Mathematical Modelling of Contemporary Electricity Markets

Front-Matter_2021_Mathematical-Modelling-of-Contemporary-Electricity-Markets
Front Matter
Copyright_2021_Mathematical-Modelling-of-Contemporary-Electricity-Markets
Copyright
Contributors_2021_Mathematical-Modelling-of-Contemporary-Electricity-Markets
Contributors
Preface_2021_Mathematical-Modelling-of-Contemporary-Electricity-Markets
Preface
Introduction_2021_Mathematical-Modelling-of-Contemporary-Electricity-Markets
Introduction
Which is the need for the book? What are its aims and scope?
What problems does the book solve?
What are the features and benefits of the book?
Who is the target audience
What is the contribution of the book in the literature?
What is the structure of the book? Does its nature (book of chapters) affect its coherence and quality?
References
Chapter-1---Forecasting-energy-dema_2021_Mathematical-Modelling-of-Contempor
Forecasting energy demand with econometrics
Introduction
Methodology
Methodology application
Data
Long-run
Short run
Impulse response functions (IRFs)
Conclusions
References
Chapter-2---An-econometric-approach-for-Ge_2021_Mathematical-Modelling-of-Co
An econometric approach for Germanys short-term energy demand forecasting
Introduction
German energy landscape
Data and methodology
Variables description
Methods and formulas
AR (p) and MA (q)
ARMA and ARMAX
Forecasting
AR
Forecast with MA
Forecast with ARMA (p,q) model
Forecasting accuracy
Results
Measuring forecasting accuracy
Comparing linear regression, simple exponential smoothing and ARMAX models
Conclusions
Appendix
References
Further reading
Chapter-3---A-novel-adaptive-day-ahead-load-forecas_2021_Mathematical-Modell
A novel adaptive day-ahead load forecast method, incorporating non-metered distributed generation: A compariso ...
Introduction
Comparative review of load forecasting methodologies
Load forecasting methods applied by TSOs
Neural networks-Mathematical background
RNNs-Transition toward LSTM
Long short-term memory
Short-term load forecast using LSTM network
Input dataset
Data preprocessing, standardization
LSTM model specification
Result evaluation
Discussion on the correlation of non-metered generation and daily loads
Conclusions
References
Chapter-4---Forecasting-week-ahead-hourly-elect_2021_Mathematical-Modelling-
Forecasting week-ahead hourly electricity prices in Belgium with statistical and machine learning methods
Introduction
Statistical and machine learning methods in electricity price forecasting
Overview of forecasting methods
Statistical methods
Seasonal naïve (sNaive)
Exponential smoothing (ES)
Seasonally adjusted simple exponential smoothing (DSES)
Seasonally adjusted exponential smoothing (DES)
Multiple Aggregation Prediction Algorithm (MAPA)
Multiple linear regression (MLR)
Autoregressive integrated moving average (ARIMA)
Machine learning methods
Multi-layer perceptron (MLP)
Random forest (RF)
Combinations
Empirical evaluation
Dataset
Experimental set-up
Results
Conclusions
References
Chapter-5---Use-probabilistic-forecasting-to-m_2021_Mathematical-Modelling-o
Use probabilistic forecasting to model uncertainties in electricity markets-A wind power example
Introduction
Data source and data conditioning
Data source
Data conditioning
Outlier detection
Data preparation
Distribution and correlation analysis
Forecasting methodology
Multiple linear regression
k-Nearest neighbors algorithm
Coordinate descent algorithm
Probabilistic forecasting based on KDE method
Probabilistic forecasting based on KDE method
Model selection
Results
Error measures
Model configuration
Evaluation results
Error analysis
Geographical distribution
Error distribution
RMSE vs. quantile score
Impact of NWP quality
Conclusions
References
Chapter-6---Modelling-interlinked-commodi_2021_Mathematical-Modelling-of-Con
Modelling interlinked commodities´ prices: The case of natural gas
Introduction
Literature review
Data and methodology
Data
Methodology
Structural breaks
Price transmission
Multivariate conditional volatility
Empirical results
Structural breaks
Price transmission
Multivariate conditional volatility
Conclusions
References
Chapter-7---An-optimization-model-for-the-_2021_Mathematical-Modelling-of-Co
An optimization model for the economic dispatch problem in power exchanges
Introduction
Mathematical model
Objective function
Model constraints
Energy supply limits
Energy consumption limits
Energy exchange limits
Block orders-Acceptance ratio
Block orders energy generation
Time-flexible block orders
Demand balance
Case study description
Results and discussion
Power system´s marginal price
Electricity trading
Thermal units´ operation
Conclusions
References
Chapter-8---Power-system-flexibility--A-methodolo_2021_Mathematical-Modellin
Power system flexibility: A methodological analytical framework based on unit commitment and economic dispatch ...
Introduction
Structure
Methodology
Preliminary evaluation of flexibility requirements
Assessment of technical capability of resources to provide flexibility
UCED model
Basic features of the UCED model
Specific issues on the formulation of the UCED model
Modelling of Reserves
Modelling of storage and DR
Modelling of maintenance operations and hydro operation
Representation of non-explicitly modeled countries
Modelling of demand
Examined indicators for the detailed analysis of power system operational flexibility
Methodology application
Case study
Results
Preliminary evaluation of flexibility requirements
Assessment of technical capability of resources to provide flexibility
Detailed analysis of power system operational flexibility
Convergence of the Monte Carlo simulations
Discussion
Critical points
Non-availability of energy versus the non-availability of adequate level of reserve
Relation between flexibility characteristics and expected market outcomes
Impact of demand response
Identification of areas for further improvement
Representation of non-explicitly modeled countries
Network modelling
Mid-term/short-term hydro scheduling coordination
Better representation of the Intraday Market
Better representation of the Balancing Market
Representation of thermal efficiency of conventional power plants
Future challenges
Conclusions
Appendix: Further results
References
Chapter-9---Retailer-profit-maximization-with_2021_Mathematical-Modelling-of
Retailer profit maximization with the assistance of price and load forecasting processes
Introduction
Methodology
Problem formulation
Test case
Results
Conclusions
References
Chapter-10---Modelling-cross-border-interacti_2021_Mathematical-Modelling-of
Modelling cross-border interactions of EU balancing markets: A focus on scarcity pricing
Introduction
Scarcity pricing in US markets
Scarcity pricing in EU markets
Cross-border considerations
Structure of the chapter
The stochastic equilibrium model
Real time
Real-time balancing platform
Generators in the Netherlands
Generators in Belgium
Loads
Belgian network operator
Market clearing
Day ahead
Day-ahead market clearing platform
Generators in Belgium
Generators in the Netherlands
Loads
Network operator
Market clearing
Application on a two-zone system
Market for real-time energy in both zones
Market for real-time reserve capacity in Belgium but not in the Netherlands
Day-ahead energy market
Day-ahead reserve market
Leaning on Dutch resources
Discussion
Equilibrium model solutions versus actual platform outcomes
Institutional considerations
Conclusions and perspectives
Appendix: Glossary
References
Chapter-11---Electricity-portfolio-optim_2021_Mathematical-Modelling-of-Cont
Electricity portfolio optimization: Cost minimization using MILP
Introduction
Mathematical model
Objective function
Case description and modelling
Modelling the power-plant
Modelling the spot market
Improving the peak load contracts
Pricing the different PLCs
Modelling the demand response
Pricing the DR program
Summing up the different models
Results and discussion
Conclusions
References
Chapter-12---Business-opportunities-in-the-day-_2021_Mathematical-Modelling-
Business opportunities in the day ahead markets by storage integration: An application to the German case
Introduction
Trading mathematical model
Practical implementation issues
Data description
Results and discussion
Technical analysis of the trading model with BESS
Financial analysis of the trading model with BESS
Econometric analysis
Conclusions and policy implications
References
Chapter-13---The-integration-of-dynamic-demand-in-el_2021_Mathematical-Model
The integration of dynamic demand in electricity markets: Blockchain 3.0 as an enabler of microgrid energy ex ...
Introduction
Demand response, storage, electric vehicles and peer-to-peer (P2P) blockchain energy trading
Peer-to-peer (P2P) energy trading
Demand response, storage, electric vehicles and blockchain
Implementation level
Technical issues on blockchain, demand response and storage
Blockchain implementations applicable to energy systems
Ancillary services market (demand response-voltage support/reactive energy)
Blockchain demand management considerations and power system operation
Algorithmic representation of blockchain
Steady state and dynamic network constraints
Social dimension
Conclusions and future work
References
Chapter-14---Optimizing-CHP-operational-planning-for_2021_Mathematical-Model
Optimizing CHP operational planning for participating in day-ahead power markets: The case of a coal-fired CH ...
Introduction
Mathematical model
Objective function
Constraints
Feasible operation region
Thermal energy balance
Operation state of the CHP plant
Operation state of pulverized-coal fired boilers supplying steam to the extraction-condensing turbine
Start-up trajectory of pulverized coal-fired boilers supplying steam to the extraction-condensing turbine
Maximum and minimum limits of combined generation
Auxiliary boilers power output and fuel consumption
Auxiliary boilers power output limits
Must-run constraints of auxiliary boilers
Start-up and shut-down trajectories of auxiliary boilers
Thermal energy storage inventory balance
Thermal energy storage capacity limit
Thermal energy storage charge and discharge limits
Thermal energy storage operation mode
Storage thermal energy losses to the surroundings
Uniform water temperature in the thermal energy storage
Illustrative example
Computational results
Conclusions
References
Chapter-15---Statistical-analysis-of-power-flows_2021_Mathematical-Modelling
Statistical analysis of power flows based on system marginal price differentials between two power systems
Introduction
Methodology
Validation of the statistical analysis
Methodology application
Conclusions
References
Chapter-16---EW-Flex--A-decentralized-flexi_2021_Mathematical-Modelling-of-C
EW Flex: A decentralized flexibility marketplace fostering TSO-DSO cooperation
Introduction
The TSO-DSO coordination issue
The Energy Web Decentralized Operating System
Trust layer
Utility layer
Toolkit layer
EW Flex
EW Flex architecture
Decentralized vs centralized flexibility marketplaces
EW Core
Application registry
EW Flex platform
Conclusions
References
Further reading
Chapter-17---Forecasting-electricity-supp_2021_Mathematical-Modelling-of-Con
Forecasting electricity supply shocks: A Bayesian panel VAR analysis
Introduction
Data and sample
Empirical methodology
Results and discussion
Conclusions
References
Chapter-18---Formulating-and-estimating-an-ener_2021_Mathematical-Modelling-
Formulating and estimating an energy security index: A geopolitical review of quantitative approaches
Introduction
Conceptualizing energy security
Estimating energy security
The role of energy markets
Incorporating qualitative techniques
Weighting and aggregating components and dimensions
Using other indexes
Forecasting
Conclusions
References
Chapter-19---Assessing-the-Western-Balkan_2021_Mathematical-Modelling-of-Con
Assessing the Western Balkans power systems: A case study of Serbia
Introduction
Mathematical formulation
Objective function
Constraints
Electricity demand balance
Operating limits
Renewable energy production
Hydropower generation
Energy trading
Ramp limits
Time limits
Reserve limits
Reserve requirements
Case study
Results
Energy mix
Economic performance
Environmental performance
Reserve mix
Conclusions
References
Chapter-20---Evaluation-of-capacity-expansi_2021_Mathematical-Modelling-of-C
Evaluation of capacity expansion scenarios for the Hellenic electric sector
Introduction
Methodology
Results
Conclusions
References
Chapter-21---An-ex-ante-market-monitoring-and-reg_2021_Mathematical-Modellin
An ex-ante market monitoring and regulation mechanism for market concentration in electricity and natural gas ...
Introduction
Generic framework of the ex-ante market monitoring and regulation mechanism
Defining the relative markets
Supply side
Demand side
Comparing supply with demand side
Defining combination of market concentration in aggregate and disaggregate markets
Mathematical framework of the ex-ante market monitoring mechanism
Supply side
Estimation of Indicator 1
Estimation of Indicator 2
Estimation of Indicator 3
Estimation of Indicator 4
Demand side
Application in the Hellenic electricity market
Application in the electricity market
Supply side
Market monitoring of market concentration
Regulation of market concentration
Lignite disaggregate market
Large hydro disaggregate market
Natural gas disaggregate market
Renewables disaggregate market
Interconnections disaggregate market
Demand side
Application in the natural gas market
Conclusions
References
Index_2021_Mathematical-Modelling-of-Contemporary-Electricity-Markets
Index
A
B
C
D
E
F
G
H
I
J
K
L
M
N
O
P
Q
R
S
T
U
V
W
Y