Converting SEER to EER for Peak Forecasting

Transcription

1 Converting SEER to EER for Peak Forecasting Itron s Annual Energy Forecasting Meeting Andrew Gledhill, PJM

2 Agenda PJM Adoption of End-Use Modeling Practices SEER vs EER: Why the Efficiency Term Used Matters Converting SEER to EER Results in PJM References 2

3 Breakdown in Accuracy PJM s original methodology used economics as a primary driver. As the elasticity of load to economics weakened, so did model performance. Investigated new variables to help explain the growing disconnect. 3

4 Equipment Indexes Create equipment variables across three usage categories: Heating, Cooling, and Other. (1) Develop Residential and Commercial sector indexes (2) Weight sector indexes and combine into single variables Each index is a weighted average across equipment types of saturation normalized for efficiency 4

5 Cooling Equipment Index Within the Residential Component of Cooling, there are four types: Central Air Conditioners, Air-Source Heat Pumps, Geothermal Heat Pumps, Room Air Conditioners The latter two use the Energy Efficiency Ratio (EER) to measure efficiency, whereas the former use the Seasonal Energy Efficiency Ratio (SEER) While investigating PJM s proposed model changes, Navigant indicated that the use of SEER might be an issue and provided guidance to correct the problem. 5

6 SEER vs EER: Why does it matter? PJM s goal is to forecast load under system peak conditions, not average conditions. This is at odds with the purpose of the SEER measure: SEER measures seasonal average performance EER measures performance at a single outside temperature of 95 degrees If there s a significant difference, then it could lead to a bias 6

7 SEER vs EER A typical 13 SEER unit has an EER of 11 (a 0.85 ratio) A typical 18 SEER unit has an EER rating of 13 (a 0.72 ratio) Improvements in average performance don t necessarily translate to peak period performance at the same rate. 7

8 SEER vs EER Conversion Different relationships used before and after 2006 In each case, median units are considered. Data is fit with a second order polynomial to account for declining EER to SEER ratio 8

9 SEER to EER Conversion Framework New Cooling Units Stock of Cooling Units Retiring Cooling Units 9

10 SEER to EER Conversion: Determine the moving parts Total Units (given) Function of number of households and the saturation rate Retired Units Retire units from the total at a rate according to their average lifetime (19 years in the case of central A/C units) New Units Equal to growth in total units plus retired units 10

11 SEER to EER Conversion: Establish SEER of cooling units SEER of all units (given) Changes over time are a function of: Efficiency of total units in prior period (given) Efficiency of retiring units exiting from the prior period Assume to be average Efficiency of new units coming in from the prior period Can be inferred algebraically from the below identity Avg_SEER t x Total_Units t = (Avg_SEER t-1 x Total_Units t-1 ) (Avg_SEER t-1 x Retired_Units t-1 ) + (Avg_New_SEER t-1 x New_Units t-1 ) 11

12 SEER to EER Conversion: Translating SEER to EER Transform SEER of new units into EER using conversion equations Translation is then done using a recursive process Establish base year EER (1995) using SEER-EER conversion equations EER values can then be calculated going forward using the formula: Avg_EER t x Total_Units t = (Avg_EER t-1 x Total_Units t-1 ) - (Avg_EER t-1 x Retired_Units t-1 ) + (Avg_New_EER t-1 x New_Units t-1 ) 12

13 Impact on Efficiency In our model, EER-based measures produce slightly more accurate results in our historical testing. The five-year forecasted annualized growth rate of SEER is 0.9% versus 0.6% for EER 13

14 Impact on PJM Load Increases forecasted load by % at the outset of the forecast, and by just under one percent 15 years from now. In PJM, this amounts to approximately MW 14

15 References Air-Conditioning, Heating, and Refrigeration Institute U.S. DOE Technical Documentation (pre-2006 EER-to-SEER) (Chapter 4; Table 4.27) PJM Load Analysis Subcommittee PJM Load Forecasting Model Whitepaper load-forecast-whitepaper.ashx 15