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Community Choice Aggregation Feasibility Analysis Alameda County <br />June, 2016 34 MRW & Associates, LLC <br />How Job Impacts Are Measured <br />The scenario-specific elements described in the prior section are expressed as annual dollar amounts (plus or minus) in comparison to what would have been expected in the county <br />economy without a CCA. Initially these amounts supplied by MRW and Tierra are general, <br />representing total project cost by year. The annual investment for specific types of renewable <br />energy projects and of making further energy-efficiency improvements are really comprised of <br />some portion spent on installation labor, a large portion for the equipment (either manufactured in the region or if not, a leakage to imports), and some small portion soft project costs. These <br />details are necessary for modeling impacts on the county economy due to a CCA program. <br />A macroeconomic impact (industry) forecasting model of Alameda County41 is used, the dollar <br />amounts, with further data refinement (detail) are introduced to the model, the economy adjusts <br />to these spending and savings changes by year and then identifies annual impacts in terms of dollar concepts (wages, sales, prices, gross regional product) and jobs, among numerous other <br />metrics. Appendix E provides some high-level background on the REMI Policy Insight model. <br />This model was chosen since it is uniquely qualified over other models and approaches to <br />understand how price (or rate) changes on the business segment (Commercial /Industrial energy <br />customers) influence business activity levels. Since electric rate differentials are a key consideration in pursuing a CCA, the study required a method that would adequately address <br />this. <br />Scenario Results <br />MRW created the three supply scenarios by considering how much within county RE investment <br />(for future generating assets) the CCA could fund, and how much it might invest elsewhere in <br />California (rest of California or roCA). Program administration and energy efficiency deployment investments are the same in all three scenarios. As can be seen from Table 17, scenario 3 has the most proposed CCA renewables investment within county but, it has the <br />lowest bill savings. In contrast scenario 1 would site a smaller renewables investment by the <br />CCA as within county, but has proportionally much higher bill savings. <br /> <br /> <br /> <br /> <br /> <br /> <br />41 The model is a Policy Insight model by Regional Economic Models, Inc. (REMI) of Amherst, MA. It is a model that has been used by the CA Energy Commission, CALTrans, Los Angeles MTA, ABAG, City of San Francisco, <br />and the South Coast AQMD. For this study a two-region socio-economic forecasting model (the county, and balance of State) with 23- industries was used.