Electricity Economics & Financial Analysis

Euromoney Learning Solutions

Euromoney Learning Solutions

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About the course

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.

Agenda

Day 1: Electricity Price Characteristics and Short-term Marginal Cost

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, 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

Experts

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....

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Electricity Economics & Financial Analysis at Euromoney Learning Solutions

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