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

✍ Scribed by André B. Dorsman, Kazim Baris Atici, Aydin Ulucan, Mehmet Baha Karan

• Publisher: Springer
• Year: 2021
• Tongue: English
• Leaves: 282
• Category: Library

✦ Synopsis

This book on Applied Operations Research and Financial Modelling in Energy (AORFME) presents several applications of operations research (OR) and financial modelling. The contributions by a group of OR and Finance researchers focus on a variety of energy decisions, presenting a quantitative perspective, and providing policy implications of the proposed or applied methodologies. 

The content is divided into three main parts: Applied OR I: Optimization Approaches, Applied OR II: Forecasting Approaches and Financial Modelling: Impacts of Energy Policies and Developments in Energy Markets. The book appeals to scholars in economics, finance and operations research, and to practitioners working in the energy sector.

This is the eighth volume in a series of books on energy organized by the Centre for Energy and Value Issues (CEVI). For this volume, CEVI collaborated with Hacettepe University’s Energy Markets Research and Application Center. The previous volumes in the series are: Financial Aspects in Energy (2011), Energy Economics and Financial Markets (2012), Perspectives on Energy Risk (2014), Energy Technology and Valuation Issues (2015), Energy and Finance (2016), Energy Economy, Finance and Geostrategy (2018), and Financial Implications of Regulations in the Energy Industry (2020).

✦ Table of Contents

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