Intro to electric power

Prof. Richard Sweeney

Overview of next few lectures

• Today:
  • Overview of technology and core engineering constraints.
  • How electricity markets work
  • Start of electricity market game
• Lecture 2: Market power.
• Lecture 3: Long run investment
  • Knowledge check

Lecture 1: Electric Power Background

• How we generate electricity
• What’s special about electricity?
• Goals for power markets and how they work

Electricity makes up 42% of US energy demand

• But eventually we want to electrify as much as possible.
• As such we will spend most of our time in this class talking about electricity.

Some terminology: Watts vs watt-hours

• A watt (W) is an instantaneous measure of the rate of power flow (equal to 1 joule per second)

• A watt-hour (Wh) refers to one watt of power flowing for an entire hour. This is what you see on your electricity bill.
  • Avg US household consumes 10,000,000 Wh per year.
• Common units of aggregation are kilowatt-hours (kWh = 1000 Wh) and megawatt-hours (MWh = 1,000,000 Wh)

• The capacity of a power plant in is denoted in megawatts (MW). This is the amount of power it can produce when operating optimally at any moment.

• If a 1 megawatt (MW) plant operates optimally for 1 hour, it creates 1 megawatt-hour of electricity (MWh).

  • This would power approximately 800 homes.

Generation Technology

Most electric power generators driven by a turbine

Source: EIA

Coal fired power plant

Source and more info here.

• Average plant is around 600 MW
• C02 emissions of 2.25 lbs per kWh

Natural gas power plant

Source and more info here

• Average plant is around 300-500 MW
• C02 emissions of 0.91 lbs per kWh. (~1/2 coal)

Nuclear power plant

Source and more info here.

• Average plant is around 2,000 MW
• Can still impose massive social costs (Fukushima)
• Waste needs to be stored / processed

Hydroelectric power plant

Source and more info here

• Sizes varies a lot.
• Large plants can be very ecologically disruptive.

Wind turbines

• Average turbine around 3 MW.
• Offshore turbines of 20 MW on the horizon.

Solar thermal plant

Solar photovoltaic (PV) is the exception

Average residential system is 0.005 MW

Some questions

• Which technologies should we use more / less of in the short run?
• What plants should we build more / less of in the long run?
• How does the market make these decisions?
• Is the market mix economically efficient?

Grid

Overview of electric power systems

Source: Wikipedia

• Power plants often located far a way
  
• Transmitting lots of power requires high voltage (dangerous)
• Needs to be “stepped down” to lower voltage to get to customers.

Electricity is different from other goods

• Generators don’t create electrons, they send waves across existing electrons on the grid
  • Flow reverberates to balance differences in potential energy across nodes (Kirchoff’s law)
• Analogy: Electricity like a pond where demanders draw water, suppliers put more in
  • Cannot track “electricity” across the grid
  • From consumer’s perspective, electricity generation is totally undifferentiated (ie it does not matter how it was produced)

Challenge: Supply and demand have to balance perfectly at every point in space and time

• Too much supply/ too little demand causes the frequency to increase.
  • Our appliances are designed to expect a very specific voltage. Even minor deviations can damage them.
  • Large deviations can cause explosions and fires on grid equipment.
  • Implication: Can’t just bring more power unless you know someone wants it.
• Too little supply/ too much demand and the frequency drops.
  • This can lead to a blackout, which precludes anyone from consuming electricity.
  • Contrast that with a typical market (Avocado example)
  • Implications: In order for someone to increase electricity use, a power plant has to concurrently increase supply.

Goal #1 for power grid: Keep the lights on

Demand

Balancing supply and demand is nontrivial because demand varies considerably across time

• When do you think we use more electricity over the course of a day? Year?

Example from New England

Challenge: Electricity not (cheaply) storable

• Many markets have seasonal / fluctuating demand (fireworks)
• Solution is often to produce at a nearly constant rate, and store the good
• Historically, energy storage has been inefficient or prohibitively expensive
  • This is changing! We will talk about batteries in a few weeks

Varying demand and limited storage means we need more plants at some times than others

• Supply and demand must balance at every point in time.
• Implication: There is a plant somewhere that only produces power during the highest demand hour of the year!
• Which plant should that be?

Efficient Dispatch: Use lowest MC plants first

Example dispatch curve, Source: EIA

Electric Power Markets

How deregulated generation markets work

• Private investors put up (a lot of) capital to build a power plants, at their own risk.
  • They sell power to earn revenue, but return is not guaranteed.
• An Independent System Operator (ISO) is given full control over balancing the grid.
  • Have to approve generation requests (solves balancing problem)

Every hour the the ISO holds an [auction]

• Generators tell the ISO the minimum price they’d need to be to produce power for next 15 mins.
• ISO “dispatches” cheapest generators first until demand is satisfied.
• Every generator that produces gets paid the marginal (ie highest clearing) bid.
  • This is called a uniform price auction.

Example

• Consider a market with following tech:

Fuel	Capacity (MW)	Marginal Cost
Hydro	10	0
Coal	30	40
Gas	20	60

Off-peak equilibrium

Demand = 35 Market clearing price P = 40 (coal’s MC).

Fuel	Cap.	MC	Q	P	Revenue	Cost	Profit
Hydro	10	0	10	40	400	0	400
Coal	30	40	25	40	1000	1000	0
Gas	20	60	0	0	0	0	0

Notes: Hydro earns inframarginal rents; Coal is marginal and breaks even.

Peak equilibrium

Demand = 55 MW Market clearing price P = 60 (gas’s MC).

Fuel	Cap.	MC	Q	P	Revenue	Cost	Profit
Hydro	10	0	10	60	600	0	600
Coal	30	40	30	60	1800	1200	600
Gas	20	60	15	60	900	900	0

Notes: Gas is marginal and breaks even; Hydro and Coal earn inframarginal rents.

Takeaways

• Market price equals the marginal unit’s marginal cost.
• Inframarginal profit: \((P - MC_j) \times \text{MWh}_j\).
• Moving from off-peak to peak raises market price from 40 to 60, expanding inframarginal rents.

Energy Market Game

Based on California electricity markets

• Goals:
  • Understand how bidding and profits work in deregulated markets
  • Explore possibilities for market power
  • Study how a carbon tax works in this market (next week)
• More info:
  • Player guide
  • Game Concepts

7 Generation companies (full portfolio)

Each period teams submit their bids

ISO arranges those bids into a supply curve

4 Demand periods

Getting started

• Take a minute to figure out the best way to keep track of things with your team
  • It may be useful to start a new (separate) google sheet
    
• Go to the Google sheet I emailed.
  • Add your name and email to the appropriate team.
• Click on your team’s link for the “base game 1 – Intro”
• Go to the “Game Conditions” and take a look at your genco portfolio (also in the “Plant List” tab in the google sheet)
  • How many plants of each type do you have? 
• Copy these over to your new google sheet. What are their capacities (MW)? what are their marginal costs? (“fuelcost” + variable o&m ”varom”)
• Go to the “place bids” tab, and confirm the default bids match these marginal costs.

Example game (Base Game 1)

• Leave bids as is (= MC)!
• I am going to solve the game, and let’s walk through each period in turn.

For each period, make note of:

• Which of your plants produced power? (were dispatched)
• What price did they get?
• What profits did they earn?

Playing for real

• Work with your team to set bids for all four periods of the “Day 1” game on the “At Home” sheet
• Goal: Earn as much profit as possible over the day.

You’ll play this game 4 more times

• Bids due:
  • Day 1: Friday at 5 pm
  • Day 2: Monday at 5 pm
  • Day 3: Tuesday at 10 pm
  • Day 4: Wednesday at 10 pm
• At these times I’ll solve the game, and you’ll be able to see your profits.
• The team that increases profits the most relative to the baseline, in percentage terms, will win a prize.

Lecture 3: Long run investment

From short run to the long run

So far we have been studying outcomes conditional on the set of plants available.

Questions for today

1. Why do we have this mix of technologies?
2. What is the “cheapest” technology?

Review your plant performance so far

• Which of your plants produced the most power?
• Which plants made the most money?
• Did any plants lose money?
• If you could get rid of one of your plants, which would it be?

Power production involves both fixed and variable costs

Which technology is cheapest?

If a plant has capital cost \(K\) and variable cost \(v\) (per hour), and it runs for \(q\) hours, it’s total lifetime cost \(C\) is

\[C = K + v*q\]

Dividing \(C\) by lifetime production \(q\), we get the average cost per unity of electricity over the life of the asset, called the Levelized Cost of Energy (LCOE)

\[LCOE = K/q + v\]

[note typically we want to discount]

This is the minimum average price the plant must be paid in order to cover costs.

Which energy tech is “cheapest”?

The answer depends on how often the asset will be used.

Why do we have any gas plants? Why build something that only runs half the time?

What does LCOE miss?

• If we want to know what technology is “best”, can we just look at LCOE?
• What important factors are not included in LCOE?

• Externalities (eg pollution)
• Grid integration costs (eg need for backup, transmission)
• Risk / Volatility
• Other factors (eg land use, water use, social acceptance)

In many studies, renewables look cheapest

Why don’t renewables just take over the grid? To increase the share of renewables on the grid, do they just need to be cheaper than fossil LCOE?

Module 1 wrapup

• Electricity is an undifferentiated good, produced by very differentiated technologies
• Supplied in an environment with important engineering constraints
• In the short run, markets allocate production to plants that bid the lowest.
• Firms earn money by being “inframarginal”
• If markets are competitive, this will keep lights on at lowest private cost
• In long-run, plants need to be paid at least their LCOE to make money.
• Next up: social cost

Backup