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Electricity Economics & Financial Analysis

Understand price forecasts & assess risk in the electricity industry
  • 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

    a. Introduction
    i. Definition of key terms – Marginal cost, load factor, efficiency, LCOE
    ii. 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 Study
    i. 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 cost
    i. Problem of short-run marginal cost and earning return on capital
    ii. Measurement of long-run marginal costs using peaker method
    iii. Long-run marginal cost and levelized cost of alternative technologies
    iv. Long-run marginal cost and the cost of interruptible rate
    v. 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 Prices
    i. 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 – 10/10 of the world’s largest banks have chosen us as there training provider and we have delivered training across the largest banks and have trained over 25,000 professionals.
    • Knowledge – our 100+ 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 25,000 events both in person and online, using simultaneous translation to delegates from over 99 countries.
    • Recognition – we are accredited by the British Accreditation Council and the CPD Certification Service. In an independent review by Feefo we scored 4.2/5 on service and 4.7/5 on Coursecheck
This course can be run virtually online or as an in-house, tailored learning solution


  • Ed Bodmer


    Ed 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.



The course will take place at a Central London hotel.

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