Your electricity
bill has an
avoidable cost.

Forewatt forecasts the electricity price hour by hour and automatically generates the optimal operating plan for your high-demand processes. No works. No changes to your machinery. No need to switch supplier.

Savings simulation — Foundry · 38,500 kWh/month
Monthly bill, not optimised€37,200
Peak demand penalties+€3,800 included
Available off-peak hoursUnder-used
Bill with Forewatt≈ €31,000–34,200
Potential savings8–17% / year

Electricity is your largest
variable cost. And it is still
managed reactively.

  • The price changes 24 times a day

    The OMIE market publishes the next day’s hourly prices at 2 pm. Without a system that processes them and acts accordingly, that knowledge arrives too late, or not at all.

  • Demand peaks are penalised for months

    Starting several machines at once during peak hours does not just cost more at that moment: it raises the capacity charge on the whole bill for the following months.

  • Your processes have complex physical constraints

    In foundry, chemicals or ceramics, high-temperature processes have thermal inertia, minimum cycle times and shift constraints that no smart meter can model.

  • Existing solutions are not built for industrial SMEs

    Energy management systems on the market are expensive, rigid and require infrastructure that a mid-sized company does not have, and should not need. Forewatt is different.

OMIE price — actual hourly variation (€/MWh) · Typical day
120804000h06h12h18h22hOFF-PEAK ↓PEAK ↑

The gap between peak and off-peak prices can exceed €80/MWh within the same day. Forewatt anticipates that curve and builds the work plan around it.

From the hourly tariff
to the lowest-cost
production plan.

Forewatt connects the electricity market with your industrial operations. The result: a daily or weekly work plan that minimises energy cost while respecting every physical and production constraint of your process.

  1. 01

    Real-time electricity market data

    Direct connection to the ESIOS API (Red Eléctrica, Spain’s grid operator) for hourly OMIE market prices and renewable generation data. No scraping, no intermediaries.

    ESIOSOMIEOfficial data
  2. 02

    Price forecasting with Machine Learning

    An XGBoost model trained on the last 14 months of data forecasts the price curve for the coming hours. It factors in the renewable generation mix, temperature and historical volatility patterns.

    XGBoostTime series14 months of history
  3. 03

    Load scheduling optimisation

    A combinatorial optimisation algorithm decides which equipment to run, when and at what load. It accounts for physical constraints (thermal inertia, minimum temperatures), work shifts and open production orders.

    Combinatorial optimisationGenetic algorithms
  4. 04

    An actionable plan for your operations team

    The system does not automate or modify your machinery. It produces a daily or weekly plan that your operators carry out from the web interface. The simulation shows the expected cost with and without optimisation: verifiable and auditable.

    Angular interfacePlant untouchedVerifiable ROI

The system calculates.
Your team decides and acts.

A simple web application that turns complex electricity market data into clear instructions for production. No technical training, no additional infrastructure.

app.forewatt.io · Week 48 simulation · 2 furnaces running
Optimised weekly cost
8,240€
↓ vs €9,640 not optimised
Savings in this simulation
1,400€
↑ 14.5% over baseline
Melts scheduled
14units
Full furnace capacity
Forecast average price
58€/MWh
vs €68/MWh unplanned
Forecast price curve — next 48hLive forecast
Mon
€50
Melt
Tue
€46
Melt
Wed
€82
Reduce
Thu
€53
Melt
Fri
€66
Normal
Sat
€88
Reduce
Sun
€39
Melt

For any industry with
high-demand processes
and concentrated consumption.

If your plant has high-power equipment that can be scheduled within time windows, Forewatt can save you money.

Foundry and metallurgy

Induction furnaces, scheduled melts and complex thermal inertia. Forewatt optimises when to switch on each furnace, at what power and which combination of parts to load, to maximise efficiency and avoid demand penalties.

Chemicals and pharmaceuticals

Reactors, autoclaves and batch processes with defined operating windows. Forewatt sequences operations to concentrate consumption in the cheapest time slots while respecting process times.

Food and meat processing

Cold stores, freezing tunnels and industrial cooking. Large consumers with real operational flexibility to shift load without compromising the cold chain or food safety standards.

Ceramics, glass and materials

Tunnel kilns and continuous firing with long temperature cycles. Forewatt models the thermal inertia of the process and finds the best start time to make the most of night-time and weekend off-peak prices.

Not monitoring.
Prescription.

The difference between knowing what you are spending and knowing exactly what to do tomorrow to spend less.

01 / PRESCRIPTIVE

It does not tell you what happened. It tells you what to do.

A smart meter shows past consumption. Forewatt delivers a concrete action plan for tomorrow, next week and next month, with the expected cost of each decision before you make it.

02 / NON-INTRUSIVE

Zero changes to your plant.

Forewatt does not automate your furnaces, install extra hardware or require changes to your current infrastructure. All you need is a computer with an internet connection. The system builds the plan; your operators carry it out.

03 / VERIFIABLE

Savings are audited, not estimated.

Every simulation records the expected cost with and without optimisation. The system generates automatic reports with the actual accumulated ROI, ready for finance, audits or reporting to public bodies.

Proven in real
industrial production.

First customer · In production

Casuso Propellers S.A.

Manufacturer of marine propellers and hydraulic turbines in Entrambasaguas, Cantabria (Spain). Two electric steel-melting furnaces —16 and 6 tonnes— with an electricity spend of €35,000–40,000 a month. Melts must reach 1,450 ºC and hold that temperature for at least two hours: a physical constraint no generic system can handle without specific modelling.

“The system does not change how our operators work. It gives them a clear plan for each week. They follow it. And the bill goes down.”
Monthly electricity spend
€35,000–40,000
Estimated potential savings
8–17% a year
Time to first simulation
48 hours
Infrastructure required
A computer and an internet connection. No works, no hardware.

Calculate your plant’s
savings potential.

Tell us your monthly consumption and your processes. In one session we will show you what Forewatt can save in your specific case.

  • No commitment
  • No changes to your installation
  • Results in one session

Or email us at info@evenbytes.com