -- 5.3.2 Forward Contracts on Electricity -- 5.3.3 Investment in Renewable Energy Sources and Effects of Taxation/Subsidization -- 5.3.4 Second-Best Taxation and Subsidization -- 5.4 Welfare Comparison: Numerical Example of Duopoly -- 5.4.1 Assumptions -- 5.4.2 Results of the Basic Scenario -- 5.4.3 Sensitivity Analysis -- 5.5 Conclusion -- Appendix: Derivation of Key Variables in Equilibrium -- A.1. Derivation of the Equilibrium Production by Conventional Generation in (5.2) -- A.2. Derivation of the Equilibrium Forward Contracts in (5.3) -- A.3. Derivation of the Equilibrium Capacity of Renewable Power Plants in (5.9)-(5.12) -- References -- 6 Behavioral Study of Demand Response: Web-Based Survey, Field Experiment, and Laboratory Experiment -- 6.1 Introduction -- 6.2 Web-Based Survey of Residential Electricity Plan Choice -- 6.2.1 Motivation -- 6.2.2 Method -- 6.2.3 Main Results -- 6.3 Field Experiment on Residential Electricity Plan Choice -- 6.3.1 Motivation -- 6.3.2 Method -- 6.3.3 Main Results -- 6.4 Laboratory Experiment on Residential Energy Conservation -- 6.4.1 Motivation -- 6.4.2 Method -- 6.4.3 Main Results -- 6.5 Field Experiment on Building Electricity Conservation -- 6.5.1 Motivation -- 6.5.2 Method -- 6.5.3 Main Results -- 6.6 Conclusion -- References -- 7 Economic Impact and Market Power of Strategic Aggregators in Energy Demand Networks -- 7.1 Introduction -- 7.2 Three-Layered Optimization Model of Energy Demand Network -- 7.2.1 Utility Company -- 7.2.2 Aggregators -- 7.2.3 Consumers -- 7.2.4 Optimization of Three-Layered Energy Demand Network</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">7.3 Optimization Processes Through Pricing -- 7.3.1 Supply Function Bidding Process -- 7.3.2 Tâtonnement Process -- 7.3.3 Information Exchange via Aggregators -- 7.4 Strategic Behavior of Aggregator -- 7.4.1 Market Power Optimization -- 7.4.2 Battery Storage Operation -- 7.5 Case Studies: Strategic Optimization of Market Power-Related Cost Function -- 7.5.1 Optimization of Market Power-Related Cost Function -- 7.5.2 Optimal Strategy and the Number of Holding Consumers -- 7.6 Case Studies: Strategic Operation of Battery Storage -- 7.7 Conclusion -- References -- 8 Incentive-Based Economic and Physical Integration for Dynamic Power Networks -- 8.1 Introduction -- 8.2 Problem Formulation -- 8.2.1 Grid Model and Information Exchange -- 8.2.2 Control Objectives and Market Model -- 8.3 Lessons from Non-incentive Strategic Bidding for LQG Models -- 8.3.1 LQG Model and Optimal 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Market</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">9.3.3 Simulation Verification -- 9.4 Conclusion -- References -- 10 Real-Time Pricing for Electric Power Systems by Nonlinear Model Predictive Control -- 10.1 Introduction -- 10.2 Maximization of Social Welfare -- 10.2.1 Objective -- 10.2.2 Power System Model -- 10.2.3 Real-Time Price Optimization -- 10.2.4 Numerical Simulations -- 10.3 Online Estimation of Consumers' Characteristics -- 10.3.1 Objective -- 10.3.2 Power System Model -- 10.3.3 Control Schemes -- 10.3.4 Numerical Simulations -- 10.4 Stochastic Optimization for High Penetration of Renewable Energy -- 10.4.1 Objective -- 10.4.2 Power System Model -- 10.4.3 Controller -- 10.4.4 Numerical Simulations -- 10.5 Conclusions -- References -- 11 Distributed Multi-Agent Optimization Protocol over Energy Management Networks -- 11.1 Introduction -- 11.2 Problem Formulation -- 11.2.1 Multi-agent Pareto Optimization Problem -- 11.2.2 Penalized Objective Function and Its Exactness -- 11.2.3 Radial Unboundedness of Constraint Functions -- 11.3 Distributed Optimization Protocol -- 11.4 Proofs -- 11.4.1 Preliminaries -- 11.4.2 Proof of the Consensus -- 11.4.3 Proof of the Boundedness -- 11.4.4 Proof of the Convergence -- 11.5 Numerical Examples -- 11.5.1 Minimax Optimization over Unbalanced Network -- 11.5.2 Application to Energy Management Systems -- 11.6 Conclusion -- References -- 12 A Passivity-Based Design of Cyber-Physical Building HVAC Energy Management Integrating Optimization and Physical Dynamics -- 12.1 Introduction -- 12.2 Preliminary -- 12.3 Physical Dynamics and Set Point Optimization -- 12.3.1 Physical Dynamics -- 12.3.2 Set Point Optimization -- 12.4 CPS Design -- 12.4.1 Optimization Dynamics -- 12.4.2 Physical Dynamics with Local HVAC Control -- 12.4.3 CPS Design -- 12.5 Passivity, Optimality, and Stability -- 12.5.1 Equivalent Transformation of Building Dynamics</subfield></datafield><datafield tag="505" 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Limited,c2020</subfield><subfield code="z">9789811535758</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-30-PQE</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-033603393</subfield></datafield></record></collection> |
| id | DE-604.BV048222660 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T19:50:37Z |
| indexdate | 2024-07-10T09:32:26Z |
| institution | BVB |
| isbn | 9789811535765 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-033603393 |
| oclc_num | 1152051987 |
| open_access_boolean | |
| physical | 1 Online-Ressource (347 pages) |
| psigel | ZDB-30-PQE |
| publishDate | 2020 |
| publishDateSearch | 2020 |
| publishDateSort | 2020 |
| publisher | Springer Singapore Pte. Limited |
| record_format | marc |
| spelling | Hatanaka, Takeshi Verfasser aut Economically Enabled Energy Management Interplay Between Control Engineering and Economics Singapore Springer Singapore Pte. Limited 2020 ©2020 1 Online-Ressource (347 pages) txt rdacontent c rdamedia cr rdacarrier Description based on publisher supplied metadata and other sources Intro -- Preface -- Contents -- 1 Economically Enabled Energy Management: Overview and Research Opportunities -- 1.1 Introduction -- 1.2 Background of Japanese Power System and Power Markets -- 1.2.1 Structure of Power Industry in Japan -- 1.2.2 Renewable Energy Integration in Japan -- 1.2.3 Power Markets in Japan -- 1.3 Perspectives Toward Economically Enabled Energy Management -- 1.3.1 Power Perspective -- 1.3.2 Economic Perspective -- 1.3.3 Control and Optimization Perspective -- 1.3.4 Interdisciplinary Viewpoint -- 1.4 Organization of the Book -- 1.5 Further Research Opportunities -- 1.5.1 Long-Term Economic Models -- 1.5.2 Systems and Control Analysis for Multi-agent Systems -- References -- 2 Supply and Demand Balance Control Based on Balancing Power Market -- 2.1 Introduction -- 2.2 Power Trade and Locational Marginal Price -- 2.3 Supply and Demand Balance Control Considering Power Flow Congestion -- 2.4 Asymmetric Procurement of Balancing Control Reserves -- 2.4.1 Balancing Control Reserves by VRE -- 2.4.2 Simulation Model and Results -- 2.5 Conclusion -- References -- 3 Resolving Discrepancies in Problem Formulations for Electricity Pricing by Control Engineers and Economists -- 3.1 Introduction -- 3.2 Motivating Examples -- 3.2.1 Control Problems -- 3.2.2 Posing Problems -- 3.2.3 The Economist's Approach -- 3.2.4 Budget Constraints -- 3.2.5 Improved Formulations of the Control Problem -- 3.3 Pricing Problems Between Two Connected Areas -- 3.3.1 Problem Formulation -- 3.3.2 Examples -- 3.4 Conclusion -- References -- 4 Effectiveness of Feed-In Tariff and Renewable Portfolio Standard Under Strategic Pricing in Network Access -- 4.1 Introduction -- 4.2 The Model -- 4.2.1 Outline -- 4.2.2 Vertical Integration -- 4.2.3 Vertical Separation -- 4.3 Comparison of Vertical Integration and Separation -- 4.4 Conclusion -- References 5 The Welfare Effects of Environmental Taxation and Subsidization on Renewable Energy Sources in an Oligopolistic Electricity Market -- 5.1 Introduction -- 5.2 Merit Order Effects of Renewable Energy Sources -- 5.3 The Model -- 5.3.1 Conventional Generation -- 5.3.2 Forward Contracts on Electricity -- 5.3.3 Investment in Renewable Energy Sources and Effects of Taxation/Subsidization -- 5.3.4 Second-Best Taxation and Subsidization -- 5.4 Welfare Comparison: Numerical Example of Duopoly -- 5.4.1 Assumptions -- 5.4.2 Results of the Basic Scenario -- 5.4.3 Sensitivity Analysis -- 5.5 Conclusion -- Appendix: Derivation of Key Variables in Equilibrium -- A.1. Derivation of the Equilibrium Production by Conventional Generation in (5.2) -- A.2. Derivation of the Equilibrium Forward Contracts in (5.3) -- A.3. Derivation of the Equilibrium Capacity of Renewable Power Plants in (5.9)-(5.12) -- References -- 6 Behavioral Study of Demand Response: Web-Based Survey, Field Experiment, and Laboratory Experiment -- 6.1 Introduction -- 6.2 Web-Based Survey of Residential Electricity Plan Choice -- 6.2.1 Motivation -- 6.2.2 Method -- 6.2.3 Main Results -- 6.3 Field Experiment on Residential Electricity Plan Choice -- 6.3.1 Motivation -- 6.3.2 Method -- 6.3.3 Main Results -- 6.4 Laboratory Experiment on Residential Energy Conservation -- 6.4.1 Motivation -- 6.4.2 Method -- 6.4.3 Main Results -- 6.5 Field Experiment on Building Electricity Conservation -- 6.5.1 Motivation -- 6.5.2 Method -- 6.5.3 Main Results -- 6.6 Conclusion -- References -- 7 Economic Impact and Market Power of Strategic Aggregators in Energy Demand Networks -- 7.1 Introduction -- 7.2 Three-Layered Optimization Model of Energy Demand Network -- 7.2.1 Utility Company -- 7.2.2 Aggregators -- 7.2.3 Consumers -- 7.2.4 Optimization of Three-Layered Energy Demand Network 7.3 Optimization Processes Through Pricing -- 7.3.1 Supply Function Bidding Process -- 7.3.2 Tâtonnement Process -- 7.3.3 Information Exchange via Aggregators -- 7.4 Strategic Behavior of Aggregator -- 7.4.1 Market Power Optimization -- 7.4.2 Battery Storage Operation -- 7.5 Case Studies: Strategic Optimization of Market Power-Related Cost Function -- 7.5.1 Optimization of Market Power-Related Cost Function -- 7.5.2 Optimal Strategy and the Number of Holding Consumers -- 7.6 Case Studies: Strategic Operation of Battery Storage -- 7.7 Conclusion -- References -- 8 Incentive-Based Economic and Physical Integration for Dynamic Power Networks -- 8.1 Introduction -- 8.2 Problem Formulation -- 8.2.1 Grid Model and Information Exchange -- 8.2.2 Control Objectives and Market Model -- 8.3 Lessons from Non-incentive Strategic Bidding for LQG Models -- 8.3.1 LQG Model and Optimal Control Policy -- 8.3.2 Drawbacks in Non-incentive Strategic Bidding Through Examples -- 8.4 Incentivizing Market Design -- 8.4.1 Moral Hazard Incentivizing Market -- 8.4.2 Adverse Selection Incentivizing Market -- 8.5 Simulation -- 8.6 Conclusion -- References -- 9 Distributed Dynamic Pricing in Electricity Market with Information Privacy -- 9.1 Introduction -- 9.2 Distributed Dynamic Pricing with Alternating Decision Making of Market Players Considering Power Flow -- 9.2.1 Problem Formulations Regarding Electricity Market and Power Grid -- 9.2.2 Distributed Maximization of Social Welfare Based on Alternating Decision Making in Market Trading -- 9.2.3 Simulation Verification -- 9.3 Optimal Demand Adjustment of Consumers with Various Electric Appliances Using Dynamic Pricing by Aggregator -- 9.3.1 Problem Formulations of Electricity Market with Aggregator -- 9.3.2 Distributed Maximization of Social Welfare by Adjusting Power Demand of Consumers in a Day-Ahead Market 9.3.3 Simulation Verification -- 9.4 Conclusion -- References -- 10 Real-Time Pricing for Electric Power Systems by Nonlinear Model Predictive Control -- 10.1 Introduction -- 10.2 Maximization of Social Welfare -- 10.2.1 Objective -- 10.2.2 Power System Model -- 10.2.3 Real-Time Price Optimization -- 10.2.4 Numerical Simulations -- 10.3 Online Estimation of Consumers' Characteristics -- 10.3.1 Objective -- 10.3.2 Power System Model -- 10.3.3 Control Schemes -- 10.3.4 Numerical Simulations -- 10.4 Stochastic Optimization for High Penetration of Renewable Energy -- 10.4.1 Objective -- 10.4.2 Power System Model -- 10.4.3 Controller -- 10.4.4 Numerical Simulations -- 10.5 Conclusions -- References -- 11 Distributed Multi-Agent Optimization Protocol over Energy Management Networks -- 11.1 Introduction -- 11.2 Problem Formulation -- 11.2.1 Multi-agent Pareto Optimization Problem -- 11.2.2 Penalized Objective Function and Its Exactness -- 11.2.3 Radial Unboundedness of Constraint Functions -- 11.3 Distributed Optimization Protocol -- 11.4 Proofs -- 11.4.1 Preliminaries -- 11.4.2 Proof of the Consensus -- 11.4.3 Proof of the Boundedness -- 11.4.4 Proof of the Convergence -- 11.5 Numerical Examples -- 11.5.1 Minimax Optimization over Unbalanced Network -- 11.5.2 Application to Energy Management Systems -- 11.6 Conclusion -- References -- 12 A Passivity-Based Design of Cyber-Physical Building HVAC Energy Management Integrating Optimization and Physical Dynamics -- 12.1 Introduction -- 12.2 Preliminary -- 12.3 Physical Dynamics and Set Point Optimization -- 12.3.1 Physical Dynamics -- 12.3.2 Set Point Optimization -- 12.4 CPS Design -- 12.4.1 Optimization Dynamics -- 12.4.2 Physical Dynamics with Local HVAC Control -- 12.4.3 CPS Design -- 12.5 Passivity, Optimality, and Stability -- 12.5.1 Equivalent Transformation of Building Dynamics 12.5.2 Passivity in Optimization and Physical Dynamics -- 12.5.3 Asymptotic Optimality and Stability -- 12.6 Extension to Co-Optimization of Multiple Buildings -- 12.7 Simulation -- 12.7.1 Development of Real-Time Building Control Simulator -- 12.7.2 Algorithm Design -- 12.7.3 Demonstration -- 12.8 Conclusion -- References Energy policy-Japan Wasa, Yasuaki Sonstige oth Uchida, Kenko Sonstige oth Erscheint auch als Druck-Ausgabe Hatanaka, Takeshi Economically Enabled Energy Management Singapore : Springer Singapore Pte. Limited,c2020 9789811535758 |
| spellingShingle | Hatanaka, Takeshi Economically Enabled Energy Management Interplay Between Control Engineering and Economics Intro -- Preface -- Contents -- 1 Economically Enabled Energy Management: Overview and Research Opportunities -- 1.1 Introduction -- 1.2 Background of Japanese Power System and Power Markets -- 1.2.1 Structure of Power Industry in Japan -- 1.2.2 Renewable Energy Integration in Japan -- 1.2.3 Power Markets in Japan -- 1.3 Perspectives Toward Economically Enabled Energy Management -- 1.3.1 Power Perspective -- 1.3.2 Economic Perspective -- 1.3.3 Control and Optimization Perspective -- 1.3.4 Interdisciplinary Viewpoint -- 1.4 Organization of the Book -- 1.5 Further Research Opportunities -- 1.5.1 Long-Term Economic Models -- 1.5.2 Systems and Control Analysis for Multi-agent Systems -- References -- 2 Supply and Demand Balance Control Based on Balancing Power Market -- 2.1 Introduction -- 2.2 Power Trade and Locational Marginal Price -- 2.3 Supply and Demand Balance Control Considering Power Flow Congestion -- 2.4 Asymmetric Procurement of Balancing Control Reserves -- 2.4.1 Balancing Control Reserves by VRE -- 2.4.2 Simulation Model and Results -- 2.5 Conclusion -- References -- 3 Resolving Discrepancies in Problem Formulations for Electricity Pricing by Control Engineers and Economists -- 3.1 Introduction -- 3.2 Motivating Examples -- 3.2.1 Control Problems -- 3.2.2 Posing Problems -- 3.2.3 The Economist's Approach -- 3.2.4 Budget Constraints -- 3.2.5 Improved Formulations of the Control Problem -- 3.3 Pricing Problems Between Two Connected Areas -- 3.3.1 Problem Formulation -- 3.3.2 Examples -- 3.4 Conclusion -- References -- 4 Effectiveness of Feed-In Tariff and Renewable Portfolio Standard Under Strategic Pricing in Network Access -- 4.1 Introduction -- 4.2 The Model -- 4.2.1 Outline -- 4.2.2 Vertical Integration -- 4.2.3 Vertical Separation -- 4.3 Comparison of Vertical Integration and Separation -- 4.4 Conclusion -- References 5 The Welfare Effects of Environmental Taxation and Subsidization on Renewable Energy Sources in an Oligopolistic Electricity Market -- 5.1 Introduction -- 5.2 Merit Order Effects of Renewable Energy Sources -- 5.3 The Model -- 5.3.1 Conventional Generation -- 5.3.2 Forward Contracts on Electricity -- 5.3.3 Investment in Renewable Energy Sources and Effects of Taxation/Subsidization -- 5.3.4 Second-Best Taxation and Subsidization -- 5.4 Welfare Comparison: Numerical Example of Duopoly -- 5.4.1 Assumptions -- 5.4.2 Results of the Basic Scenario -- 5.4.3 Sensitivity Analysis -- 5.5 Conclusion -- Appendix: Derivation of Key Variables in Equilibrium -- A.1. Derivation of the Equilibrium Production by Conventional Generation in (5.2) -- A.2. Derivation of the Equilibrium Forward Contracts in (5.3) -- A.3. Derivation of the Equilibrium Capacity of Renewable Power Plants in (5.9)-(5.12) -- References -- 6 Behavioral Study of Demand Response: Web-Based Survey, Field Experiment, and Laboratory Experiment -- 6.1 Introduction -- 6.2 Web-Based Survey of Residential Electricity Plan Choice -- 6.2.1 Motivation -- 6.2.2 Method -- 6.2.3 Main Results -- 6.3 Field Experiment on Residential Electricity Plan Choice -- 6.3.1 Motivation -- 6.3.2 Method -- 6.3.3 Main Results -- 6.4 Laboratory Experiment on Residential Energy Conservation -- 6.4.1 Motivation -- 6.4.2 Method -- 6.4.3 Main Results -- 6.5 Field Experiment on Building Electricity Conservation -- 6.5.1 Motivation -- 6.5.2 Method -- 6.5.3 Main Results -- 6.6 Conclusion -- References -- 7 Economic Impact and Market Power of Strategic Aggregators in Energy Demand Networks -- 7.1 Introduction -- 7.2 Three-Layered Optimization Model of Energy Demand Network -- 7.2.1 Utility Company -- 7.2.2 Aggregators -- 7.2.3 Consumers -- 7.2.4 Optimization of Three-Layered Energy Demand Network 7.3 Optimization Processes Through Pricing -- 7.3.1 Supply Function Bidding Process -- 7.3.2 Tâtonnement Process -- 7.3.3 Information Exchange via Aggregators -- 7.4 Strategic Behavior of Aggregator -- 7.4.1 Market Power Optimization -- 7.4.2 Battery Storage Operation -- 7.5 Case Studies: Strategic Optimization of Market Power-Related Cost Function -- 7.5.1 Optimization of Market Power-Related Cost Function -- 7.5.2 Optimal Strategy and the Number of Holding Consumers -- 7.6 Case Studies: Strategic Operation of Battery Storage -- 7.7 Conclusion -- References -- 8 Incentive-Based Economic and Physical Integration for Dynamic Power Networks -- 8.1 Introduction -- 8.2 Problem Formulation -- 8.2.1 Grid Model and Information Exchange -- 8.2.2 Control Objectives and Market Model -- 8.3 Lessons from Non-incentive Strategic Bidding for LQG Models -- 8.3.1 LQG Model and Optimal Control Policy -- 8.3.2 Drawbacks in Non-incentive Strategic Bidding Through Examples -- 8.4 Incentivizing Market Design -- 8.4.1 Moral Hazard Incentivizing Market -- 8.4.2 Adverse Selection Incentivizing Market -- 8.5 Simulation -- 8.6 Conclusion -- References -- 9 Distributed Dynamic Pricing in Electricity Market with Information Privacy -- 9.1 Introduction -- 9.2 Distributed Dynamic Pricing with Alternating Decision Making of Market Players Considering Power Flow -- 9.2.1 Problem Formulations Regarding Electricity Market and Power Grid -- 9.2.2 Distributed Maximization of Social Welfare Based on Alternating Decision Making in Market Trading -- 9.2.3 Simulation Verification -- 9.3 Optimal Demand Adjustment of Consumers with Various Electric Appliances Using Dynamic Pricing by Aggregator -- 9.3.1 Problem Formulations of Electricity Market with Aggregator -- 9.3.2 Distributed Maximization of Social Welfare by Adjusting Power Demand of Consumers in a Day-Ahead Market 9.3.3 Simulation Verification -- 9.4 Conclusion -- References -- 10 Real-Time Pricing for Electric Power Systems by Nonlinear Model Predictive Control -- 10.1 Introduction -- 10.2 Maximization of Social Welfare -- 10.2.1 Objective -- 10.2.2 Power System Model -- 10.2.3 Real-Time Price Optimization -- 10.2.4 Numerical Simulations -- 10.3 Online Estimation of Consumers' Characteristics -- 10.3.1 Objective -- 10.3.2 Power System Model -- 10.3.3 Control Schemes -- 10.3.4 Numerical Simulations -- 10.4 Stochastic Optimization for High Penetration of Renewable Energy -- 10.4.1 Objective -- 10.4.2 Power System Model -- 10.4.3 Controller -- 10.4.4 Numerical Simulations -- 10.5 Conclusions -- References -- 11 Distributed Multi-Agent Optimization Protocol over Energy Management Networks -- 11.1 Introduction -- 11.2 Problem Formulation -- 11.2.1 Multi-agent Pareto Optimization Problem -- 11.2.2 Penalized Objective Function and Its Exactness -- 11.2.3 Radial Unboundedness of Constraint Functions -- 11.3 Distributed Optimization Protocol -- 11.4 Proofs -- 11.4.1 Preliminaries -- 11.4.2 Proof of the Consensus -- 11.4.3 Proof of the Boundedness -- 11.4.4 Proof of the Convergence -- 11.5 Numerical Examples -- 11.5.1 Minimax Optimization over Unbalanced Network -- 11.5.2 Application to Energy Management Systems -- 11.6 Conclusion -- References -- 12 A Passivity-Based Design of Cyber-Physical Building HVAC Energy Management Integrating Optimization and Physical Dynamics -- 12.1 Introduction -- 12.2 Preliminary -- 12.3 Physical Dynamics and Set Point Optimization -- 12.3.1 Physical Dynamics -- 12.3.2 Set Point Optimization -- 12.4 CPS Design -- 12.4.1 Optimization Dynamics -- 12.4.2 Physical Dynamics with Local HVAC Control -- 12.4.3 CPS Design -- 12.5 Passivity, Optimality, and Stability -- 12.5.1 Equivalent Transformation of Building Dynamics 12.5.2 Passivity in Optimization and Physical Dynamics -- 12.5.3 Asymptotic Optimality and Stability -- 12.6 Extension to Co-Optimization of Multiple Buildings -- 12.7 Simulation -- 12.7.1 Development of Real-Time Building Control Simulator -- 12.7.2 Algorithm Design -- 12.7.3 Demonstration -- 12.8 Conclusion -- References Energy policy-Japan |
| title | Economically Enabled Energy Management Interplay Between Control Engineering and Economics |
| title_auth | Economically Enabled Energy Management Interplay Between Control Engineering and Economics |
| title_exact_search | Economically Enabled Energy Management Interplay Between Control Engineering and Economics |
| title_exact_search_txtP | Economically Enabled Energy Management Interplay Between Control Engineering and Economics |
| title_full | Economically Enabled Energy Management Interplay Between Control Engineering and Economics |
| title_fullStr | Economically Enabled Energy Management Interplay Between Control Engineering and Economics |
| title_full_unstemmed | Economically Enabled Energy Management Interplay Between Control Engineering and Economics |
| title_short | Economically Enabled Energy Management |
| title_sort | economically enabled energy management interplay between control engineering and economics |
| title_sub | Interplay Between Control Engineering and Economics |
| topic | Energy policy-Japan |
| topic_facet | Energy policy-Japan |
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