The Utility of the Future (Massachusetts Institute of Technology)

How the utility of the future will be?

2. The MIT Utility of the Future Study
The power sector is evolving once
again…

3. In light of these changes, the MIT Energy
Initiative examined the future of the
provision of electricity services
Examine how distributed energy resources • (DERs)
and information and communication technologies (ICTs) are
creating new options for the provision of electricity
services…
•…with a focus on the USA & Europe over the next decade &
beyond
To make • policy and regulatory recommendations…
… •to facilitate an affordable, reliable, low-carbon electricity
system that encourages efficient utilization of all resources,
whether centralized or decentralized

4. Principal Investigators
Ignacio Pérez-Arriaga,Professor, Electrical Engineering,
Institute for Research in Technology ComillasPontifical
University; Visiting Professor, MIT Energy Initiative
Christopher Knittel, George P. Shultz Professor of
Applied Economics, Sloan School of Management, MIT;
Director, Center for Energy and Environmental Policy
Research, MIT
Project Directors
RaananMiller, Executive Director,Utility of the Future
Study, MIT Energy Initiative
Richard Tabors, Visiting Scholar, MIT Energy Initiative
Research Team
AshwiniBharatkumar,PhD Student, Institute for Data,
Systems, and Society, MIT
Michael Birk, SM, Technology and Policy Program (’16),
MIT
Scott Burger, PhD Student, Institute for Data, Systems,
and Society, MIT
JoséPablo Chaves, Research Scientist, Institute for
Research in Technology, ComillasPontifical University
Research Team (continued)
Pablo Duenas-Martinez, Postdoctoral Associate, MIT
Energy Initiative
Ignacio Herrero, Research Assistant, Institute for
Research in Technology ComillasPontifical University
Sam Huntington, SM, Technology and Policy Program
(’16), MIT
Jesse Jenkins, PhD Candidate, Institute for Data,
Systems and Society, MIT
Max Luke, SM, Technology and Policy Program (’16),
MIT
RaananMiller, Executive Director, Utility of the Future
Study MIT Energy Initiative
Pablo Rodilla,Research Scientist, Institute for Research
in Technology ComillasPontifical University
Richard Tabors, Visiting Scholar, MIT Energy Initiative
Karen Tapia-Ahumada, Research Scientist, MIT Energy
Initiative
Claudio Vergara, Postdoctoral Associate, MIT Energy
Initiative
Nora Xu, SM, Technology and Policy Program (’16), MIT
The MIT Utility of the Future Study Team

5. Robert Armstrong, Director, MIT Energy Initiative
Carlos Batlle,Research Scholar, MIT Energy Initiative;
Professor, Institute for Research in Technology, Comillas
Pontifical University
Michael Caramanis, Professor of Mechanical
Engineering and Systems Engineering, College of
Engineering, Boston University
John Deutch, Institute Professor, Department of
Chemistry, MIT
TomásGómez,Professor, Director of the Institute for
Research in Technology, ComillasPontifical University
William Hogan, Raymond Plank Professor of Global
Energy Policy, John F. Kennedy School of Government,
Harvard University
Steven Leeb, Professor, Electrical Engineering &
Computer Science and Mechanical Engineering,
MITRichardLester,Associate Provost and Japan Steel
Industry Professor of Nuclear Science and Engineering,
Office of the Provost, MIT
Leslie Norford, Professor, Department of Architecture,
MIT
John Parsons,Senior Lecturer, Sloan School of
Management, MIT
Richard Schmalensee, Howard W. Johnson Professor of
Economics and Management, Emeritus
Dean, Emeritus, Sloan School of Management, MIT
Lou Carranza, Associate Director, MIT Energy Initiative
Stephen Connors, Director, Analysis Group for Regional
Energy Alternatives, MIT Energy Initiative
Cyril Draffin, Project Advisor, MIT Energy Initiative
Paul McManus,Master Lecturer, QuestromSchool of
Business, Boston University
Álvaro Sánchez Miralles, Senior Associate Professor,
Institute for Research in Technology, ComillasPontifical
University
Francis O’Sullivan, Research Director, MIT Energy
Initiative
RobertStoner, Deputy Director for Science and
Technology, MIT Energy Initiative
Faculty Committee
Research and Project Advisors

6. Chair: Phil Sharp, President, Resources for the Future
Vice Chair: Richard O’Neill,Chief Economic Advisor,
FERC
Janet Gail Besser, Executive Vice President Northeast
Clean Energy Council
Alain Burtin, Director, Energy Management, EDF R&D
Paul Centolella,President, Paul Centolella& Associates
LC, Senior Consultant, Tabors CaramanisRudkevich
Martin Crouch, Head of Profession for Economists and
Senior Partner, Improving Regulation, Ofgem
Elizabeth Endler, Research Program Manager, Shell
International Exploration & Production (US) Inc.
Phil Giuidice, CEO, President, and Board Member,
AmbriInc.
Timothy Healy, CEO, Chairman and Co-founder,
EnerNOC
Mariana Heinrich, Manager, Climate & Energy, World
Business Council for Sustainable Development
Paul Joskow, President and CEO, Alfred P. Sloan
Foundation, MIT Professor Emeritus
Melanie Kenderdine, Director of the Office of Energy
Policy and Systems Analysis and Energy Counselor to
the Secretary, U.S. Department of Energy
Christina La Marca, Head of Innovation, Global
Thermal Generation, Enel
Alex Laskey,President & Founder, Opower
Andrew Levitt, Sr. Market Strategist,
PJM Interconnection
Luca Lo SchiavoDeputy Director, Infrastructure
Regulation, Italian Regulatory Authority for Electricity,
Gas and Water (AEEGSI)
Gary Rahl, Executive Vice President, Booz Allen
Hamilton
Mark Ruth, Principal Project Lead, Strategic Energy
Analysis Center, National Renewable Energy Laboratory
Miguel Sánchez-Fornie, Director, Global Smart Grids,
Iberdrola
Manuel Sánchez-Jiménez, Team Leader, Smart Grids,
European Commission
Laurent Yana, Director Advisor of Global Bus,
Group Strategy Division, Engie
Audrey Zibelman, Chair, New York State Public
Service Commission
Advisory Committee

7. Consortium Members
Paul & Matthew Mashikian

8. “L'avenir, tu n'as point à le prévoir mais à le permettre”
Citadelle, Antoine de Saint-Exupéry, 1948
“The future, you do not have to foresee it,
but to enable it”

9. 1.A frameworkfor an efficient and evolving
power system
2.Insightsinto the value of Distributed Energy
Resources
Presentation contents

10. The MIT Utility of the Future Study
A framework for an efficient and
evolving power system
1. An Efficient System of Prices and Regulated
Chargesfor Electricity Services
2.Improved Incentives for Regulated Distribution
Utilities
3. Restructuring Revisited: Electricity Industry
Structure in a More Distributed Context
4. Updating Short-and Long-Term Electricity
Market Design

11. 1. An Efficient System of Prices and
Charges for Electricity Services

12. Expanding choice and new competition
requires improved rate design

13. The MIT Utility of the Future Study
Towards a comprehensive and efficient
system of prices and charges…
The best way to put all resources
on a level playing field and achieve
efficient operation and planning
(and thus more affordable electricity)
is to dramaticallyimprove prices and
regulated charges for electricity services.

14. 1357911131517192123
?
1. Ensure that all prices and charges are
non-discriminatory, technology neutral,
and symmetrical
Electricity rates should be based only on the injections and
withdrawals of electric power. This requires the use of improved
metering infrastructure.

15. 2. Progressively improve the granularity
of price signals with respect to both time
and location
Spatial granularity
Temporal granularity
Distributionnodal LMPs
(DLMPs, real & reactive)
Intermediate DLMPs
(substation/zonal/other)
Wholesale LMPs +
distribution losses
Wholesale nodal LMPs
Wholesale zonal LMPs
Real-time
spot price
Day-ahead
hourly price
Critical peak
pricing
Time-of-use
pricing

16. 3. Implement forward-looking peak-
coincident network charges and scarcity-
coincident generation charges to align
consumer decisions with system costs
0,00
0,25
0,50
0,75
1,00
1,25
1,50
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
$/kWh
Hour
Energy charge Generation capacity chargeNetwork capacity charge

17. 4. Allocate residual network and policy
costs without distorting efficient
incentives

18. 5. Carefully consider which costs are
included in fixed electricity tariffs to
avoid inefficient grid defection
Grid defection
costs
Grid defection
savings
Electricity Tariff
Components

19. Questions etc.
6. Address distributional concerns
without sacrificing efficient incentives
that reduce costs for everyone
1.Cross-subsidies: Lump-sum bill credits or
surcharges can restore desired cross-subsidies
between high and low cost of service areas
2.Bill stability: Pre-paymentsand hedging
arrangements can address bill variability
3.Low income support: need-based assistance
programs can replace implicit (and imprecise)
subsidies in volumetric rates

20. 2. Improved Incentives for
Regulated Distribution Utilities

21. The MIT Utility of the Future Study
1. Reward utilities for cost-savings
Time
$
1
st
regulatory period 2
nd
regulatory period 3
rd
regulatory period
?
Realized cost savings
(shared between utility
& ratepayers)
Multi-year revenue trajectory
Realized utility expenditures

22. The MIT Utility of the Future Study
2. State of the art regulatory tools to
reduce information asymmetry &
manage uncertainty
Incentive• -compatible menu of contracts to
induce accurate utility forecasts and minimize
strategy behavior
Engineering• -based reference network models to
equip regulators for forward-looking benchmarks
and analyze uncertainty scenarios
Automatic adjustment mechanisms to account •
for forecast errors
See Jenkins & Pérez-Arriaga(2017), “Improved Regulatory Approaches for the Remuneration of Electricity
Distribution Utilities with High Penetrations of Distributed Energy Resources,” The Energy Journal 38(3): 63-91

23. The MIT Utility of the Future Study
3. Put capital investment and operational
expenditures on an even footing
CAPEX OPEX

24. The MIT Utility of the Future Study
Reduction in average outage duration in Italy following
implementation of performance incentives for continuity of supply
4. Outcome-based performance
incentives
Total annual service
interruptions per customer
falls from more than 180 min
to roughly 60 min
Average cost per customer:
less than €2.5 per year

25. The MIT Utility of the Future Study
5. Incentives for long-term innovation
•Core remuneration incentives reward behavior
that reduces costs or improves performance
within the regulatory period(e.g. a few years)
•For utilities to engage in longer-term innovation,
regulators must establish appropriate incentives
•Accelerate investment in applied R&D,
demonstration projects, and learning about
capabilities of novel technologies and practices
•The goal: ensure utilities are cost-efficient not
just in the short-term but in the long-term as well

26. 3. Electricity Industry Structure in a
More Distributed Context

27. The MIT Utility of the Future Study
1. Three critical functions (and a fourth?)
System
Operator
Market
Platform
Network
Provider
Data hub?

28. The MIT Utility of the Future Study
2. Carefully assign responsibility to
minimize potential conflicts of interest
Structural reform to establish financial independence between platform
functions and competitive market activities preferable (from a textbook
perspective), but restructuring incurs costs and may be challenging in practice
Retailing /
aggregation
DER sales /
ownership
Generation
ownership
System
Operator
Market
Platform
Network
Provider
Data hub
Platform functions Market activities

29. The MIT Utility of the Future Study
2. Carefully assign responsibility to
minimize potential conflicts of interest
Retailing /
aggregation
DER sales /
ownership
Generation
ownership
System
Operator
Market
Platform
Network
Provider
Data hub
If financial independence between regulated and market activities cannot be
established, strict regulatory oversight and transparent mechanisms for
services must be implemented
Regulated activities Market activities

30. 4. Updating Short-and Long-term
Electricity Market Design

31. The MIT Utility of the Future Study
1. Enable wholesale market transactions
to be made closer to real time
This rewards flexibility and incentivizes improves •
forecasting and balancing

32. The MIT Utility of the Future Study
2. Enable new resources to play in
existing and emerging markets
•Updatewholesale market rules (such as bidding
formats) to reflect the operational constraints of new
resources

33. The MIT Utility of the Future Study
3. Align reserves & energy markets &
establish the flexibility requirements for
participation
Energy prices should reflect the increased probability of •
scarcity events as reserves are dispatched0
20
40
60
80
Baseload
Midload
Peaker
1 2 3
Optimal capacity mix
[GW
]
0 2,0004,0006,0008,00010,00012,000
Operating reserve level [MW]
0
2,000
4,000
6,000
8,000
10,000
Operating reserve
value
[$/MW/h]
1 2 3

34. The MIT Utility of the Future Study
4. Minimize the interference of support
mechanisms for clean technologies in
electricity markets
•Production-based subsidies distort marginal incentives
and can cause undesired outcomes
Frequency of 5-minute negative price spikes in CAISO

35. Insights on the Value of Distributed
Energy Resources

36. The MIT Utility of the Future Study
Distributed resources are not unicorns,
but they do provide locational services
1.The value of a distributed energy resource is highly dependent
on the specific location of that resource in the power system.
2.“Locational value” can vary dramatically within a given power
system. Efforts to define a single“value of solar” etc. will prove
futile.
3.The marginal value of DERs can decline rapidly as locational
value is exhausted.
4.Economies of scale still matter. Smaller isn’t always better.

37. The MIT Utility of the Future Study
1. Distributed resources create value by
providing locational services
Locational Services:
•Energy, network capacity margin,
network constraint mitigation,
reliability, etc.
Non-Locational Services:
•Firm capacity, operating reserves, CO
2
emissions reduction, etc.

38. The MIT Utility of the Future Study
2. Locational value can be meaningful,
but it varies dramatically within a power
system
0,1% 0,1%
8,4%
50,4%
26,2%
7,3%
2,3%
0,9% 0,4% 0,4% 0,5%
2,9%
<1 1-1011-2021-3031-4041-5051-6061-7071-8081-9091-100>100
USD per MWh
Distribution of 2015 Average Nodal LMPs in PJM
More than three quarters of nodes between $21-40/MWh
Approximately 3 percent of nodes
with very high locational value,
3-10 times the average

39. The MIT Utility of the Future Study
3. Marginal locational value can be
rapidly diminishing
Marginal value of distribution network losses avoided by distributed solar PV as
penetration increases (Texas ERCOT Example)
0%
5%
10%
15%
20%
25%
0% 5% 10% 15% 20% 25% 30% 35%
Production
-
Weighted Average
Marginal Losses Avoided by PV per MWh
Penetration Level as Percent of Annual Energy from Distributed Solar PV
3% Avg Distribution Losses 9% Avg Distribution Losses
Locational value “premium” from distribution loss
avoidance may be 6-19% of average wholesale LMP
for the first few PV systems installed, but falls
steadily as PV penetration increases.

40. The MIT Utility of the Future Study
4. Economies of scale still matter
Estimated economies of unit scale for fixed-tilt U.S. solar PV systems:
Annual cost of ownership in 2015 and projected for 2025
$0
$50
$100
$150
$200
$250
$300
$350
$400
10-100 MW
1-2 MW 1-10 kW
10-100 MW
1-2 MW 1-10 kW
10-100 MW
1-2 MW 1-10 kW
10-100 MW
1-2 MW 1-10 kW
Capital annuity and fixed O&M
($1,000/MW
-
yr) Incrementalunit cost relative to
10-100 MW system
2015 2025
(high cost estimate) (medium cost estimate) (low cost estimate)

41. The MIT Utility of the Future Study
5. High locational value can outweigh
distributed incremental costs…
$0
$20
$40
$60
$80
$100
$120
$140
$160
$180
Locational
energy value:
transmission
Locational
energy value:
distribution
losses
Conservation
voltage reduction
Network
investment
deferral
Generation
capacity
premium
ReliabilityTotal locational
value
1-2 MW system1-10 kW system
Average value per
MWh
produced
84.7
58.4
148.7
24.0
5.6
11.1
41.2
2.9 0.0
Comparison of locational value and incremental unit costs for solar PV systems:
Long Island, New York example, “high value” case
Distributedopportunity costs

42. The MIT Utility of the Future Study
6. But not always. Smaller is not always
better
$0
$20
$40
$60
$80
$100
$120
$140
$160
$180
Locational
energy value:
transmission
Locational
energy value:
distribution
losses
Conservation
voltage reduction
Network
investment
deferral
Generation
capacity
premium
ReliabilityTotal locational
value
1-2 MW system1-10 kW system
Average value per
MWh
produced
7.9
61.8
158.6
2.3
3.1
1.7 0.0 0.9 0.0
Comparison of locational value and incremental unit costs for solar PV systems:
Mohawk Valley, New York example, “average value” case
Distributedopportunity costs

43. Full report available at:
http://energy.mit.edu/uof