Introduction

This appendix describes in more technical detail the economic model and data underlying the estimates in chapter 3. The appendix begins with a review of two studies which also examine some aspects of Massachusetts’s recent goals and commitments that are the focus of this report. The rest of the appendix is divided into four broad sections, which discuss model inputs, model outputs, data sources, and additional results.

The section on model inputs provides more specifics about the calculation of model inputs, including details of how the load shares of the goals and commitments and of hydroelectricity are calculated; how the model calculates the way electricity sourcing shifts to meet the clean and renewable standards; how the compliance credits are modeled; and some background information on the five scenarios taken from the U.S. Energy Information Administration’s (EIA) Annual Energy Outlook (AEO).

The model outputs section supplies additional details on the calculations of the key model results: effects on the price of wholesale generation, effects on the costs to Massachusetts consumers, effects on the costs to New England consumers, and effects on Massachusetts emissions.

The data sources section provides details about the sources for the data in the model, including more detail on calculations used throughout.

The additional results section presents results to supplement the analysis in chapter 3. First, it reports additional estimates of the greenhouse gas emissions, giving model projections for the four alternative scenarios. Then, it presents a sensitivity analysis of the modeling assumptions outlined in table 3.2. These three sensitivity analyses focus on (1) changing the marginal resource used to satisfy renewable portfolio standard (RPS) and clean energy standard (CES) demand; (2) changing how much access Massachusetts has to clean energy imports; and (3) changing the assumption about the number of residential and commercial customers.

As was the case in chapter 3, for this appendix, “renewable” refers specifically to resources that qualify for Massachusetts’s RPS commitment and “clean” refers to resources that qualify for Massachusetts’s CES commitment, unless otherwise specified.

Related Studies of Massachusetts’s Recent Goals and Commitments

Two other studies have considered the potential effects of certain aspects of Massachusetts’s renewable and clean energy commitments on ratepayers and greenhouse gas emissions in the past five years. The first (“Massachusetts Energy study”) was prepared by Synapse Energy Economics and Sustainable Energy Advantage at the request of Northeast Clean Energy Council Institute and Massachusetts Energy Consumers Alliance. Published in May 2017, the study compares a baseline case to potential modifications to Massachusetts’s and Connecticut’s RPS commitments. For Massachusetts, the baseline case includes the 2016 Act to Promote Energy Diversity, which committed Massachusetts to acquiring long-term contracts for both offshore wind and for clean energy;^{^[1]} the Global Warming Solutions Act (GWSA) emissions commitments, which set economy-wide targets to reduce greenhouse gas emissions by 80 percent of their 1990 levels by 2050; and Massachusetts’s prior commitment to increasing its RPS by 1 percentage points per year through 2050. The study then considers, among other things, the effect of altering Massachusetts’s and Connecticut’s RPS commitments three ways: (1) an increase of 2 percentage points per year in Massachusetts’s RPS; (2) an increase of 2 percentage points per year in Massachusetts’s RPS and an increase of 1.5 percentage points per year of Connecticut’s RPS; and (3) an increase of 3 percentage points per year in Massachusetts’s RPS and an increase of 1.5 percentage points per year in Connecticut’s RPS.^{^[2]}

The second study (“Massachusetts Senate study”), published in June 2018, was prepared by the Applied Economics Clinic and Sustainable Energy Advantage at the request of the Massachusetts Senate Committee on Global Warming and Climate Change. This study analyzes the effect of provisions proposed in drafts of the 2018 Act to Promote Clean Energy: (1) an acceleration to Massachusetts’s RPS from 1 percentage point per year to 3 percentage points per year, (2) a commitment to building 5,000 megawatts of offshore wind by 2035, (3) reaching 1,766 MW of battery storage in-state by 2025, and (4) removing the cap on net metering of electricity (the selling of electricity back to the grid) from small solar installations.^{^[3]} The 2018 Act ultimately included an acceleration of 2 percentage points per year, rather than the 3 percent acceleration examined in this study. Additionally, the 2018 Act set a goal for potential offshore wind procurement at an additional 1,600 megawatts, instead of the full 5,000 megawatts modeled in the report.^{^[4]}

Both the 2017 Massachusetts Energy and 2018 Massachusetts Senate reports are built using multiple proprietary models developed by private organizations: the EnCompass model, which models electricity sector capacity buildout and generation dispatch, and the Renewable Energy Market Outlook model, which models renewable energy buildout and forecasts REC prices. These are large electricity system models that simulate the effect of renewable energy sourcing commitments on a variety of economic indicators, including the impact on greenhouse gas emissions and on retail electricity rates. Their models project the effects of the respective commitments out to 2030 under several alternative scenarios to reflect uncertainty over future market conditions.

The 2017 Massachusetts Energy study found that increasing the RPS in Massachusetts to 2 percentage points per year would result in an increase in in-region renewable electricity capacity of between 300 and 1,100 megawatts (MW).^{^[5]} The study also found that increasing Massachusetts’s RPS commitment to 2 percentage points per year is projected to reduce wholesale electricity prices by an average 0.3 percent per year between 2025 and 2030.^{^[6]} As for retail prices, the study found an additional monthly cost to consumers of between $0.10 and $0.20 from 2018 to 2030 when the RPS was increased to 2 percentage points per year.^{^[7]} This study also projected a baseline decrease in electricity sector emissions by 2030 of 60 percent over 1990 levels, while the increase in Massachusetts’s RPS to 2 percentage points per year would result in a reduction in emissions of 62 percent of the 1990 levels.^{^[8]}

The 2018 Massachusetts Senate study, by contrast, found that the commitments modeled would result in additional renewable generation capacity buildout of approximately 1,500 MW in Massachusetts.^{^[9]} This study predicted a reduction in emissions due to the commitments equal to 0.6 million metric tons of greenhouse gas emissions.^{^[10]} Finally, the study predicted an increase in Massachusetts’s average household electricity bills of 44 cents per month (or 0.25 cents per kWh) for the first three years of the forecast, with prices falling below their initial value thereafter. On average, this would result in a reduction of consumer bills by about 1.5 percent over the 2018 to 2030 window.^{^[11]}

Model Inputs

Calculation of Load Shares for Goals and Commitments, Hydroelectricity

The Commission’s model focuses on the effects of Massachusetts’s updated Class I renewable portfolio standards.^{^[12]} These standards do not mandate that a certain share of electricity generation in Massachusetts or New England come from clean or renewable sources.^{^[13]} Rather, they require that Massachusetts utilities purchase or earn enough compliance credits to cover a mandated share of the electricity load that they serve. Massachusetts’s RPS can be satisfied by renewable resources, including wind and solar, located in New England or interconnected regions. The Class I RPS commitment increases to 55 percent of Massachusetts’s load by 2050. Massachusetts’s CES commitment is higher, rising to 80 percent of Massachusetts load by 2050. It can be satisfied by hydroelectric generation (built after 2010) or nuclear generation (built after 2010), as well as by any Class I renewable resources.

In the tables and formulas below, S_o represents the initial (or “old”) RPS share of Massachusetts’s load, S_u represents the updated RPS share, and S_c represents the CES share. In each year, S_c < S_u < S_c. Table E.1 reports the shares for 2030, 2035, 2040, 2045, and 2050.^{^[14]}

Table E.1 Renewable and clean energy requirements (as a percentage of total load)

Share	2030	2035	2040	2045	2050
S_o	25	30	35	40	45
S_u	35	40	45	50	55
S_c	40	50	60	70	80
S_c – S_u	5	10	15	20	25

Source: State of Massachusetts, “Program Summaries: Summaries of all the Renewable and Alternative Energy Portfolio Standard Programs,” (accessed September 16, 2020); “Clean Energy Standard,” 310 CMR 7.75 (2017), 509, 513–14; “Act to Advance Clean Energy (H4857),” 2018,; “Renewable Energy Portfolio Standard for Retail Electricity Suppliers,” Mass. Gen. Laws ch. 25A, § 11 F.

As discussed in a footnote in the “Massachusetts’s Recent Goals and Commitments” section of chapter 3, the renewable and clean energy commitments modeled in this report generally apply to investor-owned utilities, not municipally owned utilities. Municipally owned utilities account for about 14.1 percent of Massachusetts’s total electricity demand.^{^[15]}

Table E.2 reports S_h, the share of non-municipally provided load supplied by hydroelectric power in each year in the AEO Reference case, including imports from Canada and New York. Given that the AEO does not break imports down by generation source, the share of total imports coming from hydroelectric generation is calculated using reported shares of hydroelectricity in New England imports available on the NEPOOL (New England Power Pool) General Information System. The NEPOOL information shows that for the most recent available data, 24.8 percent of electricity imports from New York State and 96.0 percent of electricity imports from Quebec were from hydroelectric generation.^{^[16]} Hydroelectricity generated in New England is not counted in the calculation of S_h due to a simplifying assumption that all New England hydroelectric facilities came online before 2011 and would not qualify to fill Massachusetts’s CES commitments.

Table E.2 Projected share from hydroelectric power, Reference case (as a percentage of total load)

Share	2019	2030	2035	2040	2045	2050
S_h	16.2	14.6	14.0	14.3	14.2	14.2

Source: USITC calculations.

Note that although table E.2 shows a decrease in the share of hydroelectric power (hydro) in total load over the 2019 to 2050 timeframe, the projected levels of hydro are relatively stable, starting at 7.5 TWh in 2019, initially falling slightly, and ending at 7.8 TWh in 2050.

Shift in the Electricity Sourcing to Meet the Standards

Since hydroelectric generation qualifies for Massachusetts’s CES, hydroelectricity satisfies most, and in some years all, of the gap between S_u and S_c. For the first two periods of the model, tables E.1 and E.2 show that the entire commitment of Massachusetts’s CES above its RPS would be satisfied by imported hydroelectricity, since S_h > S_c – S_u. The gap between S_h and S_c – S_u would be less than 1 percent in 2040 and would then rise to become closer to 5 and 10 percent in 2045 and 2050, respectively.

The model assumes that any difference between Massachusetts’s CES and RPS commitment that is not satisfied by hydroelectricity would be satisfied by building additional RPS-eligible generation in New England. It is not likely that imports of hydroelectricity would increase to fill this gap, since there are international transmission constraints that would likely persist for decades into the future.^{^[17]} Furthermore, building new nuclear or hydroelectric generation in New England is not projected to be cost effective when compared to building renewables like wind and solar.^{^[18]}

Tables E.3 and E.4 report the projected generation mix in the New England region in the AEO 2020 Reference case as supporting evidence for the argument that wind and solar, not hydroelectricity, will meet the additional demand for clean energy. Electricity generation in AEO projections is divided into two major categories: generation by the electric power sector (table E.3), which is generation by utility-scale providers that then distribute electricity to the end users, and generation by the end-use sector (table E.4), which is generation by the end users themselves. For generation in the electric power sector, the greatest growth is projected in production from onshore and offshore wind, while hydroelectric power and other renewable sources remain relatively constant. Growth in offshore wind is projected to occur rapidly over the next 10 years and then level off. A similar pattern is projected in onshore wind. For generation in the end-use sector, most of the projected increase beyond 2030 is in solar generation, representing on-site solar installations (including rooftop solar generation).^{^[19]} The AEO projects that other renewable and clean energy sources will remain relatively constant.

Table E.3 Projected renewable generation mix in the electric power sector in the New England region, Reference case (in terawatt-hours)

Type of generation	2019	2030	2035	2040	2045	2050
All renewable and clean	10.6	43.3	45.1	45.5	45.6	48.0
Solar (photovoltaic)	1.5	2.0	2.0	2.0	2.1	2.4
Offshore wind	0.1	7.1	8.8	8.8	8.8	8.8
Onshore wind	3.3	26.7	26.7	27.1	27.1	28.9
Wood and other biomass	3.3	3.6	3.6	3.6	3.6	3.6
Municipal waste	2.4	4.0	4.0	4.0	4.0	4.3

Source: Compiled from AEO 2020, Reference Case estimates.

Note: The AEO defines the electric power industry as “stationary and mobile generating units that are connected to the electric power grid and can generate electricity. The electric power industry includes the ‘electric power sector’ (utility generators and independent power producers) and industrial and commercial power generators, including combined-heat-and-power producers, but excludes units at single-family dwellings.” EIA, “Glossary” (accessed September 21, 2020).

Table E.4 Projected renewable generation mix in the end-use sector in the New England region, Reference case (in terawatt-hours)

Type of generation	2019	2030	2035	2040	2045	2050
All renewable and clean	6.6	12.7	14.4	16.3	18.1	19.9
Solar (photovoltaic)	4.9	10.8	12.5	14.4	16.1	17.9
Onshore wind	0.1	0.1	0.1	0.1	0.1	0.1
Wood and other biomass	1.4	1.4	1.5	1.5	1.6	1.6
Municipal waste	0.2	0.2	0.2	0.2	0.2	0.2

Source: Compiled from AEO 2020, Reference Case estimates.

Given the anticipated size of solar as a generation resource and that solar and wind are the renewable resources which require the smallest incentives in the projection periods, the model assumes that solar will be the marginal resource meeting demand for new renewables.^{^[20]}

Modeling the Value of Compliance Credits

The renewable and clean energy standards are designed to incentivize new energy production through the payment of compliance credits. The value of these incentives depends on how profitable new energy plants would be absent the credits. A plant’s profitability per megawatt-hour (MWh) of electricity generated is the difference between the average cost and average revenue over the full life cycle of the plant.

Massachusetts’s increased commitments only create compliance costs to the extent that they are needed to incentivize additional generation to meet the standards. If average revenue is less than average cost, the renewable or clean energy credit (or more generally “compliance credit”) covers the difference in order to make the investment in renewable or clean energy resources profitable, and the commitments are “incentivizing” new renewable or clean generation. If the standards are incentivizing, then the value of compliance credits is greater than zero and Massachusetts utilities pay the cost of the credits, which they then pass on to Massachusetts retail electricity consumers. For the model scenarios and years where the standards are not incentivizing, the value of the credits is zero. In these years the commitments have no effect on generation or other market outcomes and no effect on costs to consumers.

The model estimates the future values of the credits based on the economic fundamentals that underlie the profitability of new renewable generation. These fundamentals suggest that credit values should incorporate future technological innovations, revenue opportunities, and all other factors that determine the profitability of new generation.

For any share of renewables S, a new generation plant’s profits per MWh, π, are equal to the difference between its average revenue, AR, and its average cost, AC:

(E1)

Table E.5 provides the AEO’s projections for average revenue and average cost for solar photovoltaic (PV) generation for each of the model years.

Table E.5 Average revenue and average cost of the marginal solar generation plant, Reference case (in 2019 dollars per megawatt-hour)

Measure	2030	2035	2040	2045	2050
AR	33.70	33.11	35.30	34.79	33.69
AC	37.56	35.34	33.40	31.75	30.48
AR minus AC	-3.87	-2.23	1.94	3.03	3.21

Source: EIA, Annual Energy Outlook 2020: LACE (available from EIA on request; accessed October 2, 2020); EIA, Annual Energy Outlook 2020: LCOE (available from EIA on request; accessed October 2, 2020).

Although these estimates are generally low, REC prices in Massachusetts have been declining since they reached a peak in 2014.^{^[21]} At their highest, Class I RECs reached around $65 per MWh in 2014. The average monthly closing price of RECs for Class I renewables in Massachusetts was listed as low as approximately $5 per MWh in the third quarter of 2018, reaching around $20 per MWh in the second quarter of 2019.^{^[22]}

To account for diminishing profitability of renewables as their market share increases, the model adjusts the estimate of the profitability (in terms of 2019 dollars per MWh) of additional renewable generation at different levels of renewables penetration, using the profitability curve defined in equation (E2):

(E2)

where S₁ and S₂ represent any two shares of renewable generation in the market. If share S₂ is greater than share S₁, then π(S₂) will be less than π(S₁). This curve is almost flat when S₂ is close to S₁, decreasing S₂ as increases, and becomes very negative as S₂ approaches one. This diminishing profitability of new generation as renewable penetration increases in a particular year reflects the likely exhaustion of the best revenue opportunities and least-cost projects.

The model estimates the equilibrium value of the credit (VOC) required to incentivize enough additional renewable and clean generation to meet the updated standards in equilibrium, based on equation (E3):

(E3)

The compliance credit represents an equilibrium outcome: if the value of the credit were smaller, the standards would not be met; if the value of the credit were larger, excess investments would drive down the value of the credit.

The model defines VOC₀ as the value of compliance credits under the initial RPS, and VOC₁ as the value of compliance credits under Massachusetts’s updated RPS and its CES. These are not values at different points in time; they are values at the same point in time for different levels of electricity sourcing coming from renewables, so it is always the case that VOC₁ is greater than or equal to VOC₀. Starting from π(S_u), the profitability projection from the AEO, and defining S_x = MAX[0, S_c – S_u – S_h], the profitability measures at the updated and initial RPS are given in equations (E4) and (E5):

(E4)

(E5)

If S_h > S_c – S_u (no additional renewable sources are required beyond those that meet the updated RPS), then VOC₁ can be calculated as the difference between average revenue and average cost of the marginal renewable source, equal to MAX[0, – π(S_u)]. This is the case in 2030 and 2035 for all five AEO cases. If S_h < S_c – S_u (additional renewable sources are required beyond those that meet the updated RPS), then there is an upward adjustment in VOC₁ as the profitability of the marginal renewable resource falls. This is the case in the illustrative example provided in figure E.1, which shows that VOC₁ is found by a rightward movement along the diminishing profitability curve from π(S_u) for 2050 for the AEO High Renewables Cost case as new renewable generation becomes less profitable.

Figure E.1 provides an illustration of the relationship between VOC₀, equal to – π(S₀), and VOC₁, equal to – π(S₁), when S_h < S_c – S_u using the profitability curve for the year 2050 in the High Renewables Cost case of the model. The figure shows that at the red point, labeled π(S_u), the difference between AR and AC generated by the AEO’s general equilibrium model is approximately −$7.63 per MWh of generation. The numbers used for the value of the credits in the Commission’s modeling, however, are the points labeled VOC₀, the value of the credit with the old RPS commitment in place, and VOC₁, the value of the credit with the updated RPS and the new CES in place. These values are approximately $7.45 per MWh for the old commitment levels and $8.08 per MWh for the new commitment levels, resulting in an additional credit of $0.63 per MWh. The increased saturation of renewable and clean energy to meet the higher commitments results in lower profitability per MWh, driving up the required credit size to incentivize new renewable generation.

Figure E.1 Average revenue minus average cost estimates, 2050 High Renewables Cost case example

Source: USITC calculations.

Note: Underlying data for this figure can be found in appendix table G.41.

The model assumes that the residual of Massachusetts’s CES over its updated RPS and imported hydroelectricity is met by new renewable generation in New England, rather than clean nonrenewables. This is a reasonable assumption, because (1) large nuclear facilities would take decades to permit and construct and high construction costs, and (2) this report is not considering how additional transmission from Canada to Massachusetts would affect Massachusetts’s ability to meet its commitments.^{^[23]} Given this assumption, the value of the credit will be the same for both renewable and clean sources, as the model equalizes the return to new renewable generation being used to fill either the RPS or CES commitment. However, if adding hydroelectric power becomes a less expensive way to meet the residual of Massachusetts’s CES over its updated RPS, then the model estimates may overstate the effects of Massachusetts’s CES on compliance costs.

For context, the estimated share of Massachusetts’s CES commitments met by additional renewables is given in table E.6. The table only reports shares in 2040, 2045, and 2050; for all earlier years of the model there is enough imported hydroelectricity to satisfy the entirety of the difference between Massachusetts’s CES and RPS commitments.

Table E.6 Additional renewable generation necessary to meet CES commitment (as a percentage of total Massachusetts load)

Year	CES minus RPS share	Reference case	High Renewables Cost case	Low Renewables Cost case	High Oil and Gas Supply case	Low Oil and Gas Supply case
2040	15.0	0.7	0.4	0.1	0.0	0.0
2045	20.0	5.8	5.1	5.1	3.1	4.0
2050	25.0	10.8	10.9	10.2	9.5	10.0

Source: USITC calculations.

Background on AEO Scenarios

As mentioned in chapter 3, the AEO uses a comprehensive general equilibrium model of the U.S. economy to build projections for the energy sector through 2050. To account for the uncertainty of long-term projections, the AEO includes several alternative scenarios. The modeling makes use of data from five of the AEO’s cases: the Reference case, the High Renewables Cost case, the Low Renewables Cost case, the High Oil and Gas Supply case, and the Low Oil and Gas Supply case. Due to the uncertainty inherent in developing a model with projections 30 years into the future, these cases provide insights for several possible states of the world over the next three decades.

The Reference case represents the EIA’s “best assessment of how the U.S. and world energy markets will operate through 2050, based on key assumptions intended to provide a base for exploring long-term trends.”^{^[24]} The alternative cases then present specific adjustments to allow for potential departures from the Reference case.

First, consider the High and Low Renewables Cost cases. Recall that in table 3.2, in the High Renewables Cost case, overnight capital cost for renewables is assumed to remain at 2019 levels, where overnight capital cost is a hypothetical measure equal to the cost of building a new power plant, assuming no interest accrues during the process.^{^[25]} For the Low Renewables Cost Case, the model assumes that overnight capital cost, operating and maintenance costs, and fuel costs (where applicable) for renewables fall 40 percent lower than the Reference case equivalents by 2050.^{^[26]} From the AEO’s 2020 data release, figure E.2 shows how these two cases change the forecast capital costs associated with solar photovoltaic (PV), wind, and combined-cycle natural gas generation.

Figure E.2 Overnight installed capital cost in the United States by technology, Reference and alternative Renewables Cost scenarios (in 2019 dollars per kilowatt)

Source: EIA, AEO2020 Full Report, January 29, 2020, 21.

Note: Underlying data for this figure can be found in appendix tables G.42, G.43, and G.44.

The AEO’s Reference case depicts a higher overnight capital cost for wind for almost the entirety of the forecast window, with the cost of solar also declining far more rapidly than the cost of wind. In the Low Renewables Cost Case, however, the cost of wind and solar are very similar initially, with the overnight capital cost of solar eventually falling below the cost of wind. In the High Renewables Cost case, the overnight capital costs of solar and wind are frozen at their 2019 levels. This means even though solar is forecast to drop below wind very quickly in the Reference case, this does not occur in the High Renewables Cost case, and solar remains more expensive than wind throughout the forecast window.

Next, consider the High Oil and Gas Supply and Low Oil and Gas Supply scenarios. The High Oil and Gas Supply scenario assumes 50 percent higher well output and 50 percent higher technological improvements than the Reference case.^{^[27]} The Low Oil and Gas Supply case assumes 50 percent lower well output and 50 percent lower technological improvement than the Reference case.^{^[28]} The resulting forecasts for natural gas production are given in figure E.3.

Figure E.3 U.S. electricity generation from selected fuels, Reference, and alternative Oil and Gas Supply scenarios (in terawatt-hours)

Source: EIA, AEO2020 Full Report, January 29, 2020, 58.

Note: Underlying data for this figure can be found in appendix tables G.45, G.46, and G.47.

The AEO’s graphs of electricity generation in the Reference case show that generation from renewables is projected to pass generation from natural gas by around 2045. In the High Oil and Gas Supply case, however, natural gas is projected to remain the primary source of electricity generation throughout the forecast window, and the projected output of electricity from renewables is projected to be below the Reference case projections. In the Low Oil and Gas Supply case, electricity generation from renewables is projected to be much greater than in the Reference case by the end of the forecast window, with generation from natural gas dropping by about a third compared to its 2019 level before leveling off around 2030.

Model Outputs

Effects on the Price of Wholesale Generation

Massachusetts’s new commitments lead to additional generation when they are incentivizing. As a result, the commitments increase electricity supply in New England, lowering the price of generation available to Massachusetts utilities. The model estimates future reductions in the price of generation in New England using projections of future prices of electricity in New England for a case with the updated RPS in place and another case, the RPS Sunset case, with no RPS or CES.^{^[29]} The difference between these two price projections, prorated by the difference between Massachusetts’s initial and updated RPS plus the part of Massachusetts’s CES share above the updated RPS that is not met by hydroelectric resources in the baseline, is the estimated negative price effect of the updated RPS.

The estimated policy-induced reductions in the price of generation are small, and the effects of the additional CES are zero in most years or very small in 2050. The model applies the ratio of the changes in commitment shares to adjust the estimated reduction in the price of generation in New England observed going from the RPS Sunset case to the Reference case. Equation (E6) defines the wholesale price effect (WPE):

(E6)

where I_h is one if S_h < S_c – S_u and is zero otherwise; where the prices P_Ref and P_Sunset are the AEO’s projected prices for New England in the Reference case and RPS Sunset case, respectively; and where S_NE is equal to Massachusetts’s share of total New England load (45.6 percent). The first term of equation (E6) is the estimated price effect of the RPS commitments of all 30 policies nationwide as compared to the situation if there were no state-level RPS commitments. The second term of the equation is the prorating factor, which prorates the total effect by the amount of renewables required to meet Massachusetts’s RPS and CES commitments, (S_c – S_u) + I_h ((S_c – S_u) – S_h), divided by the increase in Massachusetts’s commitment going from the Reference case to the RPS Sunset case (equal to zero), S_u – 0. The final term further prorates the New England price effect by multiplying it by Massachusetts’s share of New England’s total load.

Effects on the Costs to Massachusetts Consumers

The effects of the standards on costs to residential and commercial electricity customers in Massachusetts will be determined mostly by the increased cost of compliance credits. Equation (E7) estimates the change in the costs of the credits, ΔCredit, to Massachusetts consumers, in 2019 constant dollars per MWh:

(E7)

where I_h is one if S_h < S_c – S_u and is zero otherwise. The effects of the standards on the total costs to consumers also include the small estimated policy-induced reduction in the price of generation discussed above. Equation (E8) defines the total cost to consumers inclusive of the credit and the price reduction in 2019 constant dollars per MWh:

(E8)

where ΔCredit is defined in equation (E7); I_v is one if VOC₁ > 0 (i.e., the policy is incentivizing) and is zero otherwise; and WPE is defined in equation (E6). For the share of load covered by the standard, any reduction in the price of generation will require an increase in the value of the compliance credits in order to maintain the profitability of the new generation, so this price reduction has no net effect on Massachusetts consumers. The reduction in the price of generation will likely mitigate some of the increased costs from compliance credits, but this effect will likely be relatively minor. From equation (E8), WPE is applied to the share of generation that is not satisfied by renewable generation. Simplifying the second term of the equation, if the share of hydro is large enough that no clean energy needs to be incentivized, then the wholesale price effect equals (1 – S_u) WPE. If the share of hydro is not large enough to satisfy Massachusetts’s CES, then all of the new renewables built to satisfy Massachusetts’s RPS also receive credits, so the price effect is applied to the share of generation not satisfied by renewables, now equal to (1 – (S_c – S_h)) WPE.

The model then calculates the total dollar value of the change in costs to consumers for each of the future years by multiplying the estimated change per MWh by the estimated Massachusetts non-municipal load in the year.

Effects on the Costs to New England Consumers

As discussed in chapter 3 of this report, the costs for the Massachusetts RPS and CES commitments from the compliance credits would be paid only by Massachusetts consumers; the economic effects of the commitments for the rest of New England would be limited to impacts on the price of generation in the region.

The model calculates the total dollar value of the change in costs to New England consumers for each of the future years by multiplying the estimated effect on the price of generation per MWh, as defined in the equation (E6), by the estimated New England load net of Massachusetts in the year.

Effects on Massachusetts Emissions

To the extent that the standards lead to more renewable or clean generation, they will reduce the greenhouse gas emissions associated with Massachusetts electricity loads. The model approximates the reduction in carbon dioxide (CO₂) emissions based on the estimated increase in renewable and clean sourcing by assuming that the renewable and clean sources replace natural gas generation, since natural gas generation is the next-lowest-cost resource.^{^[30]} Table E.7 lists these CO₂emissions rates.

Table E.7 Carbon dioxide (CO₂) emissions rate of natural gas generation in New England, Reference case (in million metric tons per megawatt-hour)

Measure	2030	2035	2040	2045	2050
CO₂emissions rate	0.411	0.392	0.429	0.437	0.447

Source: USITC calculations.

If clean generation is profitable absent incentives from Massachusetts’s CES or RPS, then although new production from clean resources will reduce emissions, those reductions will not count toward the estimated policy-induced reductions in emissions. This is why in some years the model does not project any policy-induced reductions inemissions.

Equation (E9) estimates the policy-induced change in emissions associated with Massachusetts’s load, in millions of metric tons per MWh:

(E9)

I_v is equal to one if VOC₁ > 0 and zero otherwise. erng is the CO₂ emissions rate for displaced natural gas generation in New England (table E.7). The model calculates the total policy-induced change in CO₂emissions in each of the future years by multiplying the estimated change per MWh by the estimated non-municipal load in Massachusetts in a given year.

Data Sources

The model includes data from many different sources.

· The data on the renewable and clean energy commitment shares in table E.1 are from the Massachusetts state implementing legislation.

· The model takes into account the fact that the aspects of Massachusetts’s RPS and CES modeled in this report generally apply only to investor-owned utilities and not to municipal providers by netting out the share of electricity sales coming from municipal providers. Data on the share of electricity from municipal providers are pulled from the EIA’s state electricity profile for Massachusetts table on Retail Electricity Sales Statistics for 2018 (the most recent available data).^{^[31]} The model assumes this rate remains stable over the span of the model at its 2018 level of approximately 14.1 percent.

· The data on future loads in Massachusetts are calculated using EIA’s AEO projections on net energy for New England load in the future years, adjusted for the share of Massachusetts load in total New England load reported by ISO New England and also for the share of Massachusetts load served by municipal utilities.

· The share of Massachusetts in New England’s total load is assumed to remain constant at the levels in the most recent data available (2018), equal to 45.6 percent. Massachusetts’s share is found by dividing the Massachusetts load estimates from EIA by ISO New England’s estimates of total load.^{^[32]}

· The data on the share of Massachusetts non-municipal load served by imported hydroelectric resources in table E.2 are calculated from the EIA’s AEO projections for New England’s international and interregional imports (prorated for the share of these international and interregional imports that are hydroelectric generation), assuming that the shares serving Massachusetts are the same as the shares in total New England load. The share of New England’s imports coming from hydroelectric generation is extrapolated from the most recent available NEPOOL estimates. In September 2018, 24.8 percent of imports from New York State were from hydroelectric generation. In October 2018, 96.0 percent of imports from Quebec were from hydroelectric generation.^{^[33]}

· The average revenue estimates for the marginal new renewable generation in New England are based on EIA’s levelized avoided cost of electricity (LACE) for the five AEO 2020 cases. The model uses EIA projections at the regional level, defined by ISO New England. Detailed data for each year, plant type, and case for the New England region were provided by EIA. LACE measures the revenue available to a new generator over a 30-year cost recovery period. EIA estimates revenue opportunities for the additional generation on an hour-by-hour basis over the full life cycle of the generation plant. LACE accounts for variation in daily and seasonal electricity demand and for the characteristics of the existing generation fleet to which new capacity will be added.

· The average cost estimates for the marginal new renewable generation in New England are based on EIA’s levelized cost of electricity (LCOE) estimates for the five AEO 2020 cases. Additional underlying data for each year, plant type, and case for the New England region are provided by EIA. LCOE measures the revenue required to build and operate a new generator over a 30-year cost recovery period. It is calculated by EIA based on engineering estimates of building, operating, and maintenance costs over the full life cycle of the generation plant. It incorporates projections of future technology, fuel costs, and many other factors.^{^[34]}

· The model estimates future reductions in the price of generation in New England using simulation results reported in the 2020 AEO. EIA projects future prices of electricity in the New England region for its Reference case (which includes Massachusetts’s pre-2016 RPS but not its CES or the 2018 update of its RPS) and the RPS Sunset case (with no RPS).

· Estimates of the cost to residential consumers per household per month are calculated by first finding the average consumption per household per month in Massachusetts. This is calculated using AEO’s forecasts for residential electrical energy use for New England, adjusting by the share of electricity load in New England going to Massachusetts (about 45.6 percent), and then dividing by the number of residential customers in Massachusetts according to the AEO’s state electricity profile. This makes the estimate potentially on the higher end, as it does not allow an increase in the number of residential consumers over the time period but instead assumes the number of retail customers remains constant from the 2018 levels. An alternative cost estimate in which the number of residential consumers grows according to a linear trend is included later in this appendix.^{^[35]}

· Emissions rates are calculated using AEO forecasts. Specifically, for each of the five cases considered in the Commission model, AEO forecasts the level of generation and carbon emissions by resource type over the span of the model. Taking the projected emissions from natural gas generation in a given year (the lowest-cost displaced resource) and dividing by the projected generation from natural gas in that same year yields the projected emissions per megawatt-hour of electricity coming from non-clean resources.

Additional Results

Alternative Scenarios: Cost to New England Consumers and Greenhouse Gas Estimates

In chapter 3, table 3.9 reports the estimated cost saving for the rest of New England (excluding Massachusetts) resulting from Massachusetts’s recent commitments. The corresponding estimates for the High and Low Renewables Cost cases and the High and Low Oil and Gas Supply cases are presented in table E.8.

Table E.8 Estimated savings for New England, excluding Massachusetts, due to Massachusetts’s commitments (in 2019 dollars)

Year	Price effect if incentivizing (cents per kWh)	Total annual savings, High Renewables Cost case (million $)	Total annual savings, Low Renewables Cost case (million $)	Total annual savings, High Oil and Gas Supply case (million $)	Total annual savings, Low Oil and Gas Supply case (million $)
2030	-0.0013	0.87	0.87	0.87	0
2035	-0.0044	3.00	0	3.00	0
2040	-0.0021	1.50	0	1.49	0
2045	-0.0044	3.22	0	0	0
2050	-0.0031	2.44	0	0	0

Source: USITC calculations.

Note: The price effect is calculated using the comparison of AEO estimated prices in the Reference case and the RPS Sunset case. The model assumes the same cent per kWh price effect in the other cases but zeroes out the total price effect when the policy is not incentivizing the addition of renewables. The calculation of the price effect is discussed further with equation (E6).

The total annual savings are calculated using the AEO projections for net energy for load for each scenario multiplied by the price effect per kWh. Because the price effect does not change between cases, the total annual savings are relatively constant across all five scenarios (including the Reference case).

In chapter 3, table 3.10 reports the estimated reduction in carbon dioxide emissions rates associated with the shift in electricity consumed within Massachusetts due to the new RPS and CES commitments, in million metric tons per MWh, and total carbon dioxide emissions reductions for each of the model years using data from the AEO 2020 Reference case. The corresponding estimates for the High and Low Renewables Cost cases and the High and Low Oil and Gas Supply cases are presented here in both millions of metric tons (Mmt), table E.9, and millions of metric tons per MWh (Mmt per MWh), table E.10.

Table E.9 Estimated effect of commitments on carbon dioxide emissions per MWh in Massachusetts, alternative scenarios (in million metric tons, Mmt, per MWh)

Year	Reference case	High Renewables Cost case	Low Renewables Cost case	High Oil and Gas Supply case	Low Oil and Gas Supply case
2030	-0.041	-0.041	-0.041	-0.042	0
2035	-0.039	-0.042	0	-0.043	0
2040	0	-0.044	0	-0.043	0
2045	0	-0.065	0	0	0
2050	0	-0.089	0	0	0

Source: USITC calculations.

Table E.10 Estimated effect of commitments on total carbon dioxide emissions in Massachusetts, alternative scenarios (in million metric tons, Mmt)

Year	Reference case	High Renewables Cost case	Low Renewables Cost case	High Oil and Gas Supply case	Low Oil and Gas Supply case
2030	-1.94	-1.95	-1.94	-1.99	0
2035	-1.91	-2.06	0	-2.10	0
2040	0	-2.23	0	-2.19	0
2045	0	-3.42	0	0	0
2050	0	-4.93	0	0	0

Source: USITC calculations.

Because the alternative cases are only adjusting underlying costs and supplies of resources, the reductions in emissions do not vary significantly from scenario to scenario for the years in which the policies are incentivizing. This is evident across the estimates in tables E.9 and E.10, with the Reference case estimates in 2030 and 2035 being very similar to those estimates in the alternative cases.

For the High Renewables Cost case, the reduction in emissions is forecast to increase over the timeframe of the commitments, both on a per-MWh basis and in total emissions reductions. The reduction in carbon dioxide emissions increases over time as the commitments become more ambitious through 2050. For the Low Renewables Cost case, on the other hand, the commitments are only incentivizing in the earliest projection year. For the High Oil and Gas Supply case, reductions in carbon emissions are very similar to the estimates for the High Renewables Cost case in the years in which the commitments are incentivizing (through 2040).

Sensitivity Analysis of Assumptions

In this section, the some of the model’s underlying assumptions are modified to provide sensitivity analysis for the results. Table 3.2 outlines the key assumptions used in the modeling that are relaxed in the following section. First, the chapter 3 estimates assume that marginal new renewable generation is from solar PV facilities; in the first subsection below, the cost to consumers is calculated for when wind is the marginal resource. Second, chapter 3 estimates assume that Massachusetts’s access to imports is proportional to its load as a share of total New England load; the second subsection below calculates the cost to consumers in the Reference case when Massachusetts has moderate, low, and no access to these imports. Finally, chapter 3 calculations of the monthly cost to consumers assume there is no growth in the number of residential and commercial customers in Massachusetts; the final subsection below presents the monthly cost to consumers when the number of customers is allowed to grow following a linear trend.

Wind as the Marginal Resource

The following set of estimates present an alternative scenario in which, instead of solar PV resources being the marginal resource filling Massachusetts’s RPS and CES commitments, onshore wind generation is the marginal resource. Tables E.11 and E.12 show the cost to consumers of the commitments, assuming the marginal commitments are filled by new onshore wind construction.

Table E.11 Estimated increase in per-unit cost to Massachusetts consumers with onshore wind as the marginal resource (in 2019 cents per kWh)

Year	Reference case	High Renewables Cost case	Low Renewables Cost case	High Oil and Gas Supply case	Low Oil and Gas Supply case
2030	0.072	0.089	0.012	0.082	0.009
2035	0.050	0.082	0	0.061	0
2040	0.020	0.192	0	0.047	0
2045	0	0.235	0	0.070	0
2050	0	0.184	0	0	0

Source: USITC calculations.

Table E.12 Estimated increase in total cost to Massachusetts consumers with onshore wind as the marginal resource (in millions of 2019 dollars)

Year	Reference case	High Renewables Cost case	Low Renewables Cost case	High Oil and Gas Supply case	Low Oil and Gas Supply case
2030	34.2	42.4	5.8	39.0	4.3
2035	24.5	40.5	0	30.1	0
2040	10.0	97.9	0	24.0	0
2045	0	124.4	0	36.9	0
2050	0	102.0	0	0	0

Source: USITC calculations.

Comparing tables E.11 and E.12 to tables 3.5 and 3.6, the results for wind show a significant departure from the predicted costs to consumers if solar is the marginal resource. Compared to the Reference case, wind being the marginal resource results in a cost to consumers about 75 percent higher than if solar is the marginal resource in 2030, and about 110 percent greater in 2035. Additionally, Massachusetts’s increased commitments continue to be costly to consumers in 2040, while if solar is the marginal resource they are not. These increasing differences between the cost to consumers when the marginal demand is satisfied by wind reflect the fact that the rate of overnight capital cost reductions from wind is slower than the rate of cost reductions for solar PV energy generation.^{^[36]}

For the alternative cases, however, the cost to consumers is lower when wind is the marginal resource both for the High Renewables Cost case and the Low Renewables Cost case. For the High Renewables Cost case, this is a result of the way that the AEO constructs the overnight cost of capital, as was discussed in the “Background on AEO Scenarios” section of this appendix (the High Renewables Cost case freezes the capital costs for solar and wind, leading to the price of solar never falling below the price of wind). For the Low Renewables Cost case, solar is less expensive to build than wind by around 2022 (see figure E.2), but the profitability of wind is still forecast to be greater through 2040 (see tables E.13 and E.14). As a result, the cost of the commitments is about 50 percent lower in 2030 with wind as the marginal resource. For the High Renewables Cost scenario, the commitments cost between 20 and 40 percent less over the projected time frame if wind is the marginal resource rather than solar.

Similar to the Reference case, commitments in the High Oil and Gas Supply and Low Oil and Gas Supply cases are higher across the board when wind is the marginal resource. The underlying structures of the Oil and Gas Supply scenarios do not make changes to the profitability of renewables, so it is unsurprising that the ranking of the resources does not change. The Oil and Gas Supply scenarios affect only the next-best resource.

Table E.13 and E.14 include the AEO’s projected profitability for the wind and solar as reference for the discussion in this section.

Table E.13 Profitability (average revenue minus average cost) of solar (photovoltaic) in New England for all scenarios (in 2019 dollars per megawatt-hour)

Scenario	2030	2035	2040	2045	2050
Reference	-3.87	-2.23	1.94	3.03	3.21
High Renewables Cost	-11.62	-11.04	-9.76	-9.51	-7.63
Low Renewables Cost	-2.43	1.09	4.32	5.94	6.95
High Oil and Gas Supply	-4.15	-1.73	-0.06	0.61	3.19
Low Oil and Gas Supply	0.30	4.59	7.80	8.71	9.01

Table E.14 Profitability (average revenue minus average cost) of onshore wind in New England for all scenarios (in 2019 dollars per megawatt-hour)

Scenario	2030	2035	2040	2045	2050
Reference	-6.97	-4.87	-0.60	0.53	1.55
High Renewables Cost	-8.65	-8.08	-7.51	-7.41	-4.33
Low Renewables Cost	-0.98	2.52	4.94	5.73	6.08
High Oil and Gas Supply	-7.91	-5.96	-4.31	-2.03	0.53
Low Oil and Gas Supply	-0.68	1.37	4.86	6.06	6.09

Varying Access to Imports

As discussed previously, the modeling elsewhere in the report assumes that Massachusetts receives 45.6 percent of New England’s total imports, since Massachusetts accounts for 45.6 percent of New England’s load. For this section, that assumption is relaxed, and the model examines how the results change if Massachusetts’s access to imports is lowered. This case reflects the fact that Massachusetts is geographically farther from Canada and New York State than the majority of other New England states.^{^[37]}

Lowering Massachusetts’s access to imports impacts the model through the CES commitments: when access to imports is low, Massachusetts will be filling a larger share of its CES commitments with the lowest-cost resource that fits into the clean or renewable category. As discussed earlier, the model uses solar PV generation as this resource.

For the Reference case, recall that the commitments are costly only to consumers for 2030 and 2035. In these periods, the difference between Massachusetts’s RPS and CES is small—5 percent in 2030 and 10 percent in 2035. Therefore, in those years, access to imports does not need to be large for hydroelectricity to be able to satisfy the entirety of the clean energy commitment.

The effect of varying access to imports for the High Renewables Cost case is provided as an illustration of the effect that imports have on the costs to consumers (tables E.15 and E.16). For the High Renewables cost case, reducing access to imports does not affect costs in the early years, as was also true for the Reference case. For the High Renewables Cost case with the baseline level of imports, recall that a small share of Massachusetts’s CES was met by renewables (reflected by the jump in the cost to consumers in 2040). If Massachusetts has moderate or low access to imports, then renewables are needed to meet CES commitments as early as 2040.

Table E.15 Estimated increase in per-unit cost to consumers of Massachusetts’s increased commitments, varying levels of access to imports, High Renewables Cost Case (in 2019 cents per kWh)

Year	Baseline imports (45.6 percent)	Moderate access (30 percent)	Low access (20 percent)
2030	0.119	0.119	0.119
2035	0.112	0.222^a	0.225^a
2040	0.249^a	0.254^a	0.259^a
2045	0.298^a	0.308^a	0.315^a
2050	0.299^a	0.317^a	0.331^a

^a A share of the Clean Energy Standard commitment above the Renewable Portfolio Standard is being met by renewable generation.

Source: USITC calculations.

Table E.16 Estimated increase in total cost to consumers of Massachusetts’s increased commitments, varying levels of access to imports, High Renewables Cost Case (in millions of 2019 dollars)

Year	Baseline imports (45.6 percent)	Moderate access (30 percent)	Low access (20 percent)
2030	56.5	56.5	56.5
2035	55.0	109.2^a	110.3^a
2040	126.6^a	129.5^a	131.7^a
2045	157.7^a	162.8^a	166.9^a
2050	165.9^a	175.5^a	183.5^a

^a A share of the Clean Energy Standard commitment above the Renewable Portfolio Standard is being met by renewable generation.

Source: USITC calculations.

As discussed in chapter 3 of this report, assuming Massachusetts has no access to imports results in a significant increase in the cost to consumers of Massachusetts’s increased commitments in many of the years of the model projections. The complete results of this estimation of cost to consumers are in tables E.17 and E.18.

Table E.17 Estimated increase in per-unit cost to consumers of Massachusetts’s increased commitments if Massachusetts has no access to imported hydroelectricity (in 2019 cents per kWh)

Year	Reference case	High Renewables Cost case	Low Renewables Cost case	High Oil and Gas Supply case	Low Oil and Gas Supply case
2030	0.064	0.180	0.042	0.068	0
2035	0.057	0.231	0	0.045	0
2040	0	0.270	0	0.024	0
2045	0	0.336	0	0.001	0
2050	0	0.374	0	0	0

Source: USITC calculations.

Table E.18 Estimated increase in total cost to consumers of Massachusetts’s increased commitments if Massachusetts has no access to imported hydroelectricity (in millions of 2019 dollars)

Year	Reference case	High Renewables Cost case	Low Renewables Cost case	High Oil and Gas Supply case	Low Oil and Gas Supply case
2030	30.2	85.6	19.9	32.4	0
2035	27.6	113.3	0	21.9	0
2040	0	137.4	0	12.1	0
2045	0	177.9	0	0.7	0
2050	0	207.2	0	0	0

Source: USITC calculations.

A discussion of the changes in costs as compared to the model estimates with access to imports (detailed in table 3.11) is in chapter 3.

Residential and Commercial Customer Growth

The following table reports the cost to consumers if instead of holding constant the number of retail and commercial customers at the 2018 levels, these numbers are allowed to increase following a linear trend based on Massachusetts retail and commercial customer growth observed between 1990 and 2018. This set of estimates would present a likely lower bound for the cost to consumers, whereas the estimates in tables 3.7 and 3.8 are an upper bound, as they assume a lower number of customers in each category. Tables E.19 and E.20 depict the results when residential customers and commercial customers grow according to the linear trend for completeness.

Table E.19 Estimated increase in the cost to residential consumers for high population growth, monthly cost per customer (in 2019 dollars)

Year	Reference case	High Renewables Cost case	Low Renewables Cost case	High Oil and Gas Supply case	Low Oil and Gas Supply case
2030	0.24	0.70	0.16	0.26	0
2035	0.14	0.67	0	0.11	0
2040	0	1.50	0	0.01	0
2045	0	1.82	0	0	0
2050	0	1.85	0	0	0

Source: USITC calculations.

Table E.20 Estimated increase in the cost to commercial consumers for high population growth, monthly cost per customer (in 2019 dollars)

Year	Reference case	High Renewables Cost case	Low Renewables Cost case	High Oil and Gas Supply case	Low Oil and Gas Supply case
2030	1.60	4.71	1.04	1.73	0
2035	0.90	4.29	0	0.72	0
2040	0	9.34	0	0.05	0
2045	0	11.12	0	0	0
2050	0	11.25	0	0	0

Source: USITC calculations.

[1] Summarized in more detail in a footnote at the beginning of chapter 3.

[5] Knight et al., An Analysis of the Massachusetts Renewable Portfolio Standard, May 2017, 24. More information on the supply-side commitments of the 2016 Act are available in a footnote at the beginning of this chapter.

[12] The Class II RPS did not change after 2016, so Class II commitments are not part of the estimated effects of the policy changes in 2017–19. For more information about Massachusetts’s Class II commitments, see chapter 2 of this report.

[13] References to “renewable” and “clean” in this appendix refer to resources eligible for the Massachusetts commitments specifically. This means, for example, that large-scale hydroelectricity is considered clean but not renewable. See chapter 2 of this report for more details on qualifying sources of electricity under Massachusetts’s commitments.

[14] Again, note that the old RPS commitments, S_o, and the updated RPS commitments, S_u, represent the Class I commitments by Massachusetts, which also qualify for the CES commitments. Massachusetts’s Class II commitments, which account for approximately 6 percent of total sales, do not qualify to fill the clean energy commitments in the CES, which is why the modeling examines the resources that will potentially fill the share S_c – S_u. For further discussion of the classes of resources in Massachusetts’s commitments, see chapter 2 of this report.

[17] International transmissions connections have historically been very stable. For example, the last transmission line between New York or New England and Quebec was constructed 30 years ago (though it is worth noting there are plans underway to expand transmission between the regions). Hydro-Québec, written submission to USITC, August 7, 2020, 39. Again, our model is not considering the effects of any existing or potential contracts to expand transmission. However, such contracts could increase Massachusetts’s access to imports.

[18] EIA projects that the LCOE will be far greater for hydroelectricity and nuclear than for wind and solar in 2025 in the United States. EIA, “Levelized Cost and Levelized Avoided Cost of New Generation Resources in the Annual Energy Outlook 2020,” February 2020, 7.

[20] EIA, Annual Energy Outlook 2020: LACE (available from EIA on request; accessed October 2, 2020); EIA, Annual Energy Outlook 2020: LCOE (available from EIA on request; accessed October 2, 2020). As discussed in chapter 3, and in box 3.2 specifically, the RPS Sunset case provides an additional rationale to assume that solar will grow to meet Massachusetts’s commitments.

[23] Biello, “Nuclear Reactor Approved,” February 9, 2012.

[24] U.S. Energy Information Administration, “Annual Energy Outlook 2020, Full Report,” January 29, 2020, 5.

[27] EIA, “Annual Energy Outlook 2020: Case Descriptions,” January 2020, 5–6. EIA defines technological improvements here as improvements that may lead to the development of crude oil and natural gas resources that have not yet been identified.

[29] Box 3.2 provides additional discussion of the RPS Sunset case, including how its projections compare to the Reference case results.

[30] Note that this is reflected in table 2.5 in chapter 2, which shows that natural gas supplies the largest share of generation in Massachusetts.

[32] ISO New England, “Net Energy and Peak Load by Source” (accessed March 24, 2020); EIA, “State Electricity Profiles” (accessed March 24, 2020).

[34] Calculations for LCOE (and LACE) include state and federal tax incentives, state-level renewable energy targets. EIA, “Levelized Cost and Levelized Avoided Cost,” February 2020, 4–5.

[35] EIA, Table 8: Retail Sales (accessed September 15, 2020).

[36] See discussion of figure E.2 or table 3.2.

[37] Massachusetts does not share a border with Canada and borders the downstate portion of New York’s electricity grid (which has significantly less hydropower than the upstate portion; see chapter 4 for more discussion of New York’s electricity market).