Energy & Utilities

Thousands of assets. Real-time dispatch. Optimal cost and emissions.

Volatile renewables, shifting demand, aging infrastructure. kint calculates the cost-minimal dispatch while meeting emission targets and grid constraints.

€46B

annual cost of grid congestion in Europe

ACER, 2023

30-40%

of renewable energy output is variable

IEA World Energy Outlook

10-15%

cost reduction through dispatch optimization

Lazard LCOE Analysis

When Grids Don't Wait for Perfect Plans

It's 2 PM. Cloud cover just dropped solar output by 40%. Wind is picking up in the north but demand is spiking in the south. You have 150 generation assets, 40 storage systems, and grid stability requirements that change every 15 minutes. You need an updated dispatch plan now. Not in an hour. The wrong decision costs thousands per minute in imbalance penalties.

Renewable volatility compounds complexity

Solar and wind output changes faster than manual planning can react. Forecast errors cascade into costly grid imbalances.

Cost vs. emissions is multi-dimensional

Cheap generation may mean high emissions. Clean options may violate cost targets. Finding the best tradeoff manually is impossible at scale.

Storage decisions are time-coupled

Charging now means you can't charge later. Discharging now means less reserve. Every storage decision affects every future hour.

Regulatory compliance is non-negotiable

Grid codes, emission caps, capacity reserve requirements. One violation can mean fines exceeding the savings from optimization.

Comparison

Status Quo vs. With kint

Dispatch planning

Hours for day-ahead schedule

Continuous real-time optimization

Dispatch cost

Baseline

-14% reduction

CO2 emissions

Best effort compliance

-21%, guaranteed compliance

Imbalance penalties

Frequent occurrence

Near elimination

Maintenance scheduling

Calendar-based, reactive

Condition-based, optimized

Process

How It Works for Energy & Utilities

Connect your grid data

Generation assets, storage systems, demand forecasts, weather data. API or data feed.

Define objectives and constraints

Cost minimization, emission targets, reserve requirements, grid stability rules.

Continuous optimization

kint dispatches optimally in real-time. As conditions change, the plan updates automatically.

Operator oversight

Your operators see the dispatch plan, the reasoning, and can override any decision.

Use Cases

What kint solves in Energy & Utilities.

Grid Optimization

Input

“Optimize power dispatch across 150 generation assets and 40 storage units”

Output

kint computes the cost-minimal dispatch schedule meeting demand forecasts, grid constraints, and emission targets in real-time.

The dispatch plan updates continuously as conditions change. Solar forecast drops? Wind picks up? Demand shifts? kint recalculates the optimal response in seconds.

-14%

dispatch cost

-21%

CO₂ emissions

real-time

Maintenance Scheduling

Input

“Plan preventive maintenance for 200 assets minimizing downtime”

Output

kint schedules maintenance windows to maximize asset availability while respecting crew capacity, spare parts, and seasonal demand.

Maintenance is scheduled when it has the least impact on operations. Seasonal demand patterns, crew availability, and spare part lead times are all part of the optimization.

-31%

downtime

-17%

maint. cost

+9%

asset life

Resource Allocation

Input

“Allocate field crews to 80 service regions under time constraints”

Output

kint assigns crews optimally across regions, balancing workload, travel time, skill requirements, and emergency capacity.

Each crew gets assignments that match their skills and location. Travel time is minimized globally, not per crew. Emergency reserve capacity is maintained automatically.

-26%

travel time

+18%

jobs done

95%

SLA met

∞

Your Problem

These are examples. kint is not limited to predefined use cases.

> Describe your problem. kint handles the math.

Try with your own problem

FAQ

Common Questions About Energy & Utilities Optimization

Yes. kint solves dispatch problems in seconds, enabling 15-minute or even 5-minute re-optimization cycles. The solver speed scales with problem complexity.

kint supports stochastic optimization. It optimizes against multiple forecast scenarios simultaneously, not just the most likely one.

kint integrates via API with any SCADA or EMS platform. Data flows in, optimized dispatch plans flow out. No manual data transfer needed.

Any constraint that can be expressed mathematically. Grid codes, emission caps, reserve requirements, ramp rate limits. kint guarantees compliance.

For OEM Partners