I. Research Methods. for renewable energy generation, in order to encourage greater deployment of distributed PV. The

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I. Research Methods In order to effectively organize and evaluate this research, the case method will be used to examine how local governments and utility providers can integrate their existing financial incentives for renewable energy generation, in order to encourage greater deployment of distributed PV. The case method allows multiple types of evidence to be collected in the investigation of organizational and managerial characteristics. By definition, a case study is an empirical inquiry that investigates a contemporary phenomenon within its real-life context, especially when the boundaries between phenomenon and context are not clearly evident (Yin, 2003). The case study approach was chosen for this thesis because it is a comprehensive research strategy that will explore the relationship between incentive structures and willingness of a consumer to invest in distributed PV systems. Since the influential boundaries of the incentive structures are not well defined, the case study method will provide the framework to effectively analyze this behavioral phenomenon. A formally prepared research design, as outlined in Table 3, will be used to conduct the research. Table 3. Components of the Research Design Research Question How can local and state governments can improve financing incentives to encourage development of distributed PV systems? Research Hypothesis Financing programs for distributed solar systems can be optimized through a combined use of state credit enhancement programs, and utility administered financing programs such as PPAs, RECS, and on-bill financing. Unit of Analysis Consumer decisions on distributed solar installations. Date Interpretation Cross Case Analysis with Pattern Matching by quantifying nonequivalent, Techniques dependent variables from four cases (Yin, 2003) Citeria for Interpreting Data Construct validity, internal validity, external validity and reliability (Yin, 2003).

The research design includes a research question, research hypothesis, techniques to address internal- and external validity, and criteria for interpreting the evidence. This formal approach to research design will improve the validity and reliability of the research. Additionally, it enables other researchers to better replicate its results or continue expanding it. In order to analyze and test the hypothesis presented above, this research will construct from six commonly used sources used by the case study method: documentation, interviews, archival records, direct observations, participantobservations, and physical artifacts (Yin, 2003). The use of multiple sources of evidence, as outlined in Table 4, will provide supporting analysis for the case study and the evaluation of the research hypothesis. Table 4. Sources of Evidence Documentation Relevant peer reviewed scholarly articles Research reports from government agencies and industry organizations State Legislative Documentation Industry and corporate white papers Archival Records National historical energy consumption (EIA) Data aggregators (e.g., DSIRE) Interviews Government agency representatives (e.g., Clean Energy States Alliance) Varying local utility providers (CL&P, NSTAR) Industry experts Direct Observation n/a Participant Observation n/a Physical Artifacts n/a To further supplement the collection of evidence, interviews of leaders in the public financing industry will be conducted using the interviewing methodology outlined in Stewart & Cash. Interviews will be used to complement and support the evidence and provide further clarity as necessary (Stewart & Cash, 2007). The researcher will apply for an exemption from the committee of Human Subject on the Use of Human Subjects at Harvard University before any formal interviews are conducted.

Four cases will be analyzed in order to test the research hypothesis presented in Figure 2. Two critical factors were chosen to define the four cases examined. The first of these factors is the level of participation by the local utility provider to provide incentives, such as on-bill financing. The second factor is the level of additional state financial support for distributed PV, through credit mechanisms like loans and guarantees. The combination of these two supplemental incentive structures will be the defining factors by which the unit of analysis could be altered in this research. Figure 2. Case Quadrants used to test Hypothesis High Financial Involvement of Utility Providers Low Case 2 Incentives from Utility Providers - Scenario analysis would consider the effectiveness and the potential advantages/disadvantages for additional incentives from utility companies. Case 1 Business as usual (BAU) - the federal and state government do not provide any new financial incentives for distributed solar generation. Low Additional Financial Involvement from State Case 4 Incentives from Utility Providers and State Loans/Guarantees - Scenario analysis would evaluate the leveraged effect of both financing structures on deployment of distributed PV. Case 3 State Loans and Guarantees - Scenario analysis would evaluate the effect of state and local governments providing additional financial support through a variety of credit mechanisms. High As described in Figure 2, the research design will be based on four cases that will evaluate the level of involvement and financial support of either the state or utility providers. Case 1, represents a business-as-usual scenario where the current levels of traditional state incentives will remain and no additional incentives will be offered. Case 2, will consider a change to the incentive structures by providing additional funding support through on-bill financing for customers. Case 3, will further consider the additional funding support to come from the state level through loans, such

as PACE programs, and also through loan guarantees. Lastly, Case 4 will provide an allencompassing view of cases 2 & 3, which would leverage the additional funding support through utility providers and state loan programs. The case studies analysis will be completed through qualitative and quantitative analysis. The qualitative analysis will be conducted through the use of exploratory and analytical scenarios, using the eight step guidance process from Schwartz (1996). This scenarios process involves identifying, prioritizing, and negotiating the most interesting, uncertain, and important elements of the contextual problem. The development of scenarios is one of many possible methodologies used to elaborate the underlying tensions underlying our current incentive programs and it present opportunities for change. Scenarios are distinct from forecasts in that they explore a range of possible outcomes resulting from uncertainty; in contrast, forecasts aim to identify the most likely pathway and estimates uncertainties. To better understand the driving forces between the various state and utility incentives, branches as depicted in Figure 3, will be constructed to add to the storyline composition of each scenario. Figure 3. Scenario Branch Yes Will utility companies play a more critical role in financing PV installations? Yes No Budi On-Bill Financing, State loans, guarantees, Budi etc. Yes Do state governments need more than cash & tax incentive? No State Budi Bond/Grant Funded Will state level incentives in increase the deployment of distributed PV? No Budi Federal Support

This research will focus on the interrelationship between state and utility level incentives, and how each incentive competes or complements each to encourage greater deployment of distributed PV. To accomplish this qualitative analysis, first a focal issue and key forces will be identified. Then, driving forces will be determined and ranted by importance and uncertainty. Once the driving forces are understood, scenario logics will be selected and implemented. To provide a quantitative context into the scenario narratives, the scenario-based modeling platform, Long Range Energy Alternative Planning System (LEAP), will be used to create an enduse model of distributed solar energy supply and demand in the U.S. The LEAP model will then be layered with various federal and state incentives to determine the aggregate level of funding needed to reach a market saturation of distributed PV installations. The research will follow a planned sequence defined as research protocol on Figure 4. Figure 4. Research Protocol DEFINE DESIGN DATA ANALYZE EVALUATE and CONCLUDE Research Question and Hypothesis Indentify Cases Collect Evidence for Case 1 Analyze & Discuss Cases 1 thru 4 Conduct: Cross Case Analysis, Pattern Matching Initial Literature Review Establish unit of analysis Collect Evidence for Case 2 Modify Hypothesis Based on Results from Case Studies Establish data collection protocol Collect Evidence for Case 3 Evaluate Develop Conclusions & Recommendations Identify interview candidates and develop interviews Collect Evidence for Case 4 Write Cross Case Analysis Check logical consistency for construct validity

The research will start with literature review, and the definition of a research question and hypothesis. After design of cases and data collection is concluded, the research will analyze each case separately and discuss the characteristics of each. A cross-case analysis will be applied to assess the similarities and differences between each case situation. Finally, cross-case analysis will be used to compare evidence and test the hypothesis. Using the case study method, paired with scenarios and quantitative models described above, the goals of this research is not to affirm what is already known, rather it is to explore the many ways local governments and local utility providers could leverage their financial incentives and co-evolve to provide the most effective financial support for distributed solar customers.

II. Limitations of Methods This research is subject to potential limitations that may affect the research scope and quality. The most probable of those limitations are bias, data availability, data access, and time and resource constraints. Throughout this research process, efforts will be made to identify and eliminate the limitations as discussed herein. The case study methodology will serve as the initial tool for providing research techniques so as to help identify and minimize limitations. Using multiple sources, establishing a chain of evidence, and review by a thesis director of the case study report, will allow the research to pass the test of construct validity (Yin, 2003). The research will also ensure documentation containing all perspectives on the thesis topic will be considered, and crossreference it to provide even representation of evidence. The first limitation this research will most likely be exposed to is bias. The field of sustainability in today s media is portrayed vehemently in a variety of ways, and the methods to reducing climate change have not been agreed upon. It is probable that interviewees will have a bias on the way renewable energy funding should be allocated, and whether it is the consumers, polluters, or state s responsibility to fit the bill for climate change mitigation strategies. In addition, the researcher is subject to bias as they are currently a Masters candidate in the field of Environmental Management and Sustainability. The second highly influential limitation will come from limited data availability. While the range of available financing programs is largely identified in industry reports, their effects and implementation rates are not consistently reported on. Due to their fairly recent development, some financing programs may also have unintended results that may have not been reported or discovered, but may prove to be an influential factor in determining the program s success. Additionally, limitations in this research may originate from out-of-date information given the continually evolving

regulatory systems, and continually refined industry reports which may change baseline statistics. The value of incentives is likely to alter within a short amount of time, as set by local statutes, and as they are influenced by the financial market servicing the clean energy industry. For example, the price of PV modules has varied recently in light of the economic slowdown and a significant oversupply of PV modules in the market. This ever changing statistic may drastically impact the effectiveness of financing program, as the baseline for the analysis may change throughout the research period. Furthermore, quantitative methods can also be a limiting factor, as errors can be made in establishing assumptions and calculation metrics. The researcher also has a limited timeframe and limited understanding on the entirety of this thesis topic, which may cause some elements of the analysis to not be addressed in its entirety. While the research will make every efforts to conduct thorough literature review and consult with industry professionals, not having full exposure to the inner workings of public financing policies may limit the scope of this analysis. The researcher may also be limited in their ability to attain the proper interviewees to provide a high level understanding of public financing mechanisms. The access to this background data may in turn limit the scope of the scenarios and the quantitative analysis. Lastly, the researcher also has limited funding to complete the research, which would prohibit them for using a more opinion-based research tool such as a survey. Many industry reports address program advantages and disadvantages from a theoretical perspective, however not all of the effects are further evidenced by opinion polls and surveys which would provide a more practical analysis of a program s success/failure. Additionally, this research paper does not address a variety of non-financial influential factors that contribute to a customer s decision to purchase PV. These factors may include but not be limited to, ease of installation, building aesthetics, marketing and social influences.