Energy & utilities optimization
Make capacity count across time and the grid
4colors plans storage, flexible demand, equipment and infrastructure as one system. Better decisions over time lower costs and put capacity to use.
Built on the algorithms behind best-known schedules on a public project-scheduling benchmark.
Today's decision changes tomorrow's options
Charging a battery when electricity is inexpensive can be sensible. But using too much of its capacity now may leave it unable to meet a later peak.
A manufacturing process might shift its electricity use, but not beyond its delivery deadline. A network connection may be available in aggregate while a local bottleneck limits what can actually flow.
Energy decisions connect across hours, assets and networks. Optimization helps consider those dependencies together.
One day of electricity demand, hour by hour.Grey: everyday demand. Teal: flexible loads (charging, heating, pumps, storage). Red: over the grid limit. Strip: price, darker is dearer.
Peak, share of grid limit122%
Cost of flexible demand (index)100
Illustrative example, not customer data.
Decisions that connect one hour to the next
Storage and flexible-load scheduling
Plan charging, discharging and shiftable demand across time, accounting for state of charge, operating limits, forecasts and price signals. Evaluate the effect of choices now on later availability.
Generation and asset coordination
Schedule available resources within capacity, maintenance and ramping constraints. Compare tradeoffs among cost, service obligations and operational flexibility.
Network capacity and investment
Explore congestion, flow limits and upgrade choices in connected infrastructure. A local change can redistribute demand elsewhere, so the network needs to be modeled as a system.
What 4colors offers
From the solver engine to ready-made planning apps, pick the level that suits your team.
4colors Optimizer
The solver engine behind every 4colors product. A portfolio of search methods for hard planning decisions in routing, loading, scheduling and allocation, from Python or the API.
Optimizer for Scheduling
Advanced scheduling algorithms for the software you build to manage jobs, machines, people and resources. Due dates, setups and shared resources sit in one model.
Planning Applications
Takt, Roster and Stride bring optimization to production, shift and project planning. When a rush order lands or someone calls in sick, each re-plans within your rules.
Custom Optimization
Original models and algorithms built around your own resources, rules and objectives. We work with your team from the first prototype to a planner that runs in your systems.
Decisions across the energy system
Explore more use cases- Industry article
Energy: Decisions Connected Across Time and the Grid
Electricity has to arrive when it is needed, not simply exist somewhere in the system.
Read more - Use case
Planning Energy When Tomorrow Changes Today's Best Decision
Storage creates a simple but powerful connection between hours.
Explore the use case - Insight
Energy Grid Expansion: The Upgrade That Changes Its Neighbors
Adding capacity to a network can change where the next constraint appears.
Read the insight - Insight
Are We Solving the Right Optimization Problem?
A mathematically excellent answer can be a poor result if the objective rewards the wrong outcome.
Read the insight - Guide
Hard and Soft Constraints: Where a Schedule Can Bend
The distinction between a rule and a preference tells an optimizer what kind of compromise is possible.
Read the guide - Insight
What Can an Optimization Benchmark Actually Tell Us?
The most useful performance comparison depends on when you need the answer and what kind of answer you need.
Read the insight