Aayush Damani
PrescriptiveCapstone project · Analytics in Business, Imperial Business School

Heat Smart Orkney: The Commercial Case for Demand Response

Curtailment modelling and commercial viability analysis of a proposed demand-response scheme

PythonFinancial ModellingSensitivity AnalysisData CleaningExecutive Reporting

A residential demand-response scheme would absorb less than 1% of the curtailed wind energy it could technically address. It would still turn an annual profit of £151,000 at scale.

Orkney generates far more wind power than it can use or export. The cable connecting it to the mainland fills up, so turbines get switched down and roughly 23% of the potential electricity, about 450,000 MWh a year, is simply never generated. The brief was to work out whether Kaluza, the energy company whose scheme the case is built around, could make money from that by paying households to run smart storage heaters at exactly the moments when the wind power would otherwise be wasted.

To answer that, we used several years of minute-by-minute turbine data to work out precisely when and how much energy was being lost, then built a financial model of what it would cost to install the devices in homes and what the scheme would earn from the network operator and wind farm owners.

The first finding was a disappointing one. Even in the best realistic case, with about a third of eligible households signed up, the scheme would soak up only around 0.75% of the wasted energy it could technically address. Home heating is just too small to absorb an oversupply on that scale, so anyone pitching this as a solution to curtailment would be overpromising.

The second finding is why the project still ended in a recommendation to proceed. The money doesn't come from the energy saved, it comes from being paid to provide flexibility to the grid. That changes the economics completely: the scheme breaks even at 15% household sign-up and earns around £151,000 a year at 30%. So it's a viable business even though its environmental impact is small, and the recommendation was to roll it out in phases, but only after securing a long-term flexibility contract, since that payment is what the entire business case rests on.

Why it matters

The honest answer to the question the case posed was "this won't fix the problem, but you should still do it." The scheme can't meaningfully dent the wasted wind energy, so selling it as an environmental fix would set it up to fail. It does make money though, and it makes money at a scale that's realistically achievable. Being clear about which of those two things is true mattered more than making the project sound impressive.

Annual accounting profit by household penetration. Base case: SSEN flexibility payment £250/MWh, wind-farm fee £25/MWh. Break-even (highlighted) lands at 15%.

Share of the demand-response-addressable curtailment pool the scheme actually absorbs, drawn against a full 100% axis. Even at the 32% technical ceiling it reaches 0.75%.

Dataset, tools and how it was done+

Dataset: Rousay turbine telemetry (2015-2018) and Orkney residential demand data

Tools: Python · pandas · Power curve modelling · Financial and sensitivity modelling

  • Cleaned turbine telemetry (2.63 years, 1-min intervals) to classify wind-limited, capacity-limited, and demand-limited (curtailed) states
  • Annual curtailment: ~450,431 MWh/yr (23.1%), of which 268,146 MWh/yr (59.5%) is DR-addressable
  • Sense-checked against published Rousay turbine curtailment data (model within 1.07× of implied fleet total)
  • Household financial model: device cost, 12-year lifetime, SSEN flexibility payment (£250/MWh base case), wind-farm service fee (£25/MWh)
  • Break-even at 15% penetration (£36,590/yr profit); £151,112/yr profit and £283,459 cumulative cash flow by Year 5 at 30% penetration
  • Sensitivity analysis: SSEN flexibility price is the dominant driver of viability, ahead of wind-farm fees or subsidy