3 pages plus data and exhibits.
REI Solar Energy Program Case Overview REI (Recreation Equipment Inc) is a co-operative outdoor equipment store. It has a strong stewardship mission (https://www.rei.com/stewardship), which makes sense since its equipment is mostly for outdoor activities. Its approach to energy is: Sustainable energy use is part of protecting the outdoors. We take a straightforward approach: · Seek to use less energy through good building design and energy-efficiency measures. · Generate our own energy (e.g., rooftop solar panels). · Contract directly with utilities for long-term renewable energy. · If needed, commit to purchasing Green-e® certified renewable energy certificates for the remainder of our energy from the grid. Source: https://www.rei.com/stewardship/climate-change In 2008 REI made its first investment in PV solar, equipping 11 stores with panels. This case is set in 2011, when RIE is considering expanding its investment in PV solar. The case discusses the method that REI financial analysts use to complete the capital budgeting analysis. About REI's Carbon Footprint REI's goal is to be carbon neutral in its operations by 2020. Here are two graphs from its website that track its progress. These are for today, not 2011, so are not entirely relevant to the case. In case you cannot read the methodology image, you can find it at (See attachment REI Footprint Methodology). It is important recognize that REI has, as of 2018, done about as much a possible internally to reduce its GHG (greenhouse gas) emissions. Notice that remaining emissions are from third-party transportation (employee commuting, product transport to REI then to customers). You might think that REI has some control over how its employees get to work but changing people's behavior in this realm is hard. Everyone is busy and have arranged commuting to be as efficient as possible for their sets of demands (kids to school, doing errands on the way home from work, leaving at the last minute to have more sleep time, more daily time, etc.) Supporting this notion is a Harvard Business Review article (See attachment). Background on Carbon Footprints: The standard that most companies use to calculate their carbon footprint is based on the Greenhouse Gas Protocol's Corporate Accounting and Reporting Standard (See attachment ghg protocol). It covers 7 greenhouse gases or families of gases. They are: · carbon dioxide (CO2) · methane (CH4) · nitrous oxide (N2O) · hydrofluorocarbons (HFCs) · perfluorocarbons (PCFs) · sulfur hexafluoride (SF6) · nitrogen trifluoride (NF3). The GHG Protocol approach separates emissions into 4 scopes. Scope 1 are emissions from fuels used in company assets. Examples are gasoline used in cars or trucks, kerosene used in planes, natural gas used in boilers or furnaces. The key is that the company buys the fuel and combusts it in its owned or leased assets where the emission then occurs. Clearly, Scope 1 emissions are totally under the company's control since it can choose its assets (think cars, trucks, HVAC systems, etc.) that are more or less efficient, and it also determines how much those assets are used. Scope 2 emissions are primarily the emissions from the generation of electricity that the company uses. In some place’s companies buy steam, so the emissions from generating steam that is transported and sold to companies can be another source of Scope 2 emission. Mostly, though, it is electricity generation that is associated with Scope 2 emissions. Scope 2 emissions are further divided into market-based and location-based emissions. This is a little bit of a stylized interpretation, but it is close to actual one. Location-based emissions are the emissions if all the electricity the company used was brought from the utilities serving the company's various locations. Different regions use different mixes of fuel to generate electricity. In the NW there is lots of hydropower, so a KwH of electricity has very low CO2 emissions. In Colorado there is still coal used, especially if the power is from Tri-State (but that is changing). Here are data from EPA's most recent eGrid database (See eGrid attachment) based on 2018 data. State CO2 lbs/KwH AK 0.91 AL 0.86 AR 1.21 AZ 0.97 CA 0.42 CO 1.36 CT 0.51 DC 0.44 DE 0.90 FL 0.94 GA 0.93 HI 1.51 IA 1.07 ID 0.16 IL 0.81 IN 1.74 KS 0.99 KY 1.82 LA 0.84 MA 0.73 MD 0.84 ME 0.26 MI 1.11 MN 1.00 MO 1.70 MS 0.92 MT 1.16 NC 0.80 ND 1.51 NE 1.41 NH 0.30 NJ 0.50 NM 1.33 NV 0.74 NY 0.42 OH 1.32 OK 0.89 OR 0.31 PA 0.78 RI 0.87 SC 0.63 SD 0.52 TN 0.74 TX 0.98 UT 1.60 VA 0.74 VT 0.05 WA 0.20 WI 1.39 WV 1.95 WY 2.05 U.S. 0.95 Location-based Scope 2 emissions would compute emissions as if electricity came from the grid using emissions from the suppling utility. Market-based Scope 2 emissions are the actual emissions that occurred over the reporting period, usually one year. These can differ from location-based emissions because companies can establish PPAs (Power Purchasing Agreements) with a wind farm to buy renewable energy or it can generate its own electricity from roof-top solar. Usually market-based emissions will be less than location-based emissions. You might ask why bother with this location versus market distinction. It is a way for companies to show how their procurement activities have affected their carbon footprint. By having a standard for the two types of Scope 2 emissions it lets interested parties see whether a company is pro-active about reducing its CO2 emissions. Finally, Scope 3 emissions are everything else. The REI pie chart gives good examples of the most common Scope 3 emissions: transport of goods by third party contractors, employee travel, and employee commuting. What isn't included are GHG emissions from the production of products by suppliers, the emissions from the use of the product, emissions from the disposal or end-of-life treatment of the product, emissions from land use activities like deforestation, emissions from livestock (largely methane) and probably a bunch of other sources that are sector-specific. Assignment The case must include the sections: Executive Summary, Statement of Problem, Analysis, and recommendations. The case presents the analysis of the Phase 2 PV solar investment in Exhibit 6. It is based on the discussion in the case and Exhibits 3, 4, and 5. The end result are several IRRs for different assumed project time horizons. These range from -5% to 17% depending on the time horizon used. IRRs are used because there was no discount rate given. Of course, to decide if an IRR is acceptable you have to have an implied discount rate to use as a hurdle rate: If the IRR is greater than the hurdle rate the project is acceptable. For this assignment I would like you to read through the methodology used and revise or confirm the analysis. Here are some things to think about to get started. You may identify other issues that would suggest a revision in the Exhibit 6 analysis. · Is the electricity price correct? · Is the price inflator correct? · What about the other inflation assumptions? · How much have electricity prices changed in the last 10 years? · REI had to give the RECs to the utility. Can REI still say it is lowering its carbon footprint? · Should the energy savings be taxed? · What is the appropriate time horizon? · REI has stores in many states. Is this blended or average analysis the best approach? Once you have identified what you think are the right set of assumptions, revise the financial analysis in Exhibit to reflect your assumptions. In a report of about 3 pages, explain your assumptions (maybe in a bulleted list with the topics in my list above) and why they are better than those used in the case. If you liked a case assumption, say so. Conclude your report with the IRR you computed and compare it to those in the case (-5% to 17%). Finally, explain what your result means in terms of REI's decision to pursue this investment. In an appendix (beyond the 3-page limit) show your revised analysis. A 20-year spreadsheet will be difficult to fit onto a page, so show years 1-7 and 19 and 20 (Leave out years 8 through 18). In MS Word you can insert a Section Break (New Page) then change the page format from portrait to landscape to get more width. Make sure the table is readable. Contents Table of Contents for eGRID2018_Data_v2.xls eGRID2018 Unit, Generator, Plant, State, Balancing Authority Area, eGRID Subregion, NERC Region, U.S., and Grid Gross Loss (%) Data Files March 9, 2020February 27, 2020February 27, 2020February 27, 2020February 27, 2020February 27, 2020February 27, 2020February 27, 2020February 27, 2020February 27, 2020 SheetNameDescription 1UNT18Unit year 2018 data 2GEN18Generator year 2018 data 3PLNT18Plant year 2018 data 4ST18State year 2018 data 5BA18Balancing authority area year 2018 data 6SRL18eGRID subregion year 2018 data 7NRL18NERC region year 2018 data 8US18U.S. year 2018 data 9GGL18Grid Gross Loss (%) year 2018 data Updates to eGRID2018v2 • CH4 and N2O input emission rates and fuel specific emission rates updated to correct values for the plant, state, balancing authority, eGRID subregion, NERC region, and U.S. levels. • The plant unadjusted annual Hg emissions source has been updated to the correct value (previously stated EPA/CAMD for all plants when it should have been "--"). • A typo in the listed conversion factor for MWh to GJ was corected on the Contents page (this did not affect any eGRID calculations). Feedback Customer Satisfaction Survey Contact EPA Color Coding Legend CategoryColorLink to sheet and category 1) Annual Values (generation, emissions, and heat input)GENPLNTSTBASRLNRLUS 2) Unadjusted Annual Values (emissions, and heat input)UNTPLNT 3) Adjusment Values (emissions, heat input, heat rate)PLNT 4) Output Emission Rates (emissions per MWh)PLNTSTBASRLNRLUS 5) Input Emission rates (emissions per MMBtu)PLNTSTBASRLNRLUS 6) Combustion Output Rates (emissions per MWh)PLNTSTBASRLNRLUS 7) Generation by Fuel Type (MWh)PLNTSTBASRLNRLUS 8) Renewable and Non-Renewable Generation (MWh)PLNTSTBASRLNRLUS 9) Combustion and Non-Combustion Generation (MWh)PLNTSTBASRLNRLUS 10) Resource Mix (percentages)PLNTSTBASRLNRLUS 11) Renewable and Non-Renewable Resource Mix (percentages)PLNTSTBASRLNRLUS 12) Combustion and Non-Combustion Resource Mix (percentages)PLNTSTBASRLNRLUS 13) Output Emission Rates by Fuel Type (emissions by fuel type per MWh)STBASRLNRLUS 14) Input Emission Rates by Fuel Type (emissions by fuel type per MWh)STBASRLNRLUS 15) Nonbaseload Output Emission Rates (emissions per MWh)STBASRLNRLUS 16) Nonbaseload Generation by Fuel Type (MWh)STBASRLNRLUS 17) Nonbaseload Resource Mix (percentages)STBASRLNRLUS Notes Values in parentheses are negative numbers. Dashes (-) are zeroes. Conversion Factors 1 megawatt-hour (MWh)1,000 kilowatt-hour (kWh) 1 short ton2,000 pounds (lb) 1.10231 short ton 1 metric ton 2.2046 lb1 kilogram (kg) 0.9478 MMBtu 1 Gigajoule (GJ) 1 MWh3.6 GJ Citation United States Environmental Protection Agency (EPA). 2020. “Emissions & Generation Resource Integrated Database (eGRID), 2018.” Washington, DC: Office of Atmospheric Programs