Las Vegas, NV Modeling of Clean Energy Policies and Electrification in New York and New England

Transcription

1 EPIS 20 th EMFC Las Vegas, NV Modeling of Clean Energy Policies and Electrification in New York and New England September 8,

2 Introduction Case Study Overview Objective Client seeking to model and evaluate the energy infrastructure pathways for the Northeast through 2030 and assess cost and GHG emissions of reliable energy systems, and identify opportunities and threats. Governing Question Scope How to balance cost and sustainability, while maintaining reliability to 2030? Northeast U.S. (New York + New England) with representation of electric and gas interconnections to adjacent systems Technology adoption trends to 2030 for end-uses (transport & heat) as well as power generation. Sensitivities on electricity and gas infrastructure development and supply and demand projections. Cost and operational reliability of electricity and gas networks under different GHG compliant and non-compliant energy pathways. A B C E J F G D I H K Page 2

3 Key Policy, Regulatory and Legislative Assumptions Generation Targets State & Policy Target (% or MWh) Qualifying Year CT RPS 27% solar (PV and thermal), wind (all),hydro, geo, CHP, biomass 2020 MA RPS (Class I) 25% Class I: solar (PV and thermal), wind (all),hydro (small), geo, biomass operating AFTER 1/ MA RPS (Class II) 6.1% Class II: solar (PV and thermal), wind (all),hydro (small), geo, biomass operating BEFORE 1/ ME RPS 40% solar (PV and thermal), wind (all),hydro, geo, CHP, biomass 2017 NH RPS 25% solar (PV, thermal, space and water heat), wind (all),hydro, geo, CHP, biomass 2025 NY CES 50% solar (PV), wind (all), hydro (small), biomass 2030 NY Clean Energy Fund 88 TWh solar (PV), wind (all), hydro (small), biomass RI RES 31% solar (PV and thermal), wind (all),hydro, geo, biomass 2030 VT RES 72% solar (PV and thermal), wind (all),hydro, geo, CHP, biomass 2030 MA H.B (Act to Promote Energy Diversity) 9.45 TWh Hydro, Class I RPS firmed up w/ hydro or new Class I RPS eligible sources 2023 Capacity Targets State & Policy Capacity (MWs) Qualifying Year MA RPS 1600 PV 2020 MA H.B (Act to Promote Energy Diversity) 1600 Offshore Wind 2027 NY, Offshroe Wind Master Plan Proposed 2400 Offshore Wind 2030 Analysis assumes 1000 Emissions Targets State & Policy electric sector emission reduction by 2030 Qualifying Base Year NY Clean Energy Standard 40% Power Generation 1990 NY Clean Energy Fund 133 million tons Total System 2016 Note: Reflects current policies as of Spring EE and DR targets are generally included in the ISO forecasts Page 3

4 Base Case

5 Base Case Summary of Base Case Key Assumptions Input Short- to Medium-Tem ( ) Long-Term ( ) Generation Build Generation Retirements Capacity under construction, approved by a state commission, cleared in capacity auctions and included in NYISO Comprehensive Reliability Plan (CRP), Bloomberg (BNEF). Public announcements, NYISO Gold Book, decommissions, state nuclear agreements. AURORA economic capacity additions to meet NY s Clean Energy Standard (CES), New England s RPS targets and maintain minimum reserve margins for reliability. AURORA economic capacity retirements. Power Demand Growth Gas Demand Growth Pace Global forecast based on NYISO and ISONE 2016 load forecasts. End use sectors (R,C, I and T) based on utility forecasts for filed with state commissions, plus GPCM pipeline and LNG deliveries. GPCM annual growth rates for Power generation demand from AURORA s power market simulation. Pipeline Build FERC filed projects included that impact the NE/NY region No other projects considered Gas Prices Coal Prices Policy Goals Renewables/Emissions Policy Goals: Capacity Targets Pace Global Reference Case (GPCM gas model monthly forecast). Base HH= $3.90 average ($2016 Real) by 2030 Pace Global Reference Case Announced capacity Economic renewables to meet NY s 50% Renewable Target by 2030 and Clean Energy Fund (CEF). NE states RPS targets. 9 THW of Firm Hydro Imports from Quebec Capacity additions to meet all or part of the state specific targets: MA RPS 1,600 MW PV (2020) and MA offshore wind 1,600 MW (2027) is met and NY Master Plan 2,400 MW (2030) target 1,000 MW is built Page 5

6 MW Base Case Meeting Today s Policy Targets Requires a Massive Renewable Buildout by 2030 (NY in Particular) Cumulative Capacity Additions 12,000 10,000 8,000 6,000 4,000 2,000 - NYISO ISONE NYISO ISONE NYISO ISONE Gas OnShore Wind Solar Others Off-Shore Wind Total of 35.5 GW of capacity additions in the region in GW in NYISO 7.0 GW in ISONE 4.1 GW of the total are firm announced capacity additions in Includes 3.6 GW natural gas Renewables policy goals (NY CES and NE s RPS targets) drive future additions Post 2020, only 31 GW of renewable capacity additions: 2.6 GW of off-shore wind are policy driven additions with relative poor economics Further gas-fired additions not found economic under the Base View Page 6

7 MW Base Case Majority of the Retirements in the Region are Nuclear and Oil-fired Units 4,000 3,500 3,000 Cumulative Capacity Retired A total of 13.2 GW of capacity is retired in the region GW in NYISO GW in ISONE 4.7 GW of the total are firm announced retirements in ,500 2,000 1,500 1, GW of nuclear - Indian Point (NY) and Pilgrim (NE) GW of coal The bulk of future economic retirements are oil-fired (particularly in NY) - Driven by poor economics, excess capacity and growing renewable penetration. - NYISO ISONE NYISO ISONE NYISO ISONE Coal Gas Nuclear Oil & Other There are 0.7 GW of gas-fired retirements in NY in Post 2020, the expectation is for older gas-fired capacity to survive despite low capacity factors. - Capacity payments, reliability needs, and regulation, will provide additional support as well as rising renewable penetration. Page 7

8 MW Reserve Margins MW Reserve Margin Base Case During Study Period, NY Ends Up with a Net 19.3 GW of Additional Capacity and NE Ends Up with 3.0 GW 8,000 6,000 4,000 2,000 - (2,000) (4,000) (6,000) 30,000 25,000 20,000 15,000 ISONE Nameplate Capacity NYISO 30% 25% 20% 15% 10% 5% 0% 30% 25% 20% NY has a greater need for future renewable capacity to meet the CES. This need is driven by a much lower renewable contribution in 2016 (4%), more aggressive clean energy targets and lower contribution from hydro compared to New England. Reserve margins increase for both regions in the short term with capacity additions. Capacity retirements partially offset the growth in renewable capacity in NE keeping reserve margins in NE at ~24% levels in the long-term. In NY renewable additions overcome capacity retirements through 2025, later falling due to oil retirements. 10,000 15% 5,000 - (5,000) (10,000) Nameplate Capacity % 5% 0% Page 8

9 Base Case Gas and Nuclear Generation Share Decline through Study Period, Particularly in NYISO Change in ISONE Generation Mix TWh TWh Change in NYISO Generation Mix TWh TWh Page 9

10 Base Case As Renewable Generation Targets Increase, Gas Capacity Factors Fall in Both Regions 9.45 TWh imports from Canada has fairly substantial impact on Gas CC capacity factors between 2022 and 2023 in NE. Gas CT experiences more significant initial drop-off than Gas CCs, which fall much more gradually over the study period. ISONE Gas CCs and CTs have higher capacity factors, overall, than New York. Gas capacity factors fall in all cases, more substantially in NYISO than in ISONE: Gas CC capacity factors in New York fall 21% compared to 10% in New England between 2017 and Gas CT capacity factors fall 9% in New York compared to 4% in New England between 2017 and Page 10

11 Base Case CO 2 Emissions from the Power Sector Exceed Regional Targets CO 2 emissions decline through the forecast for both regions due to new capacity additions, retirements and higher penetration of renewables. CO 2 emissions decline 20% in NE in 2023 with 9 TWh of firm hydro imports displacing natural gas generation through CO 2 emissions decline in NY in with new capacity additions, retirements and rising imports. NY emissions decline further post-2024 due to over 15 GW of renewable capacity additions and ~ 6 GW of oil-fired retirements. Page 11

12 However Economy wide Emissions Reduction Targets are not Met Meeting the 40% target via this particular pathway requires: Meeting all base case assumptions (CAFE standards, EE, RPS/CES, offshore wind, large-scale transmission.) Greater emissions reductions from the transport, residential and commercial sectors. Higher penetration of disruptive technologies Page 12

13 Disruptive Technology Scenario 100% of Light Duty Vehicles Sales coming from Electric Vehicles by % electrification of all light-duty vehicles with 100% of total sales coming from electric vehicles by 2029 in the Northeast. Electric Vehicle demand penetration reaches 10% of total load by 2030 vs. 2% penetration in the base case. * PHEV = Plug-in Hybrid. BEV = Battery Electric Vehicles Page 13

14 Disruptive Technology Scenario Near Complete Elimination of Oil and Propane Heat, through a Mix of Electrification and Gas Growth. Growth in electric heat pump technologies displaces traditional heating sources such as Propane, Kerosane, Electric Baseboards and reduces oil-fired heating (diesel). Natural gas heating increases through 2028 to be somehow later displaced by newer electric heating technologies. Electric heating penetration reaches 9% of total load in NYISO by 2030 vs. 2% penetration in the base case. * ASHP = air source electric heat pump. GSHP = geothermal electric heat pump. Page 14

15 Disruptive Technology Scenario Electricity Demand Growing after 2023 Load remains relatively flat through ~2023 (particularly in ISONE) and then increases with rising penetration of EVs and electric heating demand. This is based on the expectation that EVs and electric heat adoption will take several years to be realized. In the scenario load forecasts are 13% higher than base in both New England and New York in Page 15

16 Northeast 2030 Project Overview: Increased Clarity on One Pathway to 40 by 30 Meeting the 40% target via this particular pathway requires: Power: Meeting all base case assumptions (CAFE standards, EE, RPS/CES, offshore wind, largescale transmission.) 13-16% higher capacity buildout than Base Case (42GW vs. 36GW.) Transport: 50% electrification of all light-duty vehicles. LDV sales 100% electric by Heat: Near complete elimination of oil and propane heat, through a mix of electrification and gas growth. Page 16

17 Billions $ Meeting the Emissions Reductions Targets Comes at the Price of a Huge Investment Cost New Generation Capital Investments Costs NYISO and ISONE Meeting today s policy goals requires generation capital investment of at least $20 Billion in New England and $54 Billion in New York. This is mostly made up of generic renewable new builds, particularly in New York. These costs do not account for the additional transmission buildout required, which could be quite substantial at this level of renewable penetration. Disruptive load increases required capital investment by $1-3 Billion in New England, and $8 Billion in New York Base NYISO Base ISONE Disruptive NYISO Disruptive ISONE Announced units Generic New Builds Distributed Generation Page 17

18 Modelling Approach 20 th EMFC Las Vegas, NV

19 Modeling a Challenging Task Client s to do list: 1. Model 3 types of electric vehicles with specific charging shapes. 2. Modeling of rising electric heating demand with specific load shapes 3. Modeling a 50% target for NYISO and ~30% for ISONE 4. 9 TWh of Firm Hydro imports from Quebec with at least 70-90% availability during the summer months 5. Model distributed solar and BTM storage 6. Modeling improving capacity factors for solar and wind. End up with 8-9 change sets, each with 4-6 tables modified. Page 19

20 Gas and Power Integrated Modeling Approach AURORAxmp as a Modeling Framework GPCM Modeling Framework Power modeling used AURORA, an hourly dispatch model, to simulate the economic dispatch of power plants within the New York and New England power markets for AURORA also assessed the economics of existing and future generation technologies for future builds and retirements in order to maintain minimum reserve margins and meet RPS targets. Natural gas fuel price inputs were produced using the GPCM model, a dynamic model that incorporates natural gas supply, demand, and infrastructure inputs, to solve for expected prices and flows throughout North America. Iterations were performed between the two models to ensure gas prices and power demand were in sync. Page 20

21 Modeling of RPS and Capacity Additions Modeled it using the constraint table in Aurora with an LT Energy Min constraint type. The model determines the most economical resources to meet the energy targets set in the Limit column of the constraint table (linked to an annual vector). Renewable energy requirements were set each for NYISO and ISONE with NY having two policies. The overall requirement for NE was estimated outside the model taking into account the RPS for each state and qualifying resources. Run the LTCE using the mixed-integer program and a Maximize value objective function Page 21

22 Modeling of Electric Vehicles as a One Way Battery Modeled as a one-way storage in Aurora with a fixed schedule for three different types of charging profiles. Modeled each profile by pricing zone in Aurora with rising capacity through the forecast. Storage ID linked to the Storage table determines the charging profile for each resource. The overall impact of EVs on load is spread across the day due to the combined effect of the residential, fast charging stations and commercials. Charging behaviors per recent client studies and validated by Siemens Building Technologies Division. Page 22

23 Modeling of Electric Heating as a Negative DSM Resource Modeled as a negative DSM resource to create a positive impact on load. Modeled through a set hourly profile by month and pricing zone with input capacity increasing throughout the forecast. Hourly shapes are input through a monthly and weekly vector. Storage Shaping Factor set to -1 to create the opposite effect. Page 23

24 Modeling Distributed Generation as a Must Run Resource Pace Global assumed BTM generation will primarily be based on solar PV technology, and exhibit capacity factors 3.9 to 5.5 percent points lower than utility scale solar. BTM storage was simulated under the assumption that real time metering is still limited by 2030 and customers do not operate storage in response to real time pricing signals but following their load needs. Effectively, the BTM storage softens the duck curve seen in systems with large penetration of BTM Solar. BTM solar and BTM storage were modeled in Aurora as a combined generation resource dispatched as a must run resource. The hourly dispatch profile of the DG solar resource was combined with the hourly profile of the BTM storage. Thus, the combined output from these resources should be interpreted as the net reduction in demand. Page 24

25 Questions Page 25

26 Pace Global Disclaimer This Report was produced by Pace Global, a Siemens business ( Pace Global ), and is meant to be read as a whole and in conjunction with this disclaimer. Any use of this Report other than as a whole and in conjunction with this disclaimer is forbidden. Any use of this Report outside of its stated purpose without the prior written consent of Pace Global is forbidden. Except for its stated purpose, this Report may not be copied or distributed in whole or in part without Pace Global s prior written consent. This Report and the information and statements herein are based in whole or in part on information obtained from various sources as of September 5, While Pace Global believes such information to be accurate, it makes no assurances, endorsements or warranties, express or implied, as to the validity, accuracy or completeness of any such information, any conclusions based thereon, or any methods disclosed in this Report. Pace Global assumes no responsibility for the results of any actions and inactions taken on the basis of this Report. By a party using, acting or relying on this Report, such party consents and agrees that Pace Global, its employees, directors, officers, contractors, advisors, members, affiliates, successors and agents shall have no liability with respect to such use, actions, inactions, or reliance. This Report does contain some forward-looking opinions. Certain unanticipated factors could cause actual results to differ from the opinions contained herein. Forward-looking opinions are based on historical and/or current information that relate to future operations, strategies, financial results or other developments. Some of the unanticipated factors, among others, that could cause the actual results to differ include regulatory developments, technological changes, competitive conditions, new products, general economic conditions, changes in tax laws, adequacy of reserves, credit and other risks associated with third parties, significant changes in interest rates and fluctuations in foreign currency exchange rates. Further, certain statements, findings and conclusions in this Report are based on Pace Global s interpretations of various contracts. Interpretations of these contracts by legal counsel or a jurisdictional body could differ. Page 26

27 Contact Information Marcelo Saenz Sr. Consultant Phone: (713) Claire Behrens Principal Consultant Phone: (978) Page 27

28 Technical Appendix

29 AURORAxmp Modeling Zones Closely Align with ISO Zones NEISO Zonal Overview NYISO Zonal Overview D ISONY D ISONY E ISONE ME B E F ISONY F A C ISONE VT/NH ISONY A-C G ISONY G-I H I ISONE MASS Hub ISONY J NYC J K ISONE CT ISONE MA Boston ISONY K Long Island ISONE RI Page 29

30 Greener Generation Fleet in NY and NE by 2030 Renewable share of total generation reaches 31% in NE and 49% in NY, by That compares to 12% in NE and only 4% in NY in In NYISO gas generation is displaced by rising wind (on and offshore) and solar generation. Coal and oil-fired generation disappears from the generation mix in the region by 2030 due to economic retirements. The entrance of over 9 TWH of firm hydro imports in ISONE in 2023 displaces mostly gas generation in the region through Nuclear generation share in NY declines 15% by 2030 from 29% levels in In NE declines 6 percentage points to 23% of the total by Page 30

31 Modeling Limitations Transmission: In AURORA, transmission capacity is an input, and therefore the model does not solve for an optimized transmission build. However, the ProMod effort identifies binding transmission constraints in the NYISO/ISONE base case in one year (2030). Gas Price Resolution: GPCM (the natural gas market model) price forecasts are at the monthly resolution. It thus does not analyze LNG for relieving peak demand. Out of scope items: Analysis of neighboring regional action (e.g. PJM, Ontario, Quebec) Capacity Expansion sensitivities, e.g. the impact of different price and cost forecasts for natural gas, wind & solar capital costs, nuclear costs, etc. Analysis of alternative power sector decarbonization pathways: Power sector decaronibation via nuclear or CCS Heat decarbonization via zero-c pipeline fuels (e.g. renewable gas, hydrogen) Transport decarbonization via low-carbon fuels (e.g. hydrogen, biofuels, RNG) Impact of additional nuclear retirements beyond those announced by May 2017 Impact of missed targets and deadlines (RPS, CES, 83c, 83d) Assessment of potential FERC 1000 investment opportunities Page 31