E-12022 Rate and Bill Impact Analysis
20 passages
Cumulative and annual participation Each year, E1 combines participant records (for programs that track participant information) with participant records from previous years. In this way, E1 can identify the first year that a customer part...
AI summary E1 tracks cumulative and annual participation by combining records and using transaction data and scaling factors. For some programs, Guidehouse's ProCESS model is used, while others rely on 2021 data scaled by energy savings and product rebates. Custom Incentives use different assumptions.
Figure 2: Average Rate Impacts (2011-2039) as a Result of DSM Activities in 2011-2025 - [Figure 3](#page-29-0) illustrates the annual rate effects (difference between the no-DSM scenario and the DSM - scenario for each year), assuming that...
AI summary Figure 2 and Figure 3 analyze average rate impacts from 2011-2039 due to DSM activities, highlighting that annual rate changes are influenced by DSM cost recovery and avoided cost fluctuations. The annual impacts in Figure 3 are clarified as not reflecting actual customer rate changes experienced.
4.2 OVERALL BILL IMPACTS - Generally speaking, those ratepayers that participate in DSM programs most directly benefit - from DSM programs by reducing their electricity consumption and thereby lowering their - electricity bills. Together,...
AI summary The 2022 RBIA analysis shows DSM programs reduce electricity bills for participants by -10.2% to -1.9%, while non-participants see minor savings or increases (-0.03% to +2.4%). Total customer bill impacts range from -8.9% to -1.9%, with $2.5 billion in savings for Nova Scotia ratepayers over 2011-2039. Lower-consumption classes benefit more from efficiency measures.
Figure 5: Average Bill Impact (2011 – 2039) as a Result of DSM Activities in 2011-2025 When examining non-participant bill impacts, it is important to note the broad reach of E1's point-of-sale rebate program components, Instant Savings an...
AI summary The text discusses the impact of E1's rebate programs (Instant Savings and BER-IR) on non-participant and participant bill savings. It highlights that participation rates are high across customer classes, making non-participant scenarios rare. Non-participant results represent minimum savings, while participant results reflect average savings, with some participants achieving higher savings.
4.3 OVERALL PARTICIPATION IMPACTS Figures 6 through 9 present actual participation for 2011-2021 and estimates for 2022 through 2025. Two types of participation figures are presented – tracked and untracked. Tracked participants are those...
AI summary The text discusses participation data from 2011-2025, distinguishing tracked (direct contact with E1) and untracked (point-of-sale programs like BER-IR and Instant Savings) participants. Tracked data is based on actual tracking, while untracked is estimated. Cumulative participation is shown in figures 6 and 7.
Figure 7: Cumulative Participation Rates by Rate Class (tracked + untracked) E1 employs the assumption that all customers in the Large General, Medium Industrial, Large Industrial and Municipal classes participate in BER-IR each year, so t...
AI summary Figure 7 shows cumulative participation rates by rate class, with E1 assuming 100% annual participation for Large General, Medium Industrial, Large Industrial, and Municipal classes in BER-IR. Other classes show steady participation growth since 2011. Figures 8 and 9 detail annual rates.
4.4.2 SMALL GENERAL • As modelled, the Small General class includes Rate Code 10 only. • The average rate impact over the study period is an increase of 3.0 percent, or 0.41 cents/kWh. • Participants in the Small General class see an avera...
AI summary The text analyzes rate impacts and bill changes for Small General, General, and Large General rate classes. Despite rate increases (3.0%, 1.5%, 1.3% respectively), overall customer bills decrease due to participation in BER-IR. Small General sees 10.2% lower participant bills, General 9.0%, and Large General 8.0%. Non-participants experience smaller bill increases.
Medium Industrial - ↑ 0.9% Rates - ↓ 4.0% Participant Bills - ↑ 0.7% Non-Participant Bills - ↓ 4.0% Avg. Total Cust. Bills - Non-Participants see an average bill increase of 0.7 percent over the study period. - The class overall sees an av...
AI summary Medium Industrial rate class shows a 0.9% rate increase, with participant bills down 4.0% and non-participant bills up 0.7%. All customers are assumed to participate in BER-IR, achieving 100% participation by 2011. Non-participant data is displayed despite potential non-existence in this class.
4.4.7 LARGE INDUSTRIAL - As modelled, the Large Industrial class includes Rate Code 23 (Large Industrial), Rate Code 25 (Large Industrial, interruptible service), and the one-part high voltage real time pricing tariff. - The average rate i...
AI summary The Large Industrial rate class includes Rate Codes 23, 25, and a high-voltage real-time pricing tariff. The average rate increases 0.2%, but participants see a 4.3% bill decrease, while non-participants see a 0.03% decrease. All customers are assumed to participate in BER-IR, achieving 100% participation by 2011, aligning participant and total customer bill effects.
2022 Rate and Bill Impact Analysis
AI summary The 2022 Rate and Bill Impact Analysis document outlines regulatory proceedings related to utility rate structures and customer bill impacts. Key focus areas include demand-side management, cost of service studies, and regulated business investment applications, with references to various programs and initiatives aimed at energy efficiency and carbon emission reductions.
Figure 1: Avoided Costs Sensitivity Analysis: Average Rate Impacts (2011 – 2039)
AI summary Figure 1 presents a sensitivity analysis of avoided costs and their impact on average rates from 2011 to 2039. It examines how variations in demand-side management (DSM) and other factors influence rate structures, reflecting key considerations in regulatory proceedings related to energy efficiency and cost allocation.
Figure 2: Avoided Costs Sensitivity Analysis: Average Participant Bill Impacts (2011 – 2039)
AI summary Figure 2 presents a sensitivity analysis of avoided costs and their impact on average participant bills from 2011 to 2039. The analysis evaluates how variations in demand-side management (DSM) programs and other factors influence electricity costs over time.
Figure 3: Avoided Costs Sensitivity Analysis: Average Non-Participant Bill Impacts (2011 – 2039)
AI summary Figure 3 presents a sensitivity analysis of avoided costs on average non-participant electricity bills from 2011 to 2039. It evaluates impacts under different scenarios, focusing on demand-side management (DSM) and related programs, including carbon emission differences and energy rebate initiatives.
Figure 4: Avoided Costs Sensitivity Analysis: Average Total Customer Bill Impacts (2011 – 2039)
AI summary Figure 4 presents a sensitivity analysis of avoided costs and their impact on average total customer bills from 2011 to 2039. It evaluates how variations in demand-side management and other factors influence billing outcomes over time.
Appendix D: Assumptions
AI summary Appendix D outlines key assumptions for a Nova Scotia regulatory proceeding, referencing acronyms related to energy management, cost studies, and regulatory applications. It provides context for terms like DSM, COSS, and RBIA, which are central to the proceeding's analysis.
Methodology for determination of changes in NS Power's base cost rates as a result of DSM-induced changes in class usage and total system costs November 27, 2020
AI summary The document outlines a methodology to assess how Demand Side Management (DSM) initiatives impact NS Power's base cost rates by analyzing changes in class usage and total system costs. It emphasizes regulatory considerations for adjusting rates based on DSM-induced shifts in energy consumption patterns.
1.0. Introduction In an effort to more precisely and accurately align EfficiencyOne's (E1) RBIA Model with the methodological process used by NS Power in setting of its base cost rates, all rate setting functionality from E1's RBIA model h...
AI summary EfficiencyOne's (E1) RBIA model has had its rate-setting functionality removed, with NS Power now using its COSS methodology. NS Power will provide annual inputs to E1's RBIA model under 'With DSM' and 'No DSM' scenarios from 2011 to 2035, including revenue forecasts, demand forecasts, and customer data. NS Power assumes responsibility for cost allocation methods and data inputs.
Overview of Spreadsheet Calculations
AI summary The document provides an overview of spreadsheet calculations used in a Nova Scotia regulatory proceeding, likely related to energy efficiency programs, cost studies, and demand-side management initiatives. Key entities include regulatory bodies, efficiency programs, and technical acronyms relevant to electricity generation and distribution.
"Total-Savings" tab The "Total-Savings" tab provides a sum of annual class savings in energy and demand usage at the generator's gate and customer's meter. In addition, class demand savings at the high side of the bulk power substation are...
AI summary The 'Total-Savings' tab calculates annual energy and demand savings at the generator's gate, customer's meter, and bulk power substation. These savings determine avoided fuel, generation, transmission, and distribution costs. FAM-related costs use unit avoided fuel costs multiplied by energy savings, while non-FAM costs use avoided infrastructure costs multiplied by demand savings.
2022 Rate and Bill Analysis
AI summary Analysis of 2022 rate and bill data for Nova Scotia, involving regulatory considerations for demand-side management, cost of service studies, and efficiency programs. Key entities include Nova Scotia Power Inc., Efficiency Nova Scotia Corporation, and related regulatory frameworks.