The document summarizes the transition to smart grids, including changes to the roles of consumers, utilities, vendors, and governments. It discusses the current state of smart grid development and open issues remaining, such as fully replacing old equipment and establishing new regulatory frameworks. Technology trends in demand response, distribution automation, and reliability are also reviewed. Financial analysis of utilities includes examining historical growth rates, cost structures, and valuation approaches for smart grid projects using real options theory. Examples of smart grid development in Russia are provided, noting both challenges and opportunities for the transition.

1. Sergey Syntulsky
Smart grid: technology and market
evidence

2. Smart grid ecosystem transition
Current state Target state
(Mostly) price and volume-
taking consumer
Prosumer with internal
optimization
Utility as unilateral service
provider
Utility as adaptive network
of prosumers
B2B utilities equipment
vendors
B2B + B2C vendors and
lessors
Regulation of power system
technical and economic
issues
Regulation of information
exchange (privacy,
interoperability) and pricing
of information/control
services

3. Current state
Role Current state
Consumers Demand response mostly for large consumers, PV
devices for household consumption, AMI, time-based
rates. But hard to engage in complicated cooperation,
need to be seamless.
Utilities Economic stimuli are not aligned enough. Later timing
option benefits (no exponential growth for early
adopters). It is easier to force new hardware installation,
but harder to encourage new business-processes.
Vendors Those who can work in emerging business model
achieve exponential growth, others have moderate
margins.
Governments Face transition problems: stranded assets, subsidies for
early adopters, problems with regulation for both old
and new ecosystem.

4. Open issues
 Full equipment replacement :
 Move to advanced metering and control devices
 Move to distributed generators
 Storage, consumer devices, electrical cars
 Mechanism design, proper stimuli for each side:
 New technical and economic regulation (information
exchange protocols, market model)
 Good patterns for small (esp. household) consumers
involvement
 Right risk/return for private funding

5. Plan
 Technology changes
 Bi-directional communications with consumer (AMI)
 Intermittent (solar and wind) and cheap balancing
(gas and biofuel) power generation
 Demand response/energy efficiency
 Distribution automation
 Moderate increase in reliability
 Financial data perspective
 Valuation of smart grid projects
 Some cases in Russia

6. Technology trends

7. Stable peak loads during last 10
years
*EIA peak load statistics

8. Demand response
 ~700 000 customer-based devices under SGIG
prpgram (mostly direct load control devices and
controllable thermostats)
 Customers enrolled in time-based pricing:
*chart from smartgrid.gov

9. Distribution automation
 ~8000 automated feeder switches installed (5%
of distribution circuits) in SGIG (smart grid
investment grant) program
 =>50% shorter and 11%-49% less frequent
outages
 Utilities data analytics market for utilities and
regulators is expected to grow 33% per year
 Cybersecurity plan requirements for subsidized
projects

10. Reliability
*Charts from Larsen, LaCommare, Eto, Sweeney, Assessing Changes in reliability of the US Electric power
system, 2015

11. Plan
 Technology changes
 Financial data perspective
 Changes in utilities cost structure
 Historical growth of sales and earnings
 Fundamental growth rate
 Sales/asset ratio
 ETF historical returns and PEG
 Valuation of smart grid projects
 Some cases in Russia

12. Utilities cost structure change
*EIA utilities expenses report

13. Historical growth
 High sales growth in
equipment sector
(>market)
 Small growth in utilities
and power sectors
(<market)
 Strong margin growth
relative to weak sales
growth in utilities and
power sectors
*data published by Aswath Damodaran:
http://people.stern.nyu.edu/adamodar/New_Home_Page/dataarchived.html

14. Fundamental growth rate = ROC *
reinvestment rate

15. Reinvestment rate (NetCapEx/EBIT)
NetCapEx = CapEx - Depreciation

16. Return on capital (EBIT/Assets)

17. Sales/assets ratio

18. Net investments / sales by industry

19. POWERGRID/utilities/power ETF
behavior (current time data)

20. Price/Earnings/Growth
*data published by Aswath Damodaran:
http://people.stern.nyu.edu/adamodar/New_Home_Page/dataarchived.html

21. Plan
 Technology changes
 Financial data perspective
 Valuation of smart grid projects
 Smart grid as real option
 Generator valuation
 Smart grid valuation
 Some cases in Russia

22. Real option characteristics
 Some of smart grid value is delivered in straight-
forward way:
 Reliability/QOS increase
 Reduction in losses due to better dispatch
 Decrease in capacity reserves needed
 Other part of smart grid value is an option:
 To build new generation (small scale and on consumer
side)
 To establish new pricing and shared control schemes
 While first part can be estimated under existing
regulatory framework, second is non-trivial

23. Example
 Consider option:
 to build small-scale gas-fired power plant on
consumer side
 connect it to the grid,
 sell excess energy to the grid for years.
 Its value depends on gas and power market
prices
 Gas power fired plant can be valued as spark
spread option

24.  t – hour
 Vt – consumption
 C – generator capacity
 K – efficiency coefficient
 Gt – gas price
 Xt – electricity price
 f – price of electricity
consumed from grid
 g – price for selling
electricity
Example: generator valuation

25. Example: smart grid valuation
 Cost – cost function to build generator with capacity
C
 Build 2D tree:
 1st dimension – long-term gas price
 2nd dimension – long-term electricity price

26. Plan
 Technology changes
 Financial data perspective
 Valuation of smart grid projects
 Some cases in Russia
 Smart grids in Russia: pros and cons
 UIAS FTS of Russia regulation approach
 Utilities automation issues

27. Smart grids in Russia: cons
 Some factors are against immediate smart grid
development:
 Low demand for non-hydro renewables (cheap gas)
 Low household tariffs (cross-subsidies)
 Low median household income (will not invest in
smart appliances)
 Access to cheap financing is limited for small
entities
 Poor contracts enforcement (incumbent can
preserve market share)

28. Smart grids in Russia: pros
 Some new initiatives like virtual power plant and
smart grid in Crimea, not enough information
 On opposite there are some markets with good
economic potential:
 Wind and fossil-based microgrids for power supply of
isolated or remote sites (like mines and related housing)
 Insolated territories of Northern Caucasus with
extremely high transmission expenses
 Large energy-intensive consumers (including world
largest district heating systems, water supply and
disposal)
 Smart grid creation seems to be less relevant task
than power grid automation and quantitative decision
support

29. UAIS scheme
SCADA and
metering system
ERP and
accounting
Computer-aided
design systems
Balance management system
Investments planning
Abnormal situations (losses,
outages) root cause analysis
Regulatory accounting and
cost allocation
Regional
regulatory
bodies
Holding
Federal
regulatory body
Cross-
validation
between grids
Forecasting and planning next
year balance

30. Scheme of typical contracts between
power grids in single region

31. Issues with utilities grid automation
 Technological state of different power grid parts can
be very different, often managed on different
platforms
 Accounting, CAD and metering entities are often not
mapped
 No explicit topology information is combined with
metering data, unable to localize losses
 Data exchange between power grid (operates
metering) and energy retail (billing function) is poorly
formalized (no single protocol)
 Most value can be gained after full data model
consolidation, it is time-consuming and expensive
 Hard to prove value of analytical work to regulator
under weak institutions

32.  High corruption level leads to:
 high abnormal power losses (stealing of energy)
 unnecessary investments,
 Projects, that are dedicated to prevent such
things can face opposition
Issues with utilities grid automation