Hydrogen-Powered Turbines May Help Clean And Improve Electrical Grid Reliability
The title of this post, is the same as that of this article on Hydrogen Fuel News.
This is the first paragraph.
In less than three years, one or more hydrogen-powered turbines are expected to be up and running at or near New Jersey’s Bayonne Energy Center power plant, which feeds power to New York City.
Note.
- The Bayonne Energy Center is a peaker plant with ten gas turbines, with a total capacity of 640 MW.
- Peaker plants automatically cut in, when power demand is high, but power generation is low.
- The Bayonne Energy Centre transfers power to New York, through an underwater cable.
- The electrolyzers will be made by Ohmium International Inc and I suspect they will be powered by offshore wind.
- The hydrogen that is created will be stored. As Bayonne has a history of chemical manufacturing, there may be salt caverns that can be used or the hydrogen could be stored as a compressed gas or liquid in tanks.
I can see hydrogen being used in peaker plants elsewhere in the world, where there is lots of renewable energy and suitable hydrogen storage.
The hydrogen can also be used to decarbonise local industries and transportation.
The Potential For Wind Power In New Jersey
Wikipedia says this about the potential of wind power in the state.
New Jersey has the potential to generate 373 GWh/year from 132 MW of 80 m high wind turbines or 997 GWh/year from 349 MW of 100 m high wind turbines located onshore as well as 430,000 GWh/year from 102,000 MW of offshore wind turbines.
Note.
- New Jersey used 76,759 GWh in 2011
- It appears that most of these turbines would be located along the coast.
There is also a worry about hurricanes. But solving that is an engineering problem.
From my experience of modelling floating structures, I believe they may stand up to high winds better. But I’m not sure!
Classic Cars Are Being Rebuilt As Hydrogen-Powered Vehicles
The title of this post, is the same as that of this article on Hydrogen Fuel News.
This is the first paragraph.
Arrington Performance has rebuilt a 1964 Ford Falcon Sprint coupe to be powered by H2 in a trend converting classic cars into hydrogen-powered vehicles.
The company has also converted was a 1948 Chevrolet pickup, which it rebuilt with a 6.2-liter GM V8.
Not everybody would consider these to be classic cars, but surely if you can convert a 1948 pickup with a 6.2 litre engine, you can convert a wide range of vehicles.
An Expedition To Muswell Hill To Get Some Lovely Liver
After my plea in Need To Regularly Eat A Large Plate Of Calves’ Liver, I got a recommendation to try The Cilicia at Muswell Hill.
It was delicious and just what my body wanted. The liver had been cooked in sage butter with tomatoes, mushrooms and potatoes.
I shall return!
The only problem is that Dalston and Muswell Hill is not the easiest journey to make by public transport.
My route was as follows.
- I took by taking a 141 bus from close to my house to Manor House station.
- I then got a Piccadilly Line train to Turnpike Lane station.
- From there it was a 144 bus to Muswell Hill Broadway.
It took about 45 minutes.
But it might be quicker to take a 102 bus from Bounds Green station.
Or go to the Angel Islington and get a 43 bus from there to Muswell Hill Broadway.
But my route could all have been so different.
This map shows the Muswell Hill branch which was closed by British Rail and has since been mainly built over.
The Muswell Hill branch would have been part of the comprehensive Northern Heights Plan.
- The Northern Line would have been extended from Edgware to Bushey Heath.
- The Mill Hill East branch would have been extended to Edgware.
- If you look at the maps in Wikipedia, the Northern Line would be very different through London.
- The Muswell Hill branch would have given better access to the magnificent Alexandra Palace.
But Austerity after World War II meant the extension never happened.
I can see a case could be made for some parts of the Northern Heights plan, but it is too late now, as viaducts have been demolished and routes have been built over.
My feeling is that if there was a need for the Northern Heights plan in the 1930s, then as London has expanded, that need will need to be fulfilled in the future.
So when Austerity hits as it did after World War II and as it is happening now due to Covid-19 and Vlad’s war in Ukraine, we should make sure we don’t compromise our plans for the future.
I believe that with a small amount of safeguarding in the 1960s, the Northern Line would now have a useful branch to Alexandra Palace and Muswell Hill.
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
Rail Flood Defender
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: 10038342
Project title: Rail Flood Defender
Lead organisation: University of Sheffield
Project grant: £249,770
Public description: Rail Flood Defender will deliver a more reliable railway network that is safer for all stakeholders,
and empower Network Rail (NR) and the UK to become global leaders in intelligent holistic rail
drainage management. It will future-proof rail transport against the effects of climate change where
more intense and regular rainstorm events are expected.
The project will explore principles of autonomous active flow control to reduce manual operations
associated with protecting rail infrastructure from the effects of flooding. It achieves this by taking
the latest advances in edge computing and applying it to real-time automation of mechanical and
electrical equipment to control the flows in rail drainage systems, thus protecting the track drainage
from being overloaded and flooded during rainstorm events.
The importance of managing rail drainage infrastructure cannot be overstated. It is designed to
carry stormwater safely water away from the track via a system of pipes and channels. When
drainage infrastructure is compromised or inadequate, flooding can occur. Flooding causes delays
to passengers and costs to asset owners, but crucially can also affect other assets such as
structures and signalling, which endangers human life (e.g. Watford Tunnel
Derailment https://www.gov.uk/raib-reports/derailment-and-subsequent-collision-at-watford). This
project aims to collaboratively investigate the application of AI-powered automated real-time control
(RTC) for protecting the railway system and mitigating any impact on adjacent land.
The feasibility project will identify how the following benefits and sustainability opportunities can be
delivered:
- Reduce risk of rail services being disrupted during rainstorm events.
- Make the drainage design process more efficient.
- Avoid capitally and spatially expensive flood solutions (e.g. stormwater retention tanks).
- Provide a means for automated flushing to clear blockages (reduce manual intervention).
- Reduce surcharging on adjacent rural or urban areas.
- Explore additional opportunities such as rainwater harvesting for agriculture.
My Thoughts And Conclusions
Fifty years ago, I wrote and provided the software, that the Water Resources Board used to plan the water flows and new reservoirs in a large part of England. As over the intervening years, there have been few water shortages due to lack of reservoirs, I am led to believe that the WRB must have done a good job.
Now fifty years later our computing capabilities are much more advanced and I feel that the aims of this project are readily achievable.
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
Protection and Resilience for OLE using ComputerVision Techniques (PROLECT)
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: 10037158
Project title: Protection and Resilience for OLE using ComputerVision Techniques (PROLECT)
Lead organisation: ONE BIG CIRCLE LTD
Project grant: £247,115
Public description:
This project will utilise Computer Vision techniques applied to existing video footage and capturing
a new type of video sensor to address two main challenges which are exacerbated by weather
events and can result in the railway being closed. Providing means in which these type of challenge
can be predicted and prevented will help provide the railway to become more resilient to weather
events and season agnostic.
The following two areas will be addressed:
- Extreme hot weather causes OLE wires to extend and cause the tensioners to come into contact with the ground which can reduce tension and cause damage or event dewirement. Utilising existing video footage this project will automatically identify OLE tensioners, position and measure them and generate an live asset map with current status level. This can be utilised as part of a digital twin model and fed into systems which are able to alert maintainers to the issue so they are able to take preventative action.
- Hot, cold and humid weather can also have an impact causing Corona discharge from electrical assets such as insulators. The Corona discharge is an early warning sign of potential damage and failure of the equipment and can be measured as part of a predictive maintenance regime to prioritise preventative maintenance activities. This project will install a UV Corona camera onto a measurement fleet or in-service train and enable automated data capture with real-time data transmission and processing. The results will be evaluated by experienced working groups to tune and amend the level of Corona events to ensure an optimum level of precision and recall ensuring an operationally useful tool.
Both of these events can have very impacts on the railway in terms of delay, safety and customer
experience. By providing tools which have the capability of preventing these from occurring the
railway will have an increased resilience to the weather conditions.
My Thoughts And Conclusions
NextGen Data-Driven Timetable Performance Optimisation Tool
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: 10037862
Project title: NextGen Data-Driven Timetable Performance Optimisation Tool
Lead organisation: ARTONEZERO LIMITED
Project grant: ££157,826
Public description:
During the pandemic, the on-time reliability of services significantly increased due to the reduction
in the number of services and passengers.
However, as passengers have returned to the railway performance has once again deteriorated.
This has an even greater impact on the industry post-pandemic as passengers’ expectations for services that are reliable and run on-time is even higher. Increased delays and passenger dissatisfaction therefore leads to an even greater decreased revenue from ticket sales.
Poor performance is in large part due to a poorly planned timetable that is often operationally unachievable or cannot handle minor perturbations. This is due to the timetable usually being planned with simulations and the method does not in how trains performing in reality at junction or stations.
Through years of working closely with performance, planning and operational teams, we’ve identified that by using granular train movement data and machine learning techniques, the actual performance of the existing timetable could be accurately calculated. This would enable planners with accurate information to make faster and better planning decisions that are based on real-world evidence.
Our Timetable Analysis tool will deliver automatically updated insights and recommendations to planners that is highly aligned to the planning process. Utilising both on-track (track circuit) and onfleet (GPS and OTMR) data, the tool will provide an integrated view to both Network Rail and TOC teams.
Fundamentally this tool will result in a step change in the speed and quality of timetable planning, moving away from the use of limited simulations and anecdotal experience to a fully evidenced-based approach.
The Anonymous Widower 