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

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

3 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 The MIT Utility of the Future Study Team Principal Investigators Ignacio Pe rez-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

5 Faculty Committee 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 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, MIT Richard 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 Research and Project Advisors 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

6 Advisory Committee 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 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, Former Chair, New York State Public Service Commission

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 Presentation contents 1. A framework for an efficient and evolving power system 2. Insights into the value of Distributed Energy Resources

10 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 The MIT Utility of the Future Study

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

12 Expanding choice requires improved rate design

13 Towards a comprehensive and efficient system of prices and charges The best way to put all resources (centralized & distributed) 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. The MIT Utility of the Future Study

14 1. Ensure that all prices and charges are non-discriminatory, technology neutral, and symmetrical Metered Withdrawals and Injections?

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

16 $/kwh 3. Forward-looking peak-coincident network capacity charges Energy charge Network capacity charge Hour

17 $/kwh 3. and scarcity-coincident generation capacity charges 1.50 Energy charge Generation capacity charge Network capacity charge Hour

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

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

20 6. Address distributional concerns Questions etc. 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

21 2. Improved Incentives for Regulated Distribution Utilities

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

23 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): The MIT Utility of the Future Study

24 3. Outcome-based performance incentives Reduction in average outage duration in Italy following implementation of performance incentives for continuity of supply 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 The MIT Utility of the Future Study

25 4. 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 The MIT Utility of the Future Study

26 3. Electricity Industry Structure in a More Distributed Context

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

28 2. Carefully assign responsibility to minimize potential conflicts of interest Market Platform Network Provider System Operator Data hub? DER Provision / Ownership Retailing / Aggregation Generation The MIT Utility of the Future Study

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

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

31 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 The MIT Utility of the Future Study

32 3. Align reserves & energy markets & establish the flexibility requirements for participation Operating reserve value [$/MW/h] Optimal capacity mix [GW] Energy prices should reflect the increased probability of scarcity events as reserves are dispatched 10, , Peaker 6,000 4, Midload 2, ,000 4,000 6,000 8,000 10,000 12,000 Operating reserve level [MW] Baseload The MIT Utility of the Future Study

33 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 The MIT Utility of the Future Study

34 Insights on the Value of Distributed Energy Resources

35 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. The MIT Utility of the Future Study

36 1. Distributed resources create value by providing locational services Power system values Locational Energy Network capacity margin Network constraint mitigation Power quality Reliability and resiliency Black-start Non-locational Firm generation capacity Operating reserves Price hedging Other values Land use Employment Premium values* Emissions mitigation Energy security * Private values; do not need to be reflected in prices and charges The MIT Utility of the Future Study

37 2. Locational value can be meaningful, but it varies dramatically within a power system Distribution of 2015 Average Nodal LMPs in PJM More than three quarters of nodes between $21-40/MWh 50.4% 26.2% Approximately 3 percent of nodes with very high locational value, 3-10 times the average 0.1% 0.1% 8.4% 7.3% 2.3% 0.9% 0.4% 0.4% 0.5% 2.9% < >100 USD per MWh The MIT Utility of the Future Study

38 Production-weighted average marginal losses avoided by PV 3. Marginal locational value can be rapidly diminishing Marginal Distribution Network Losses Avoided by Distributed Solar PV: Texas ERCOT Example 20% 4% Avg Distribution Losses 8% Avg Distribution Losses 15% 10% 5% 0% 1% 6% 11% 16% 21% 26% 31% 36% 41% 46% Percent of annual energy from distributed solar PV The MIT Utility of the Future Study

39 Levelized Cost of Electricity (2015 USD/MWh) 4. Economies of scale still matter Incremental cost relative to utility scale, NY insolation $ $48 $ MW Utility-scale 1.5 MW Community 1 MW C&I Rooftop 5 kw Residential Rooftop The MIT Utility of the Future Study

40 Average value per MWh produced 5. High locational value can outweigh distributed incremental costs $250 $230 $210 $190 $170 $150 $130 $110 $90 $70 $50 $30 $10 -$10 LMP Locational Premium Locational Value and Distributed Opportunity Cost of Distributed Solar PV: Long Island, New York Example, High Value Case Distr. loss reduction CVR Network invest. deferral Generation deferral Reliability 84.7 Total locational value MW 1.0 MW 5.0 kw Locational Value The MIT Utility of the Future Study Distributed Opportunity Costs

41 Average value per MWh produced 6. But not always. Smaller is not always better $250 $230 $210 $190 $170 $150 $130 $110 $90 $70 $50 $30 $10 -$10 LMP Locational Premium Locational Value and Distributed Opportunity Cost of Distributed Solar PV: Mohawk Valley, New York Example, Average Value Case Distr. loss reduction CVR Network invest. deferral Generation deferral Reliability 7.9 Total locational value MW 1.0 MW 5.0 kw Locational Value The MIT Utility of the Future Study Distributed Opportunity Costs

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