The power sector is evolving once - asocodis.org.co Luke, SM, Technology and Policy Program (’16), MIT RaananMiller, Executive Director, Utility of the Future Study MIT Energy Initiative

The MIT Utility of the Future Study

The power sector is evolving once again…

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

Principal Investigators Ignacio Perez-Arriaga, Professor, Electrical Engineering, Institute for Research in Technology Comillas Pontifical 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 Raanan Miller, Executive Director, Utility of the Future Study, MIT Energy Initiative

Richard Tabors, Visiting Scholar, MIT Energy Initiative

Research Team Ashwini Bharatkumar, 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

Jose Pablo Chaves, Research Scientist, Institute for Research in Technology, Comillas Pontifical University

Research Team (continued)Pablo Duenas-Martinez, Postdoctoral Associate, MIT Energy Initiative

Ignacio Herrero, Research Assistant, Institute for Research in Technology Comillas Pontifical 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

Raanan Miller, Executive Director, Utility of the Future Study MIT Energy Initiative

Pablo Rodilla, Research Scientist, Institute for Research in Technology Comillas Pontifical 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

Robert Armstrong, Director, MIT Energy Initiative

Carlos Batlle, Research Scholar, MIT Energy Initiative; Professor, Institute for Research in Technology, ComillasPontifical University

Michael Caramanis, Professor of Mechanical Engineering and Systems Engineering, College of Engineering, Boston University

John Deutch, Institute Professor, Department of Chemistry, MIT

Tomás Gómez, Professor, Director of the Institute for Research in Technology, Comillas Pontifical 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, MITRichard Lester, 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, Questrom School of Business, Boston University

Álvaro Sánchez Miralles, Senior Associate Professor, Institute for Research in Technology, Comillas Pontifical University

Francis O’Sullivan, Research Director, MIT Energy Initiative

Robert Stoner, Deputy Director for Science and Technology, MIT Energy Initiative

Faculty Committee

Research and Project Advisors

Chair: Phil Sharp, President, Resources for the Future

Vice Chair: Richard O’Neill, Chief Economic Advisor, FERC

Janet Gail Besser, Executive Vice President NortheastClean Energy Council

Alain Burtin, Director, Energy Management, EDF R&D

Paul Centolella, President, Paul Centolella & Associates LC, Senior Consultant, Tabors Caramanis Rudkevich

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, Ambri Inc.

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 Schiavo Deputy 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

Consortium Members

Paul & Matthew Mashikian

“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”

1. A framework for an efficient and evolving power system

2. Insights into the value of Distributed Energy Resources

Presentation contents


A framework for an efficient and evolving power system

1. An Efficient System of Prices and Regulated Charges for 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

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

Expanding choice and new competition requires improved rate design


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 dramatically improve prices and

regulated charges for electricity services.

1 3 5 7 9 11 13 15 17 19 21 23

?

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.

2. Progressively improve the granularity of price signals with respect to both time and location

Sp

atia

l gra

nu

lari

ty

Temporal granularity

Distribution nodal LMPs(DLMPs, real & reactive)

Intermediate DLMPs(substation/zonal/other)

Wholesale LMPs +distribution losses

Wholesale nodal LMPs

Wholesale zonal LMPs

Real-timespot price

Day-aheadhourly price

Critical peakpricing

Time-of-usepricing

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 charge Network capacity charge

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

5. Carefully consider which costs are included in fixed electricity tariffs to avoid inefficient grid defection

Grid defection costs

Grid defection savings

Elec

tric

ity

Tari

ff

Co

mp

on

ents

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-payments and hedging arrangements can address bill variability

3. Low income support: need-based assistance programs can replace implicit (and imprecise) subsidies in volumetric rates

2. Improved Incentives for Regulated Distribution Utilities


1. Reward utilities for cost-savings

Time

$

1st regulatory period 2nd regulatory period 3rd regulatory period

?

Realized cost savings (shared between utility

& ratepayers)

Multi-year revenue trajectory

Realized utility expenditures


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 errorsSee 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


3. Put capital investment and operational expenditures on an even footing

CAPEX OPEX


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


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

3. Electricity Industry Structure in a More Distributed Context


1. Three critical functions (and a fourth?)

System Operator

Market Platform

Network Provider

Data hub?


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


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

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


1. Enable wholesale market transactions to be made closer to real time

This rewards flexibility and incentivizes improves •

forecasting and balancing


2. Enable new resources to play in existing and emerging markets

• Update wholesale market rules (such as bidding formats) to reflect the operational constraints of new resources


3. Align reserves & energy markets & establish the flexibility requirements for participation

Energy prices should reflect the increased probability of •

scarcity events as reserves are dispatched

0

20

40

60

80

Baseload

Midload

Peaker

1 2 3

Opti

mal

cap

acit

y m

ix [

GW

]

0 2,000 4,000 6,000 8,000 10,000 12,000

Operating reserve level [MW]

0

2,000

4,000

6,000

8,000

10,000

Oper

atin

g r

eser

ve

val

ue

[$/M

W/h

]

1 2 3


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

Insights on the Value of Distributed Energy Resources


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.


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, CO2

emissions reduction, etc.


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 1-10 11-20 21-30 31-40 41-50 51-60 61-70 71-80 81-90 91-100 >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


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%

Pro

du

ctio

n-W

eig

hte

d A

vera

ge

M

arg

inal

Lo

sse

s A

void

ed

by

PV

pe

r M

Wh

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.


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

10-1

00

MW

1-2

MW

1-10

kW

10-1

00

MW

1-2

MW

1-10

kW

10-1

00

MW

1-2

MW

1-10

kW

10-1

00

MW

1-2

MW

1-10

kWC

apit

al a

nn

uit

y an

d f

ixe

d O

&M

($

1,0

00

/MW

-yr) Incremental unit cost relative to

10-100 MW system

2015 2025(high cost estimate) (medium cost estimate) (low cost estimate)


5. High locational value can outweigh distributed incremental costs…

$0

$20

$40

$60

$80

$100

$120

$140

$160

$180

Locationalenergy value:transmission

Locationalenergy value:distribution

losses

Conservationvoltage reduction

Networkinvestment

deferral

Generationcapacitypremium

Reliability Total locationalvalue

1-2 MW system 1-10 kW system

Ave

rage

val

ue

per

MW

hp

rod

uce

d

84.7

58.4

148.7

24.05.6

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

Distributed opportunity costs


6. But not always. Smaller is not always better

$0

$20

$40

$60

$80

$100

$120

$140

$160

$180

Locationalenergy value:transmission

Locationalenergy value:distribution

losses

Conservationvoltage reduction

Networkinvestment

deferral

Generationcapacitypremium

Reliability Total locationalvalue

1-2 MW system 1-10 kW system

Ave

rage

val

ue

per

MW

hp

rod

uce

d

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

Distributed opportunity costs

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

Documents

The power sector is evolving once - asocodis.org.co Luke, SM, Technology and Policy Program (’16), MIT RaananMiller, Executive Director, Utility of the Future Study MIT Energy Initiative