program plan - Entergy New Orleans, Inc.

• Customer sales data
• Public data mining including:
• Federal Reserve Bank data
• CBECS and RECS
• Energy Information Administration (EIA)
• The US Census Bureau
In the Best Practices Review, CLEAResult collected data on program portfolio performance and spending
for a sample of 12 utilities. The analysis reviewed utilities of comparable size, as well as regional utilities
operating in comparable markets. In addition, the assessment included utilities located in developed energy
efficiency markets. The 2014 – 2017 DSM portfolio was compared against these utilities in terms of its
economic efficiency ($/kW, $/kWh), equitability ($/customer), and sophistication (program types offered).
Data sources in the Best Practices Review were:
• Investor-Owned Utility DSM program plans and annual reports
• The Energy Information Administration (EIA)
• E Source
Measure Selection, Characterization & Screening
CLEAResult developed a preliminary measure list based on the three year Energy Smart program history,
the best practices assessment and our understanding of the local market derived from the Market Profile
and the 2012 IRP appendices. These measures were then screened by the project team engineers and
analysts, using a comprehensive measure screening process that considers each measure’s engineering
characteristics
• Savings Potential: Using the Energy Smart Deemed Savings, Installation and Efficiency
Standards, we developed measure savings assumptions that account for all engineering
characteristics (e.g. hours of use, applicable building types etc.).
• Local Market Applicability: Given the local program implementation history, we considered the
participation likelihood based on the building types and end-uses located within the ENO and ELL-
Algiers territory, and for existing measures, the performance of the measure over the initial three
year Energy Smart implementation cycle. For both new and existing measures we reviewed measure
performance in comparable markets relying on CLEAResult’s national implementation expertise
and internal proprietary datasets.
• Cost-effectiveness: We evaluated the incentives and measure costs to develop measure level cost
effectiveness results, which were used to screen-out underperforming measures.
With numerous code changes going into effect in 2014, our analysis also considered the baseline changes
affecting measures included in the portfolio; primary baseline changes are outlined in the table below.
Table 4: Primary Baseline Changes Affecting the 2014 - 2017 Portfolio
Measure
Current Baseline as of
March 2013
Change
Date
Baseline Change
Residentia
l
Water heater
40 gal
Water heater
50 gal
0.92 EF 4/16/2015 0.95 EF
0.90 EF 4/16/2015 0.95 EF
9 | P age