Key to the success of BID3 is the quality of the data that accompanies it. And the reason we can maintain high quality data is that we use it ourselves: as the largest supplier of independent market reports (AIM Reports) we have a team of 100 experts checking our data and scenarios so you don’t have to.

Standing data

Power plants, efficiencies, capacities, reservoir sizes, inflows, interconnector capacity … the list goes on. Although you can use your own data in BID3, many clients choose to start with an AFRY-calibrated dataset to guarantee quality. Best of all if you disagree with any data, our country experts from the AIM Reports are happy to explain why and how they’ve got the data or how they made the assumption.

Profiles and weather data

Weather data is at the heart of the BID3 design, and we can provide benchmarked time series data that is on a consistent weather basis. That way your temperatures, wind, solar, demand and hydro all match – both across technologies and across geographies. Modelling more than one weather pattern is key to getting accurate results, but whether you want to keep it lightweight with 3 weather patterns from or heavyweight with 100, we can support you.

Scenario data

Although the purpose of having a model is to allow you to develop your own scenarios, having a calibrated starting point is a quick way of getting started. We can support you by providing off-the-shelf scenarios based around our AIM Reports, giving you the trust that the scenario has been independently calibrated.

Alternatively, we can build you a bespoke scenario based on your own assumptions. That way you can start your scenario building from something that has been customised and set-up to your own views of the future.

Backcast

We backcast (backtest) our data thoroughly, and when you subscribe to our datasets we’ll provide a full backcast of the data. This allows you to understand the accuracy of the data, for all market variables including hourly prices, flows, generation, CO2 emissions. We also backcast critical economic information like capture prices and battery operation. With this transparency you can gain confidence that the model is accurately simulating the future.