How Smart Grid overlaps with Energy Efficiency
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Smart Grid provides some energy efficiency savings, but it is often overlooked. This presentation shows some of that overlap.
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Semelhante a How Smart Grid overlaps with Energy Efficiency
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How Smart Grid overlaps with Energy Efficiency
- 1. Smart Grid & Energy Efficiency Two ships passing in the night? Jim Thayer Resilience Consulting ©Jim Thayer
- 2. Smart Grid can’t save energy by itself “Bills don’t go down automatically just because you have a smart grid. The customers have to do something.” - Patrick James, Director of Smart Grid Technologies, TXU Energy Can it really help energy efficiency programs?
- 3. Load shifting vs. Conservation. Demand Response programs typically shift energy usage! Exposing users to time-of-use rates will encourage them to shift some usage to lower cost periods. This does not qualify as energy savings. Some energy uses may be reduced by using, for example, dimmable lighting ballasts, producing a net conservation effect. Only the curtailed energy usage counts towards energy efficiency goals!
- 4. Smart Grid increases energy savings: Energy usage feedback can increase energy savings. Automated and continuous monitoring tools will improve yields. Better electricity usage data can improve program designs. Smart meters can reduce EM&V costs; savings can be reinvested. Dynamic pricingcan reduce overall usage. Smarter transmission management can reduce line loss.
- 5. Energy Usage feedback Energy use feedback lowers residential consumption by up to 11%. * However, persistence of feedback savings is suspect… Not much information about feedback saving associated with commercial and industrial users. * King and Delurey, 2005
- 6. Automated Diagnostics. Whole building meter data continuously tracks performance revealing energy wasting issues. Continuous monitoring can reduce rebound and increase energy savings persistence. Combining meter data & equipment data permits load disaggregation and precision fine tuning. Energy savings potential strongest in residential and small commercial buildings.
- 7. More detailed electric usage data. Better data going in; better results coming out. Detailed baseline data about building’s energy use and target market load shape combined with better utility data management systems will improve the design of EE programs. This will help identify priority targets and improve the effective yield of utility EE program offerings.
- 8. Dynamic pricing effects. Exposing users to dynamic pricing has reduced usage 4% in residences.* Energy savings depends on whether the load is curtailed or simply shifted. Impact depends on how high prices peak. CPP pricing effective at motivating when price differential are low. * King and Delurey, 2005
- 9. Reduced EM&V costs. Use of 15 minute interval meter data results in more accurate baseline and post-implementation modeling that can identify targeted energy saving. Using more accurate data for evaluation, measurement and verification may lead to significant cost savings compared to conventional on-site evaluation processes - permitting reinvestment of savings into more EE programs. Also permits tracking of energy usage over time…
- 10. Energy Savings Persistence Better data will permit us to go beyond verification and track performance over time. Continuous performance data can spot rebound effects and enable continuous commissioning to ensure energy savings persistence. Retro-commissioning impacts made more enduring by ability to detect problems in building energy systems. Energy savings “rebound” estimated from 5% to 40%
- 11. Reduce Line Loss The electric power industry loses 12% to 15% of all electricity produced. One of the most effective ways to reduce line losses requires continuously adjusting voltage control settings in response to changing system conditions. For this approach to be effective, a centralized automatic process is required (ie., a “smart” grid). * * EPRI Transmission Efficiency Initiative, 2010
- 12. Conclusions Measure-based incentives may be replaced with whole building approach. Widespread deployment of automated diagnostic tools will streamline EM&V and enable continuous commissioning. “In the future, demand response, energy efficiency, operational improvements and distributed generation may be combined to a single integrated offering with performance tracking to increase persistence.” * * Wiring the Smart Grid for Energy Savings: Mechanism and Policy Considerations – Hannah Friedman & PriyaSreedharan
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- the potential impact of feedback on energy consumption could be even greater for low energy buildings with solar photovoltaics (PV). For instance in an early California ZEH, the occupants who were previously not interested in their low energy house found that the energy feedback meter provided with the PV system became a powerful motivator to lower their energy use to better match the output of the solar electric system. Current research in Great Britain underscores the potential of feedback in grid-connected PV homes (Keirstead, 2005).recent, larger utility studies have shown indicated savings from residential energy feedback of 0-7%
- Whole building meter data continuously tracks performance revealing energy wasting issues: scheduling, unoccupied energy usage, demand peaks, correlations with outside temperatures, etc.Continuous monitoring can reduce rebound and increase energy savings persistence. Combining meter data & equipment data permits load disaggregation and precision fine tuning. This is limited by interoperability challenges with other data sources, especially in industrial uses.