Spot trading vs hedging: what your electricity forecast is actually worth

Every participant in an electricity market — generator, supplier, or large consumer — manages the same tension. Lock your price in ahead of time, or take the price the market gives you on the day.

Lean too far towards certainty and you pay for it. Lean too far towards the spot market and one bad week can undo a quarter. Where you can afford to sit on that spectrum is, more than anything else, a function of how well you forecast.

The two levers

Hedging means fixing price in advance: forward contracts, futures, power purchase agreements. You know what you'll pay or receive months or years out. That certainty is valuable — it's also priced. Hedge everything and you give up the upside when the market moves your way, and you still carry volume risk: you hedged a forecast quantity, and your actual generation or demand will differ.

Spot exposure means transacting closer to real time — the day-ahead auction, the intraday market, and ultimately the balancing mechanism. Spot prices are volatile by design: they spike when the system is tight and can go negative when renewables flood it. That volatility is a hazard if you can't see it coming, and an opportunity if you can.

Neither lever is "correct." A portfolio is a mix, and the mix is a bet on your own forecast error.

Why forecasting sets the mix

Three places where forecast quality turns directly into money:

• Imbalance costs. Whatever you nominate, the gap between your forecast and your actual position settles at the imbalance price — usually the worst price of the day to be exposed to. Better short-term demand and generation forecasts shrink that gap every single settlement period.

• Spot participation. Confidence in your day-ahead and intraday view lets you leave more volume unhedged and capture spreads — shifting flexible load into cheap hours, selling into tight ones. Without that confidence, prudence pushes you to over-hedge and pay the premium.

• Hedge sizing. Even the hedged book depends on forecasts. Hedging a wind farm's output means forecasting that output seasons ahead; hedging supply means forecasting your customers' demand. Systematic forecast bias becomes a systematically mis-sized hedge.

As grids add renewables, all three get harder. Intermittent generation makes both sides of the equation — supply and price — spikier, and the value of being right about the next few hours keeps going up.

The data problem underneath

Here's the uncomfortable part: the forecasts that matter most feed on exactly the data teams find hardest to keep.

Short-term power forecasting improves with granular history — years of settlement-period readings, weather, and market outcomes, at full resolution. But a decade of half-hourly data across thousands of meters and nodes is expensive to keep hot, so in practice it gets downsampled to daily averages or shipped to cold storage.

Averaging is precisely the wrong compression for this job. The events that drive P&L — the spike, the negative-price afternoon, the cold snap — live in the tails, and downsampling erases the tails first. The history you deleted is the history your next forecast needed.

How we approach it

This is the problem Bhasa was built for. pdata compresses structured market and meter history by orders of magnitude and keeps it directly queryable — so a decade of full-resolution data stays hot at a fraction of the storage cost. Bhasa then forecasts straight from that compressed representation: no decompression step, no downsampled shadow copy, no tails thrown away.

That's the engine behind our electricity forecasting pilots, which run on live UK grid and market data today.

If you trade power — or you're paying to store the history that could make your forecasts better — talk to us about a pilot.