Voltcast Research Working Papers
A single, preregistered series about European dynamic electricity prices, EVs, batteries, heat pumps, forecast uncertainty, carbon-aware control and dependable automation. Every paper links its frozen evidence and assumptions. Null and insufficient results remain visible.
How much does hourly averaging cost a 15-minute home. Positive values mean native quarter-hour selection found a cheaper schedule than hourly averaging.
Can daylight-saving time break an EV or heat-pump schedule. DST creates legitimate 23- and 25-hour local days; fixed 24-hour controllers can mis-index them.
Why a missing ENTSO-E A03 point is not missing data. Interval counts alone confuse a valid local-clock transition with missing delivery energy.
Can tomorrow’s day-ahead curve change after its first publication. The append-only revision sidecar measures whether first publication and latest observation differ.
When are tomorrow’s prices actually ready across Europe. This measures Voltcast fan-out after a complete auction curve is detected, not exchange gate closure.
Did 15-minute trading create volatility—or reveal it. The statistic decomposes observed variance; it does not identify a causal effect of the market redesign.
What does a one-hour timezone error cost a flexible household. The counterfactual isolates timestamp alignment; it is not an annual retail-savings claim.
What should an optimizer do when one price interval is missing. Selecting the next-cheapest valid interval produces a bounded fallback in the observed curves.
How closely do ENTSO-E and SMARD agree on German and Austrian prices. The canonical hot table retains one source per cell, so this snapshot cannot support a source-agreement estimate.
Should cross-country cheapest-window studies use local time or UTC. Local-day grouping better matches household deadlines; UTC grouping can assign edge intervals to another day.
How long do negative electricity-price episodes last. Duration is energy-weighted from native interval lengths, so DST and mixed MTUs remain valid.
Are longer negative-price events also deeper. A positive value means longer observed episodes tended to reach more negative prices; correlation is not causation.
Are negative prices solar events, wind events, or both. This descriptive comparison distinguishes solar and wind co-movement without assigning causality.
Why weekends and holidays change negative-price risk. Calendar composition is associated with negative-price incidence; national holidays are not uniformly available.
Do negative prices propagate across European borders. Co-occurrence along observed border links is descriptive and does not prove physical propagation.
What happens immediately after a negative-price episode. The transition statistic measures immediate curve shape, not a tradable return.
Are negative electricity prices always low-carbon. Negative wholesale prices often coincide with abundant low-marginal-cost output, but are not themselves a carbon measure.
How well calibrated are 14-day negative-price probabilities. Positive values mean lower proper-scoring loss than the recorded baseline.
How many negative-price intervals can a household actually use. Technical availability materially limits how much of a negative-price episode a household can use.
Has the structure of negative pricing changed since 2015. The long-run series establishes structural change but does not attribute it to one technology or rule.
How charging duration changes the value of smart EV scheduling. Longer charging sessions consume more of the price-ranked window and change both gross and per-kWh value.
What does an earlier EV departure deadline cost. A tighter departure deadline removes optional intervals and can raise minimum feasible cost.
Can a charging plan survive uncertain arrival times. Reserving feasibility for the latest arrival has a measurable wholesale opportunity cost.
How much flexibility do 3.7, 7.4, 11, and 22 kW chargers create. Higher power can concentrate energy into fewer cheap intervals, subject to connection and vehicle limits.
Is interruptible EV charging worth more than one continuous block. Allowing pauses expands the feasible set and cannot be worse under the same price curve.
When do 15-minute charger commands beat hourly control. Positive values mean native quarter-hour selection found a cheaper schedule than hourly averaging.
Should an EV charge for the lowest price or the lowest carbon. Daily generation is too coarse to identify the cleanest interval; this reports alignment, not an interval carbon optimum.
How often does a forecast-aware EV schedule change its mind. Observed lineage-matched MAE scales deterministic perturbations of the realized curve; this is a scenario, not logged customer behavior.
What is a seven-day price forecast worth for EV energy planning. The translation is a sensitivity bound, not guaranteed charging savings.
Which market properties predict smart-charging value across Europe. The range is a simple cross-market predictor; the result is descriptive and evaluated on observed days.
What round-trip efficiency makes day-ahead battery arbitrage worthwhile. The threshold is derived from observed captured spreads and is a screening statistic, not a device warranty.
How degradation cost changes the optimal home-battery schedule. Degradation above this normalized amount removes the index's gross wholesale value.
Is a second daily battery cycle actually worth taking. A second cycle is represented as value above the median first-cycle day; no physical dispatch is inferred.
Why one-, two-, and four-hour batteries earn differently. Longer duration accesses more spread but does not scale linearly because cheap and expensive intervals are finite.
When inverter power matters more than battery capacity. The duration comparison is an index-level proxy for the capacity-versus-power constraint.
Can price quantiles produce a safer battery schedule. Observed dispersion provides a transparent risk band; it is not a forecast quantile schedule.
How much battery value is lost when forecasts replace perfect foresight. The ratio is a sensitivity bound using serving-lineage MAE, not a measured battery dispatch loss.
Are home-battery savings spread across the year or concentrated in a few days. Concentration reveals whether averages depend on a small set of zone-month-duration observations.
Can carbon-aware battery dispatch increase cost—or reduce emissions. The unmatched aggregate association is exploratory; it cannot establish emissions savings.
How much battery value comes from the rebound after negative prices. The association captures the whole monthly curve, not only the first rebound interval.
How many hours of thermal inertia does price-aware heating need. This is the observed price-range opportunity scaled by a two-hour inertia assumption.
When does heat-pump COP overwhelm the electricity-price signal. Higher COP reduces electricity exposure per unit of delivered heat and can dominate modest price spreads.
Is domestic hot water more flexible than space heating. Separate storage and comfort constraints make domestic hot water more shiftable in this declared scenario.
What is the price of a tighter indoor-comfort band. Comfort has an explicit opportunity cost in the reduced-order scenario; no comfort preference is assumed optimal.
Do cold snaps align high heat demand with high power prices. Cold days are associated with different prices; this does not isolate causal heat-pump demand.
When wholesale prices and network time-of-use charges disagree. A network time-of-use signal can offset the wholesale signal and reverse the preferred interval.
How forecast uncertainty changes a preheating decision. The ratio bounds how often forecast noise could overwhelm the daily thermal-shift signal.
Can synchronized preheating create a household rebound peak. A five-percent synchronized shift is a stress scenario, not an observed Home Assistant fleet event.
Which European zones offer the strongest heat-pump flexibility signal. The ranking is a market flexibility signal, not a building-level savings forecast.
Should a household place only flexible heating load on a dynamic tariff. Separating flexible from inflexible load limits both upside and tail exposure.
What makes one European bidding zone harder to forecast than another. Zone difficulty differs materially, so one fleet average cannot represent every household market.
How quickly does forecast skill decay from day one to day seven. Exact-horizon lineage prevents a day-one score from being presented as seven-day skill.
Are P10, P50, and P90 price forecasts actually calibrated. Lower deviation means observed interval coverage is closer to the declared probability.
What happens to probabilistic coverage during price spikes. Coverage during high-error cells tests whether probabilistic bands widen enough in difficult regimes.
Are negative prices harder to forecast than positive prices. Higher loss on realized negative-price days indicates event-specific forecast difficulty.
How renewable generation changes day-ahead forecast error. This regime relationship is observational and does not assign model-error causality.
How temperature extremes change electricity-price forecast error. This regime relationship is observational and does not assign model-error causality.
Are weekends and holidays intrinsically harder to forecast. The calendar contrast is descriptive; holidays are not isolated in this contract.
How serving-lineage controls prevent forecast survivorship bias. Lineage prevents hindsight selection of a model after the delivery outcome is known.
Why backtest accuracy and live accuracy diverge. Backtests and served forecasts answer different questions; this result uses only recorded serving decisions.
Do cross-border flows make neighboring prices converge. Positive values are consistent with convergence, but constraints and common shocks remain confounders.
How persistent are household-relevant congestion price spreads. Persistent high spreads are household-relevant when tariffs expose the local bidding-zone price.
Do net-importing zones pay a systematic price premium. Flow sign is not a complete net-import balance, so this is a directional association only.
What happens to local prices when generation capacity goes offline. The event comparison is not causal because outage timing and system stress are jointly determined.
Do cross-border flows reverse around negative-price events. Direction changes describe coupling dynamics; negative-price timing is examined as a robustness stratum.
How fast do day-ahead price shocks propagate between zones. Daily lead-lag persistence bounds propagation speed but cannot resolve quarter-hour shock transmission.
How strongly do Nordic reservoir levels predict household price regimes. The public-safe snapshot contains no reservoir-level series, so the preregistered association is not estimable.
Does a diverse generation mix reduce price volatility. The Herfindahl complement is descriptive and category coverage varies by zone.
Can neighboring-zone prices improve a simple local forecast. This is a deliberately simple benchmark, not a production model promotion.
Did 15-minute market coupling change cross-border price convergence. The timing contrast is descriptive; market redesign, season, and system regime coincide.
How often is Europe’s cheapest electricity also its cleanest. Price and low-carbon output overlap imperfectly; either objective can select different days.
What is the carbon cost of always charging an EV overnight. Daily low-carbon share cannot identify an overnight carbon intensity; the result is an alignment diagnostic.
Why price and carbon intensity sometimes move in opposite directions. A weak or positive relationship explains why cheapest and cleanest schedules may disagree.
Does a higher renewable share reduce—or increase—short-run price volatility. More renewable output may lower means while increasing short-run shape; this is observational.
Is low-carbon electricity sold at a discount or a premium. Negative means clean days sold at a discount in this operational-share definition.
Can smart EV charging absorb solar’s low-capture-price hours. A lower capture rate identifies solar-heavy low-price periods that flexible EV load could absorb.
How wind-forecast uncertainty changes price and carbon risk. Observed output share is a proxy for wind regimes, not a wind-forecast error measurement.
Does a Dunkelflaute increase the value of household flexibility. The bottom-decile solar-and-wind proxy is transparent but not a meteorological Dunkelflaute definition.
When can a price-optimized battery increase average grid emissions. Price-only dispatch can select low-price days that are not cleaner than the sample median.
Are clean charging windows stable across seasons. Seasonal variation means one fixed clean-charging clock cannot generalize across the year.
How much can standardized household profiles save on a dynamic wholesale tariff. The envelope is an upper-bound scenario, not attainable measured savings.
What does bill value-at-risk reveal that average savings hide. Tail exposure reveals risk hidden by average savings.
When does a simple time-of-use tariff beat a fully dynamic tariff. A simple tariff can outperform when full dynamic exposure is costly or automation is constrained.
How much fixed-price hedging should a flexible household retain. This transparent volatility ratio is a risk proxy, not financial advice or an optimized retail contract.
How taxes and network charges dilute the wholesale price signal. Invariant taxes do not change interval rank, while time-varying network charges can; this scenario shows magnitude dilution.
Can a simple price cap protect dynamic-tariff households from extreme days. A cap truncates extreme exposure but also requires a counterparty and premium not modeled here.
Do EVs, batteries, and heat pumps complement or cannibalize one another. EV, battery, and heat-pump flexibility compete for the same cheapest intervals.
How much annual flexibility value comes from the best ten days. A concentrated opportunity set makes annual averages sensitive to automation reliability on a few days.
Do smart-home savings survive the 2021–2022 crisis regime. Crisis regimes amplify both flexibility value and exposure; robust conclusions must survive both samples.
Can seven-day probabilistic prices make household energy budgets safer. A probabilistic budget can reserve against forecast error; it does not remove retail price risk.
How to make Home Assistant electricity schedules safe across DST. UTC identities plus local display dates avoid duplicate or missing Home Assistant actions.
Does evcc preserve native market intervals end to end. The market data contract preserves interval duration; a downstream evcc adapter must not silently expand hourly values.
Polling or webhooks: which gives n8n the more reliable auction signal. Webhooks reduce expected detection delay when delivery succeeds; polling remains a recovery path.
How precise and timely are negative-price alerts. Timeliness is measured from complete-curve detection to notification, not from exchange gate closure.
How idempotency prevents duplicate actions when market data is revised. Idempotency keys should bind zone, delivery start, and source revision so a restatement updates state without repeating an action.
What should a home-energy controller do when Voltcast or an upstream source is unavailable. A controller can hold the last safe state briefly, then stop or fall back to a declared tariff schedule.
How stale can a forecast become before automation should reject it. Automation should validate issued-at, target window, and freshness rather than trust a cached payload indefinitely.
Can schema contracts prevent silent breakage in home-energy integrations. Required-field and interval-contract validation turns silent shape drift into an explicit rejected payload.
Do Markdown and JSON make AI electricity answers more verifiable. Shared paper metadata keeps the human narrative and machine-readable evidence addressable by the same stable ID.
Can an as-of record reproduce a household energy decision months later. An as-of decision is reproducible only when inputs, revisions, issue clocks, assumptions, and output hashes are retained.
The monthly European power roundup
Negative-price records, the biggest spreads, which zones were hardest to forecast — every number computed from our production data, on the 2nd of each month. No filler, unsubscribe anytime.