Smart Grid & Energy Efficiency

Jim ThayerResilience Consulting

Two ships passing in the night?

©Jim Thayer

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?

Load shifting vs. Conservation.

1. 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.

2. Some energy uses may be reduced by using, for example, dimmable lighting ballasts, producing a net conservation effect.

Demand Response programs typically shift energy usage!

Only the curtailed energy usage counts

towards energy efficiency goals!

Smart Grid increases energy savings:

3. Better electricity usage data can improve program designs.

4. Smart meters can reduce EM&V costs; savings can be reinvested.

5. Dynamic pricing can reduce overall usage.

6. Smarter transmission management can reduce line loss.

1. Energy usage feedback can increase energy savings.

2. Automated and continuous monitoring tools will improve yields.

Energy Usage feedback

1. Energy use feedback lowers residential consumption by up to 11%. *

2. However, persistence of feedback savings is suspect…

3. Not much information about feedback saving associated with commercial and industrial users.

* King and Delurey, 2005

Automated Diagnostics.

1. Whole building meter data continuously tracks performance revealing energy wasting issues.

2. Continuous monitoring can reduce rebound and increase energy savings persistence.

3. Combining meter data & equipment data permits load disaggregation and precision fine tuning.

Energy savings potential strongest in residential and small commercial buildings.

More detailed electric usage data.

1. 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.

Better data going in; better results coming out.

2. This will help identify priority targets and improve the effective yield of utility EE program offerings.

Dynamic pricing effects.

2. Energy savings depends on whether the load is curtailed or simply shifted.

3. Impact depends on how high prices peak. CPP pricing effective at motivating when price differential are low. * King and Delurey, 2005

1. Exposing users to dynamic pricing has reduced usage 4% in residences.*

Reduced EM&V costs.1. Use of 15 minute interval

meter data results in more accurate baseline and post-implementation modeling that can identify targeted energy saving.

2. 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…

Energy Savings Persistence

1. Better data will permit us to go beyond verification and track performance over time.

2. Continuous performance data can spot rebound effects and enable continuous commissioning to ensure energy savings persistence.

3. Retro-commissioning impacts made more enduring by ability to detect problems in building energy systems.

Energy savings “rebound” estimated from 5% to 40%

Reduce Line Loss1. The electric power

industry loses 12% to 15% of all electricity produced.

2. 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

Conclusions1. Measure-based incentives

may be replaced with whole building approach.

2. Widespread deployment of automated diagnostic tools will streamline EM&V and enable continuous commissioning.

* Wiring the Smart Grid for Energy Savings: Mechanism and Policy Considerations – Hannah Friedman & Priya Sreedharan

3. “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.” *