Second Life Energy Storage Firm Smartville Inc On Modules vs Packs, Ramp-Up Plans And Tesla’s Approach
The title of this post, is the same as that of this article on Energy Storage News.
I like the concept of taking the life-expired batteries out of electric vehicles and giving them a second life as grid batteries.
Smartville seem to have taken this simple and useful idea to a new level.
These are my thoughts.
The Internet Of Batteries
By the use of clever software, it appears, that they can control different types of battery packs, in a manner that could be called the Internet of Batteries.
They can also measure the state and performance and calculate the replacement date of each battery pack.
The Mother Of All Batteries
The implementation of this concept in their MOAB product allows the controlling software to manage a number of battery packs precisely to deliver a battery of the precise number of MWh, that the customer ordered.
- Provided an interface driver can be written, any type and make of battery pack can be incorporated.
- Nearly new, salvaged or elderly battery packs cab be used.
- The operating system can predict, when a battery pack must be replaced.
- Smartville are planning to install a 4MWh grid battery in central California that will be co-located with an existing power plant.
In some ways, the controlling software, is like the Chief Coach of a tug-of-war team, of mixed sexes, weights and strengths, that by asking for the right level of power from each member, gets the required performance.
Working With Tesla
The article talks about why, they don’t work with Tesla, where this is said.
Our experience in the US is that Tesla does not seem to be interested in working with outside partners. They’ve also publicly stated that they’re not focused on battery repurposing, not in their current business model at least, which I think might change over time. But that’s their public stance at the moment. We’re absolutely open to working directly with them but the opportunity hasn’t presented itself.
Does this indicate, that Tesla and Elon Musk are not the easiest people to deal with?
Conclusion
I shall be following Smartville.
I Can Now See Why A Big Pharma Company Liked My Software Daisy
Yesterday, I went to a seminar about medical research.
There was a presentation, where data in several dimensions was shown and the data was crying out for a Daisy Chart.
A Daisy Chart
This chart is a very simple presentation of telephone data, but I can imagine arcs showing factors like Dose, Blood Pressure, Sex, Patient Satisfaction etc.
Note.
- This chart is what I call a Day of the Week/Hour of the Day chart, which is a powerful way of looking at any time-based data, like faults or A & E arrivals.
- You can click on the nodes and links of the chart to access the data underneath. So if you wanted all female patients with high blood pressure in a separate Excel spreadsheet, this is possible with a couple of clicks.
- The charts can also be clipped from the screen and inserted into reports.
Daisy was used by one Big Pharma company twenty years ago and after yesterday’s presentation, I can understand, why they used it.
The seminar changed my mind about my attitude to Daisy and I got rather fired up about its possibilities.
Google Buys Scottish Offshore Wind Power
The title of this post, is the same as that of this article on offshoreWIND.biz.
This is the sub-heading and the first paragraph.
ENGIE and Google have entered into a 12-year, 100 MW corporate power purchase agreement (CPPA) supporting the Moray West offshore wind development in Scotland.
ENGIE will provide Google with more than 5 TWh of green power from the Moray West project, a nearly 900 MW offshore wind farm set to begin generating power from 2025.
Increasingly, it seems that large energy users are committing themselves to long-term energy deals.
One of Google’s senior people is quoted as saying.
People across the UK and Europe are increasingly worried about climate change and energy security. We share that concern and believe technology is an important part of the solution – both by reducing our own emissions, and by helping others to reduce their own.
I have a few thoughts.
How Much Of Moray West’s Output Is 5 TWh?
Consider.
- Moray West has an maximum output of 882 MW.
- This converts to 7.73 TWh.
If Google are buying all the electricity produced by the wind farm, that would mean that the capacity factor is around 64.7 %, which is quite reasonable, if a bit high for a fixed foundation wind farm.
If we are, it does surely reflect a desire for stability and security in a fast-changing world.
Are We Seeing More Corporate Power Purchase Agreements (CPPAs)?
Norwegian Company To Power Data Centres With Offshore Wind
The title of this post, is the same as that of this article on offshoreWIND.biz.
This is the sub-title.
Norwegian energy company Earth Wind & Power (EWP) is set to offtake up to 400MW of excess and pre-grid offshore wind power to supply electricity to data centre infrastructure in Northern Europe.
This sounds like a good idea.
Over the next few years, the UK will be ramping up our production of renewable energy.
Data centres could be an ideal way to make money from our excess energy.
State Of The Railway Compiler Data Solution (SORClite): Open Access Real-Time Signalling Data
This project was one of the winners in the First Of A Kind 2022 competition run by Innovate UK.
In this document, this is said about the project.
Project No: 10038973
Project title: State Of The Railway Compiler Data Solution (SORClite): Open Access Real-Time Signalling Data
Lead organisation: PARK SIGNALLING LIMITED
Project grant: £217,128
Public description: Our project seeks to support Network Rail in regaining understanding and ownership of key
signalling asset information so that this data can be used to adopt new performance measures,
identify bottlenecks within the rail network and target the 800,000 unexplained delay minutes that
occur annually. The project combines a number of existing technologies to deliver the hardware,
pipeline, analytics, and visualisation as a working demonstration. The data stores will also be
available for use by train operators and the wider data analytics supply chain, removing some of
the systemic blockers around access to data.
My Thoughts And Conclusion
SBRI: FOAK 2022 Optimising Railway Possessions
This project was one of the winners in the First Of A Kind 2022 competition run by Innovate UK.
In this document, this is said about the project.
Project No: 10038228
Project title: SBRI: FOAK 2022 Optimising Railway Possessions
Lead organisation: FRAZER-NASH CONSULTANCY LIMITED
Project grant: £236,226
Public description: One of the biggest challenges facing the railway industry is the complex process of planning and
possession management. The logistics of diverting, blocking, or closing sections of track can have
implications across the network. As the rail timetable becomes more congested, with increased
services, there is more potential for disruption and less obvious times for possession. Delays on
main-lines could result in huge fines, consequently delivering works and handing back possession
on-time is vital.
In 2020/21, NR spent £1.6bn on enhancements, £1.9bn on maintenance, and £3.2bn on renewals
(Office of Rail and Road, 2021). This translates into thousands of engineering works, most of these
require possessions to allow safe, traffic-free worksites for maintenance activities (e.g. remedial
works, inspections, maintenance and planned renewals).
Possessions result in both planned and unplanned disruption. Unplanned disruption can occur for
many reasons; machine faults, access issues, staff planning, or wrong engineering train
arrangement – all demonstrating the complexity of planning possessions.
Getting staff and equipment to worksites on time and minimising travelling distances are critical
efficiency requirements. The barriers to this are mutual road and rail points, staff numbers and
equipment types. Furthermore, engineering trains typically start in sidings which may be in remote
locations due to available sidings being occupied during large possession works. Consequently,
this cause issues in both timetabling and plans that ensure that engineering trains reach worksites
at the correct time and in the correct formation.
With increasing traffic and reducing availability of possessions this problem is likely to be further
exacerbated. Network Rail have identified a requirement to develop solutions for planning
procedures such that possession efficiency is increased, resulting in the delivery of infrastructure
maintenance work with minimal disruption and cost.
Combining Frazer-Nash’s deep experience in optimisation of railway challenges and eviFile’s
possession management solution, we will innovate to develop a product that will support rapid
planning and replanning of possessions through the application of optimisation and ML algorithms
to identify potential optimal plans. Using wide-ranging railway possessions data we will research
and adapt algorithms that will consider (for example) multiple scenarios, locations and types of
work, and optimise and efficiently manage resources to ensure minimal impact to infrastructure
traffic and capacity.
This will deliver possessions more efficiently, help plan work-activities during possessions more
precisely, manage infrastructure access more efficiently, allow tasks to be planned more efficiently,
and predict the impact of possessions on overall network performance more accurately.
My Thoughts And Conclusion
One of the biggest construction sites near me was the A45 dualling of the 1970s. It was a nightmare as there was no system managing possessions and frequently there were temporary traffic lights and diversions.
Things have got better since then and roadworks on main roads don’t cause as much delay as they used to.
The same improvement that good project management has had on the roads, now needs to be applied to the railways.
Trains With Brains(R)
This project was one of the winners in the First Of A Kind 2022 competition run by Innovate UK.
In this document, this is said about the project.
Project No: 10036632
Project title: Trains With Brains(R)
Lead organisation: JR DYNAMICS LIMITED
Project grant: £248,046
Public description:
Trains with Brains(r) aims to integrate data from a range of remote condition monitoring sensors
into Network Rail’s monitoring and planning systems/processes, to enable operations and
maintenance teams to address key cost efficiency and performance priorities via more informed
possession planning.
This will be delivered via a head to toe monitoring solution, enabled via bi-directional integration
between Transmission Dynamics and Network Rail.
My Thoughts And Conclusion
Unauthorised Cable Removal And Fault Triage
This project was one of the winners in the First Of A Kind 2022 competition run by Innovate UK.
In this document, this is said about the project.
Project No: 10038790
Project title: Unauthorised Cable Removal And Fault Triage
Lead organisation: FOCUS SENSORS LIMITED
Project grant: £215,310
Public description: When cable thefts occur the operation of the railway, often in nationally critical locations, can be
brought to a standstill with significant impact on passengers and freight supply-chains. Under
extreme industry and public pressure, Network Rail must delay scheduled activities and scramble
teams to effect repairs and get critical railway operational systems working again. Current
technology may not be able to locate the break to better than a few km accuracy, meaning long
periods of manual inspection are required to locate the exact position of the theft before the repair
can be started. This wastes valuable time, increasing the effect of the theft on the efficiency of the
network and creating cost for operators and delays for customers.
This proposal is for a technology solution, using existing trackside optical fibre cables, which can be
used to locate cable thefts instantly to within +/- 1m. After a theft is reported or detected by other
system, automatic analysis will pinpoint the location of the acoustic signatures of the theft activity.
The location of the theft will be instantly displayed, both on a map overlay with geographical
coordinates, and as a linear ELR, miles and yards track location. This will enable first-responder
policing and security to be deployed sooner and more accurately. Secondly, with an accurately
timed and positioned event signature, there is an opportunity for other parties with evidence
collecting abilities (e.g. Forward Facing CCTV on trains) to more proactively, and possibly
automatically, to retain evidence which may support prosecution. Thirdly the Network Rail
engineering team will be given advanced information to allow them to attend the site with the right
materials and resource to affect an earlier resolution.
As secondary activity we will enable location of optical cable by creating a companion
georeferencing co-reference for the trackside fibre cable, so that faults and fibre issues can be
located instantly to a more precise physical location. This provides a valuable tool for Network
Rail’s engineering teams, to reduce time for maintenance and fault finding.
My Thoughts And Conclusions
My software; Daisy was used by British Rail or was it Railtrack to analyse cable faults many years ago. Because of the discussions, we had at the time, I believe that this could be a very successful project.
Optimal Prediction of Sand For Adhesion
This project was one of the winners in the First Of A Kind 2022 competition run by Innovate UK.
In this document, this is said about the project.
Project No: 10039258
Project title: Optimal Prediction of Sand For Adhesion
Lead organisation: GOVIA THAMESLINK RAILWAY LIMITED
Project grant: £153,228
Public description: Train services are affected by seasonal variables particularly leaf fall between September and
December. They can also be compromised by wet weather, icy and snowy conditions at a regional
or very localised level on a particular route. Maintaining wheel-rail contact to ensure adequate and
safe braking requires the use of sand in low adhesion conditions. Sand is dispensed to trains in
response to a combination of train service plans and of weather forecast. However, not all trains
are currently able to be replenished during overnight stabling and servicing with attendant risks of
delays and damage to trains and infrastructure. Also, there is a high level of safety risk when sand
replenishment on trains is carried out on a third-rail yard.
“Optimal Prediction of Sand for Adhesion” (OPSA) lead by Govia Thameslink Railway, the major
Train Operating Company on third rail in the UK, will deliver a more efficient and cost-effective
means of predicting the dispensing of sand to trains to ensure services are not compromised by
adhesion losses and train sets are not required to be removed from planned operating diagrams
because of inadequate on board sand supplies. The algorithm developed as a results of this project
will base the estimates on an integrated framework that includes the forecast adhesion, track
maintenance and the expected speed profile in order to capture the change in weather and the seasonal factors.
The algorithm developed represents a cost effective solution to predict the use of sand and
schedule the maintenance of trains enhancing in turn safety and reducing the impact of delays on
the timetable. The algorithm will be developed including direct measure of sand dispersion, braking,
wheel slip and line speed diagram also accounting for human behaviour effects such as driving
style.
Govia Thameslink Railway has engaged with Cranfield University to deliver the disruptive
innovation proposed in this project. The algorithm will enable a more efficient train scheduling
improving public performance measure (PPM) addressing train delay targeting in particular the
25% of delay up to 15 minutes cause by several concurrent issues including train rescheduling and
the National Rail Passenger Survey satisfaction.
My Thoughts And Conclusions
FEIDS – FOAS Enabled Intruder Detection System
This project was one of the winners in the First Of A Kind 2022 competition run by Innovate UK.
In this document, this is said about the project.
Project No: 10038989
Project title: FEIDS – FOAS Enabled Intruder Detection System
Lead organisation: THALES GROUND TRANSPORTATION SYSTEMS LIMITED
Project grant: £223,660
Public description: Intruders in a railway environment and critical sites are a major problem for the rail industry, and
one that can cause severe delays if not prevented. Conventional monitoring technology is low
range, impractical and has a high deployment and operational cost. Instead, a system that can
monitor the perimeter of a large area with minimal human supervision and can be used to direct rail
staff to the correct location is required to introduce work efficiencies.
Thales’ subcontractor Focus Sensors have developed the technologies capable of delivering a
persistent perimeter detection system that can detect persons approaching a site before they reach
the perimeter boundary and alert railway staff to their precise location. This will support railway staff
to respond effectively and reduce delay minutes, insuring efficiency and cost benefits.
We propose to showcase a first-of-a-kind application of Focus Sensors’ next-generation Fibre Optic
Acoustic Sensing (FOAS) technology to deliver accurate and real-time information and alerts on
intruders or potential intruders in a rail environment using our lateral-positioning technology
developed for detection trains. This capability will enable security staff to rapidly respond to
incidents and ensure intruders can be dealt with quickly and efficiently.
The FOAS-Enabled Intrusion Detection System (FEIDS) will use FOAS to detect objects moving
near the fibre/perimeter, identify them and determine the distance from a boundary. This monitoring
is both real-time and persistent, enabling alerts to be sent when a person or vehicle gets too close
to or crosses a boundary. The high fidelity of the system means that an intruder’s location can be
determined to an accuracy of +/- 50cm, and this information is crucial to ensuring that on-site
security teams are able to quickly and efficiently deal with the intruder.
This technology can be utilised both along sections of the railway and at specific, sensitive sites.
Due to the long range and autonomous nature of the system, it drastically reduces the workload of
railway staff. Staff will be provided with an automatic alert that will provide them with information on
the nature of the intruder(s) and the exact location. This reduces the time for intervention, enabling
trains slowed due to the risk to resume at normal speed quicker, lowering the impact of trespass. It
also increases the likelihood of trespassers being stopped committing vandalism, which can disrupt
operations, and reduces the likelihood of reoffending.
My Thoughts And Conclusions
The Anonymous Widower 