Utilities & District Energy
District heating, CHP and waste-to-energy sites adding post-combustion capture inherit the exact unit this platform was built and calibrated on — along with the foaming, fouling and solvent losses that come with it. The same method reads the boiler, the turbine and the network too, and in a public asset the numbers it produces are the ones the regulator and the customer both ask for.
SOURCEDIEA district heating analysis · ecoprog waste-to-energy survey · Global CCS Institute. Every figure on this page is linked at the foot of it.
Part one — the capability
The engine compares what the plant is doing against what physics says a healthy unit should be doing, ranks the gaps, names the cause behind each one and prices the consequence. On a public asset that price is not only money — it is heat that was going to be sold, and an efficiency figure somebody will be asked to defend.
What goes wrongFoaming, absorber flooding, lean/rich exchanger fouling, reboiler scaling and corrosion, filter plugging, solvent degradation and losses.
What comes back22 named faults, each with the root cause behind it and the evidence that fired. This is the unit the platform was built on — a capture retrofit is the one part of your site that needs no new science.
What goes wrongExcess air, fouling and slagging on the heat transfer surfaces, air leakage, and a fuel — especially waste — whose calorific value moves every hour.
What comes backMeasured duty against modelled duty at the fuel actually being burned, so an efficiency drop is separated from a bad fuel batch instead of being blamed on one.
What goes wrongHeat rate creep, blade deposits, condenser fouling and vacuum loss, extraction balance between power and heat that drifts away from optimal.
What comes backThe real cost of the last megawatt against the last megajoule of heat, hour by hour — the trade that a CHP set makes constantly and prices annually.
What goes wrongReturn temperature drifting up, distribution losses assumed from a commissioning figure, pumping power spent to overcome a fault nobody has located.
What comes backModelled against measured losses along the network, so a leak or a mis-set substation has a location rather than an allowance.
What goes wrongReagent overdosing, bag filter and scrubber performance decay, and continuous emissions data that has to survive a regulator rather than an internal review.
What comes backReagent consumption against what the measured flue gas actually required, and an emissions figure with a derivation somebody can follow line by line.
What goes wrongPlant dispatched on yesterday’s pattern, storage used by habit, and fuel or waste feed quality treated as a constant when it is the largest variable on site.
What comes backWhat each unit costs to run right now against what it delivers, so dispatch is a calculation rather than a convention.
One answer, four audiences
A finding only a specialist can read gets ignored; a finding only a manager can read gets distrusted. Because every call is denominated in both engineering units and money, one output serves everybody without being rewritten.
One ranked list at the start of a shift, in plant units, with the evidence attached. Not four hundred alarms and a colour.
The residual against expected-healthy, the indicators that fired, the ones that corroborate, and the ones that would have ruled the fault out. Something concrete to disagree with.
Which item is degrading, how quickly, and what each week of delay costs. Cleaning and outage scope argued from a number instead of from a habit.
Energy and losses per unit, priced daily. The margin review and the emissions report draw on one model, so they stop disagreeing with each other.
Part two — the market
A utility’s performance is scrutinised by a regulator, a municipality and its own customers. The measurements already exist. What is missing is the chain from a measurement to a number somebody can defend in public. On the left is how that is handled today; on the right is what it is worth to do properly.
To put one number on itA capture retrofit on a waste-to-energy line capturing 400,000 tonnes a year, running three tenths of a gigajoule per tonne above where it should be, wastes about 120,000 GJ of steam a year — heat that was going to be sold. At typical heat network value that is on the order of $1 million a year, from one avoidable cause. The steam price is an assumption, stated so you can substitute your own; the physics behind the 0.3 GJ is not.
Why this and not another dashboard
A statistical model has to be shown the fault before it can find it. A physics reference model needs equipment datasheets. On a unit that has never failed inside its recorded history — which is most units, and every new-build — only one of those two is any use.
Every diagnosis carries the indicators that fired, the ones that corroborate it, and the ones that would have ruled it out. An engineer can argue with it. That is the only reason anyone in a control room ever acts on it.
Six consequences are priced directly, so a finding arrives as a cost per hour rather than a severity colour. The same output serves the operator, the planner and the board without being rewritten for each.
The cost of the next unit is datasheets, a tag list and a fitting pass — not a new product. That is the whole scaling argument: the platform grows by calibration, and calibration is the cheapest thing in this business to change.
The path from the calibrated unit
Each stage below reuses the same engine and the same knowledge-base structure. What changes is the unit it is fitted to — and that is deliberately the cheapest thing in this business to change.
Absorber, water wash, lean/rich exchanger, stripper, reboiler and the full solvent circuit, fitted against an operating amine train with thirteen days of one-minute history: 26 equipment items, 161 tags, 22 faults, 19 root causes, 54 indicators, 6 costed consequences.
Your flue gas, your solvent, your steam supply. This is a calibration against your own history rather than a new model, which is why a capture retrofit is the cheapest place on a utility site to start.
Where the capture plant stops being separable from the host. Modelling both sides puts a number on the steam the capture unit is taking, against what that steam was worth as heat or power.
The part of a district energy business that is measured everywhere and modelled nowhere. Closing that loop turns an annual efficiency report into an operating decision.
Being straight about it
The platform runs on a real amine train with thirteen days of one-minute history behind it — live diagnosis, ranked evidence, root causes and cost per hour. It is the same unit a capture retrofit puts on your site.
Sources
The industry figures on this page are public and third-party. The amine figures — 22 faults, 19 root causes, 54 indicators, 6 costed consequences, thirteen days of one-minute history — are ours, and are countable in the platform.