Skip navigation
Share via:
This proposal was moved to: Energy Supply 2016

Pitch

Provide insight in consumption up to appliance level with Smart insight of Ipsum. Shift behavior through competition and cash prices.


Description

Summary

Total energy consumption data is send to Ipsum Energy through the internet. Ipsum translates this into consumption per appliance, name the appliance and provide the information to users via App and website. Users can real-time see their savings, compare their consumption to other users or earlier periods, and on top of that see if replaced appliances really use less energy.

Smart insight of Ipsum is an extremely effective addition to an existing infrastructure: smart meters. The intelligence is back-end based. This means no expensive hardware is required which makes the service super scalable and accessible to everyone because of the low costs.

The roll out can scale per country depending on the availability of smart meters. In the coming 5 years the number of residential smart meters will grow to over 1 Billion.

Research has shown that 24/7 insight up to classified appliance level will lead to the highest possible impact at consumers. Adding a competition with cash prices will increase the number of participants and the total impact for a changing climate.

It is possible to create competition among the users of Smart insight. Competition is possible at local, regional, national and global level. The prices should be linked to the overall impact of change on the energy consumption made by the participants. 

We expect that local news will report on winners, leading additional participants. The solution has a ROI of less than 6 months with on top of that the possibility to earn cash at different competition levels.

 


What actions do you propose?

The main policy, key to make this change happen, is the installation of smart meters. It is key that smart meter have a free communication port for households to use. In most countries this is policy. Implementation is on its way.

Second most important step is the acceptance of Smart insight by large companies or governments to allow for a large scale low cost roll-out. We see the intention in our pilot country, the Netherlands, that there is interest from e.g. energy companies, bank, pensions fund, municipalities, housing corporations to provide Smart insight free of charge or at reduced cost for their consumers. Cost levels, quality of the service and impact on energy consumption will determine the overall success.

 


Who will take these actions?

Leaders in sustainability will be leading to make the change, either from business or government.

On top of this Ipsum should be leading and convince the public step by step. 


Where will these actions be taken?

We expect to be present in the main countries in which smart meters are being rolled out. Currently our focus is on Europe and USA.

Once we have a consumer connected (takes 3-5 minutes in the Netherlands) we will inform the consumer in a mobile app. We provide insight, we classify the appliances with consumption based on their smart meter data. With push notification and personalized tips we will keep them engaged. At the start no change is required. We see after the initial results change does come. E.g. we have a group of a Dutch client with idle consumption between 10W and 740W, and an average of 165W. Our messages in the beginning are targeted to reduce idle consumption and based on initial results we see impact is evident. In the Netherlands 740W idle does cost 1400 euro per year, while you are sleeping or in the office. 


How will these actions have a high impact in addressing climate change?

Our solution will lead to an average of > 12% consumption reduction. We believe that any form of competition will increase the savings and behavior change.


What are other key benefits?

> 12% energy reduction on average per participant

increased awareness on energy and CO2 leading to changing in the public environment following the changes made at home

Differentiators

1. Cost. Our solution has the lowest costs. Above mentioned study by EPRI shows a lowest cost of 150 USD for a 5 year contract. We can offer 5 years at 30 USD per year. 

2. Ease of installation. 3-5 minutes. Many solution not using the smart meter connect to the electrical wire and as a consequence require electrical knowledge, high risk or an installer @75-100 USD

3. Automatic classification. We classify more appliances with our algorithm as most offerings. In many cases of competition the consumer will see Appliance 15 and than the consumer has to do classification?!?!

4. Real-time. Smart insight by Ipsum has max 1 minute delay. Many solution are not that close to real-time with their feedback. We see some of our competitors use statistics instead of real usage of an household.


What are the proposal’s costs?

Cost are limited to an investment in localization of the solution per country. The investment is needed to create hardware, if not available, for the country specific smart meter. 

Of course some investment is needed for marketing and sales to grow the impact per country. The amount will determine the speed of the impact.

Our proposal is solely based on Ipsum Energy. Above differentiators make the implementation and scalability possible. We do not believe that in initial investment of >200 USD will create the change needed to reduce CO2. We offer customer in the Netherlands the option to purchase for insight for a short and long term. 12 months insight is below 50 euro.


Time line

Our focus is 1-5 years. In this time period we should be able to create impact at millions of families in the USA and Europe. 


Related proposals


References

Great papers on the value of disaggregation using smart meter data and the value of direct feedback on behavior change. 

http://web.stanford.edu/group/peec/cgi-bin/docs/behavior/research/disaggregation-armel.pdf

In the image on page 6 the Ipsum Energy solution can be categorized on the far right as Appliance Feedback Augmented, automated personalized recommendations plus.

http://www.sciencedirect.com/science/article/pii/S0301421512007446

http://web.stanford.edu/group/peec/cgi-bin/docs/behavior/research/FieldExperimentPowermeter_vrevised_May2012_authors_vf_pdf.pdf

http://www.sciencedirect.com/science/article/pii/S030142151630074X