Applied Operations Research and Financial Modelling in Energy: Practical Applications and Implications

Foreword by Otto Jager
Contents
Introduction: Applied Operations Research and Financial Modeling in Energy
1 Introduction
2 Operations Research and Financial Modelling in Energy
3 Issues Covered in This Book
4 Concluding Remarks
Optimization Methods on Electricity Generation and Transmission Expansion Planning Problem
1 Introduction
2 Mathematical Model
2.1 Objective Function
2.2 Constraints and Technical Conditions
2.3 Final Deterministic Model
3 Uncertainty
3.1 Uncertain Electricity Demand and Power Generation by Renewable Sources
3.2 Uncertain Equipment Failure
4 Solution Method
5 Summary
References
Demand-Driven Electricity Supply Options of Electric Vehicles: Modelling, Simulation, and Management Strategy of Public Charging Stations
1 Introduction
2 Related Work
2.1 Worldwide Current Condition
2.2 Location and Simulation of CSs
3 Locating Charging Stations
4 Simulation Modeling
4.1 Numerical Results
5 Pricing Policies and Open Problems
6 Conclusion
References
A Review on Smart Energy Management Systems in Microgrids Based on Power Generating and Environmental Costs
1 Introduction
2 Renewable Energy and Applications
2.1 Hydroelectric Power
2.2 Solar Power
2.3 Wind Power
2.4 Other Renewables and Contemporary Trends
3 Microgrids and Smart Energy Management Systems (SEMS)
3.1 Smart Energy Management Systems
4 Conclusion
References
Measuring Efficiency and Productivity Change in the Turkish Electricity Distribution Sector
1 Introduction
2 Literature Review
3 An Overview of the Turkish Electricity Market
4 Methodology
4.1 Efficiency Analysis and DEA
4.2 Malmquist Productivity Index
4.3 Tobit Analysis
5 Application
5.1 Data and Sample
6 Results
6.1 DEA Results
6.2 Tobit Results
6.3 Malmquist Productivity Index Results
7 Conclusions
Appendix 1
Appendix 2
Appendix 3
References
Price and Volatility Forecasting in Electricity with Support Vector Regression and Random Forest
1 Introduction
2 Previous Research
2.1 Price Forecasting with Machine Learning in Electricity Markets
2.2 Volatility Forecasting in Electricity Markets
3 Methods
3.1 Support Vector Regression
3.2 Random Forest Modeling
4 Data and Methodology
4.1 Data Set
4.2 Price Forecasting Model
4.3 Volatility Forecasting Model
4.4 Metrics
5 Findings
5.1 Price Forecasting
5.2 Volatility Forecasting
6 Conclusion and Policy Implications
References
Forecasting the Hydro Inflow and Optimization of Virtual Power Plant Pricing
1 Introduction
2 Turkish Electricity Market
3 The Proposed Methodology
4 Hydro Inflow Forecasting
5 Virtual Power Plant Pricing
5.1 Hydro Power Optimization
5.2 VPP Pricing
5.3 Sensitivity to Parameters in Hydro Optimization
5.4 Volume at Risk
6 Concluding Comments
References
Comparing the Renewable Energy Technologies via Forecasting Approaches
1 Introduction
2 Literature Review
2.1 Wind Energy Forecasting
2.2 Hydro Energy Forecasting
3 Brief Information of the Applied Methods
3.1 Principal Component Analysis (PCA)
3.2 Linear Regression and Polynomial Regression
3.3 Long Short-Term Memory (LSTM)
3.4 Gated Recurrent Unit (GRU)
4 Empirical Study
4.1 Dataset and Data Preprocessing
4.2 Empirical Methods
5 Conclusion
References
Business Cycles and  Energy Real Options Valuation 
1 Introduction
2 The Basic Real Option Valuation with Regime Shifts
2.1 Valuing the Option to Invest
2.2 Solution of the Constants and Critical Triggers
2.3 The Single Regime Case
3 Valuing Regime Switching Real Options Under Arithmetic Brownian Motion
3.1 Valuing the Option to Invest in Projects with Regime Switching ABM Cash Flows
3.2 The Single Regime Case
4 Numerical Analysis
5 Conclusions
References
Understanding the Electricity Switching Behavior of Industrial Consumers: An Empirical Study on an Emerging Market
1 Introduction
2 An Overview of Turkish Electricity Retail Market Developments
2.1 Literature and Theoretical Framework
3 Methodology
3.1 Data Description and Procedure
3.2 Measurement of the Study Variables
4 Findings
4.1 The Confirmatory Factor Analyses
4.2 The Preliminary Analyses
4.3 Binomial Logistic Regression Model
4.4 Supplementary Analyses
5 Discussion
Appendix 1: Descriptive Statistics
References
Does the Market Value Clean Innovation? Evidence from US Listed Firms
1 Introduction
2 Hypothesis and Literature Review
2.1 Environment-Friendly Innovation Can Improve a Firm's Financial Performance
2.2 Environment-Friendly Innovation Can Deteriorate a Firm's Financial Performance
3 Data and Variables
3.1 Sample of Firms and Firm-Level Patent Data
3.2 Limitations of Using Patent Measures as a Proxy for Innovation
3.3 Key Variables of Interest
3.4 Descriptive Statistics
4 Methodology
5 Empirical Analysis
5.1 Association Between Tobin's Q and Innovation Productivity Variables
5.2 Do US Firms Have Sufficient Incentive to Produce Environment-Friendly Technologies?
5.3 Association Between Disaggregated Innovation Productivity Variables and Tobin's Q: Tests for Time-Varying Capital Market Response
6 Conclusion and Discussion
References
The Power Grid: From a Technical to a Finance Issue. Who Bears the Financial Risk?
1 Introduction
2 Clearing
3 The Introduction of the Price and Quantity Risk in the Electricity Market
4 Balancing in the Electricity Market and Counterparty Risks
5 Empirical Quantification of Risk
6 Conclusion
References