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Why am I being charged VAT?
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Electricity Economics & Financial Analysis
A four day intensive, technical hands-on course in which attendees receive comprehensive instruction on the theory and practice of making price forecasts and assessing risk in the electricity generating industry.
Forward pricing and valuation in electricity generation is a four day intensive, technical hands-on course in which attendees receive comprehensive instruction on the theory and practice of making price forecasts and assessing risk in the electricity generating industry. After discussion of electricity markets around the world, the course moves to programming and model structuring, where attendees follow the lead of the instructor in building various analyzes of forward pricing and valuation issues. Exercises include analysis of supply and demand, modeling of capacity mix and capacity level optimization; construction of time series analysis for fuel prices loads and hydro generation; and, project finance analysis of merchant plant investments. As the course progresses, attendees apply risk assessment, option pricing, and valuation techniques in real world cases using an integrated model. In addition to building their own models, participants learn how to use fully developed models that incorporate sophisticated debt structuring, break-even analysis, contract pricing, time series equations and Monte Carlo simulation.
The course will cover:
- Learn practical tools to analyse a host of issues in electricity analysis including efficient tools to work with supply and demand data; creating flexible scenario and sensitivity analysis to evaluate power prices and marginal costs; effectively presenting short-term and long-term supply and curves; development of hydro analysis; Monte Carlo simulation and other issues.
- Create demand and supply models of electricity pricing that incorporates changes in fuel prices, new capacity, demand profiles, maintenance outages to measure hourly marginal cost and total generation cost.
- Study the structure of market designs around the world and simulate pricing strategies through evaluation of the California crisis and simulation exercises.
- Understand the relationship between capacity pricing, reliability, loss of load probability and reserve margins through extending the short-run supply and demand analysis and modelling outage cost with different capacity configurations.
- Model the economic value of different types of renewable resources in alternative markets including storage hydro, run-of-river hydro, wind and solar.
- Develop efficient ways to quickly compute the levelised electricity cost of different technologies using carrying charge factors and alternative financial models and use levelised cost analysis to develop screening models of optimal resources.
- Evaluate long-run marginal cost of electricity cost through simulating the value of different generating resources given load curves and simulate the effects of different capital costs, heat rates and fuel prices on the long-run marginal cost.
- Compute the effects of start-up costs, heat rate curves, and transmission constraints on the value of alternative plants and the price of electricity.
Day 1: Electricity Price Characteristics and Short-term Marginal Cost
1) Analysis of Electricity Price and Load Data in Different Markets Around the World
i. Definition of key terms – Marginal cost, load factor, efficiency, LCOEii. Importance of marginal cost concepts in evaluating PPA prices
iii. Marginal cost as underlying basis for studying electricity prices
iv. Understanding long-run and short-run marginal cost
b. Computation of Short-run cost in demand suppressed market
i. Heat rate and cost of diesel fuel
ii. Conversions and measurement of heat rate
iii. Variable cost versus fixed cost
c. Costs and Benefits of PPA Provisions
i. Cost of delay and benefits of delay
ii. Costs of outage and benefits of outage
iii. Costs and benefits of efficiency
iv. Participant case exercise on use of marginal cost
2) Data Analysis of Electricity – Part 1
a. Comparison of Prices in Different Markets
i. Commodity price data over time
ii. Analysis and summary of load data
iii. Sources for electricity price data
iv. Review and Presentation of electricity price data
v. Presentation of electricity price and load data for different time periods
b. Statistical Characteristics of Prices
i. Volatility in different time periods – hourly, daily, monthly, annual
ii. Mean reversion of electricity prices
iii. Price boundaries on electricity prices
iv. Comparison of electricity prices to stock prices, interest rates and other commodities
Day 2: Electricity Price Characteristics and Short-term Marginal Cost
a. Computation of Plant Value per kW in De-regulated Markets
v. Value per kW for hydro plant – run of river and storage with constrained energy
vi. Value per kW for coal plant through matching coal prices and heat rates with electricity price
vii. Value per kW for gas plant through matching gas prices and heat rates with electricity prices
viii. Value per kW for renewable energy
b. Monte Carlo Simulation Model of Electricity Using Time Series Models
ix. Theory of time series modelling and applicability to electricity
x. Model with volatility
xi. Model with volatility and mean reversion
xii. Including equilibrium prices in model
3) Short-term Marginal Cost of Electricity
a. Modelling of short-run energy cost
i. Review of supply curves in different markets
ii. Creation of supply curve from fuel cost and variable O&M
iii. Use of MATCH, INDEX and SMALL Functions
iv. Creation of step function for supply curve
v. Presentation of supply curve
b. Incorporation of renewable energy and hydro in short-run marginal cost
i. Adjustment of demand curve versus supply curve
ii. Run of river hydro
iii. Solar and time of day
iv. Wind and seasonal
v. Storage hydro with load duration curve
c. Incorporation of Demand Curve and Sensitivity Analysis
i. Demand curve with price elasticity
ii. Intersection of supply and demand
iii. Computation and presentation of short-run marginal cost for hour, day, week and multiple years
iv. Computation of energy generation cost for different time periods with different capacity expansion options
d. California Power Crisis Case Studyi. Review of supply and demand drivers
ii. Evaluation of market power
iii. Bidding game
Day 3: Continued Short-term Marginal Cost and Long-run Marginal Cost
e. Risk analysis for short-term cost marginal cost
i. Uncertainty and volatility in demand – working with demand curves
ii. Uncertainty and volatility in fuel cost
iii. Uncertainty in plant outages
iv. Uncertainty in hydro generation
v. Effects of uncertainty with different reserve margins
4) Long-run marginal cost and capacity prices
a. Discussion of alternative capacity cost frameworks
i. Price spikes and no price caps
ii. Administrative capacity uplifts and energy cost pricing
iii. Capacity price bidding
iv. Pros and cons of alternative models
v. Effects of alternative models on energy prices and addition of new capacity
b. Economic Theory of Customer outage cost and loss of load probability
i. Incorporation of demand response and demand elasticity into short-run marginal cost model
ii. Calculation and analysis of loss of load probability
iii. Computation of reserve margin through equating loss of load criteria with capital cost of peaker.
c. Theory of long-run marginal costi. Problem of short-run marginal cost and earning return on capitalii. Measurement of long-run marginal costs using peaker methodiii. Long-run marginal cost and levelized cost of alternative technologiesiv. Long-run marginal cost and the cost of interruptible ratev. Long-run marginal cost and the cost of customer outage
d. Computation of levelized cost for alternative technologies
i. Capacity cost database
ii. Seven factors that drive levelized cost
iii. Derivation of LCOE formula
iv. Importance of cost of capital in technology cost
v. Regional differences in cost of electricity
e. Carrying charge rates - traditional
i. Theory of carrying charge rates
ii. Computation of carrying charges using utility approach
iii. Calculation of levelized carrying charges with different tax, cost of capital and capital structure assumptions
iv. Incorporation of inflation in carrying charges
v. Analysis of levelized cost of electricity with different carrying charges
Day 4: Long-term Marginal Cost and Equilibrium Pricing
f. Computation of carrying charges using project finance modelling
i. Basic structure of project finance model
ii. Required IRR, debt financing and other assumptions for simple project finance model
iii. Building a basic project finance model with flexible construction periods, plant lives, tax depreciation methods and return assumptions
iv. Use of project finance model to compute carrying charges
v. Contrast use of project finance model and traditional model in deriving levelized cost of electricity.
vi. Enron Dabhol Case – 2
5) Equilibrium long-run price of electricity
a. Theory and importance of computing long-run cost
i. Relationship of price and cost in long-run
ii. Marginal cost with multiple efficient technologies
iii. Theory of capital recovery per kW
b. Screening Analysis
i. Creating model of capital cost, operating cost and capacity factor
ii. Computing optimal capacity factor for different fuel/capacity cost tradeoffs
iii. Optimal capacity factor for different units
iv. Capacity factor versus time on the margin
c. Integrated Marginal Cost Model for Evaluating Long-term Pricesi. General Structure – combining short-run cost models with value per kW
ii. Setting-up model with different capital costs, fuel costs and supply mix.
iii. Computation of energy value per KW and capacity value per KW for each unit.
iv. Simulation of clearing energy price with multiple units
v. Computation of optimal supply mix and resulting combined energy and capacity price.
d. Case Study of Supply and Demand – U.K. Market Crash
i. Sutton Bridge Discussion
ii. Changes in market structure
iii. AES Drax capital structure
iv. AES Drax financial analysis
e. Start-up costs, heat rate curves and minimum capacity in supply curve
i. Discussion of heat rate curves
ii. Equations for incremental and average heat rate curves
iii. Incorporation of heat rate curves and fleet of generation
iv. Day ahead scheduling and real-time dispatch
v. Volatility of day-ahead prices and real-time prices
f. Transmission constraints and energy prices
i. Theory of transmission constraints and prices from comparative advantage
ii. Transmission constraints in electricity versus transmission in oil, gas, food and other products
iii. Modelling of region by marginal cost with regional supply and demand
iv. Modelling transfers of capacity with alternative transmission constraints
v. Computing the value of transmission
vi. Policy issues associated with addition of transmission capacity
vii. Case study of transmission capacity additions
Our Tailored Learning Offering
Do you have five or more people interested in attending this course? Do you want to tailor it to meet your company’s exact requirements? If you’d like to do either of these, we can bring this course to your company’s office. You could even save up to 50% on the cost of sending delegates to a public course and dramatically increase your ROI.
If you want to run this course at a location convenient to you or if you want a completely customised learning solution, we can help.
We produce learning solutions that are completely unique to your business. We’ll guide you through the whole process, from the initial consultancy to evaluating the success of the full learning experience. Our learning specialists ensure you get the maximum return on your training investment.
We have a combined experience of over 60 years providing learning solutions to the world’s major organisations and are privileged to have contributed to their success. We view our clients as partners and focus on understanding the needs of each organisation we work with to tailor learning solutions to specific requirements.
We are proud of our record of customer satisfaction. Here is why you should choose us to help you achieve your goals and accelerate your career:
- Quality – our clients consistently rate our performance ‘excellent’ or ‘outstanding’. Our average overall score awarded to us by our clients is nine out of ten.
- Track record – we have delivered training solutions for 95% of worlds’ top 100 banks and have trained over 250,000 professionals.
- Knowledge – our 150 strong team of industry specialist trainers are world leading financial leaders and commentators, ensuring our knowledge base is second to none.
- Reliability – if we promise it, we deliver it. We have delivered over 20,000 events both in person and online, using simultaneous translation to delegates from over 180 countries.
- Recognition – we are accredited by the British Accreditation Council and the CPD Certification Service. In an independent review by Feefo we scored 96% on service and 95% on product
BiographyEd has created innovative forward pricing, productivity measurement and investment valuation software for consulting clients throughout the United States. He has taught energy economics and finance throughout the world, and formulated significant government policy and corporate strategy in the U.S. His consulting clients include investment banks, commercial banks, research institutions and government agencies on a wide variety of complex valuation and advisory matters. He has constructed a unique framework for electricity price forecasting and valuation using production cost modelling techniques combined with option price theory and Monte Carlo simulation. He is also an adjunct professor at leading University where he teaches courses in microeconomics. Along with his practical experience that covers a multitude of major advisory projects, he has taught specialised courses in financial modelling, electricity pricing, option valuation, mergers and acquisitions and contracting to investment banks, commercial banks, industrial corporations and electric utility companies. He was formerly Vice President at the First National Bank of Chicago where he directed analysis of energy loans and also created financial modelling techniques used in advisory projects. He has used the models in providing expert testimony on subjects ranging from capital structure to investments in multi-billion dollar nuclear plants to complex valuation of new investments. He received an MBA degree specialising in econometrics (with honours) from the University of Chicago and a BS degree in finance from the University of Illinois (with highest university honours). He has written many articles and is in the process of completing a textbook on valuation of electricity assets.
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