Solve AC optimal power flow with an independent check
Solve AC optimal power flow with an interior-point method and exact sparse Hessians. It is a newer Garmo Solvers module from the October 2026 benchmark campaign, outside the 1.0.2 release. Results are checked against the original input; the measured result below states where it is ahead and where it is not.
BUILT FOR
Grid operators, utilities and power-system planning teams with AC optimal power flow workloads.
CHALLENGES → PRODUCT RESPONSE
The problem you face. What the product changes.
YOUR CHALLENGEWITH AC-OPF
01
The problem needs the right operation
An AC optimal power flow case in MATPOWER format (PGLib-OPF).
Solve AC optimal power flow with an interior-point method and exact sparse Hessians.
02
A result must answer the original question
An answer detached from its original constraints or input is difficult to rely on.
The suite rechecks the answer against the original input and identifies the applicable result state.
03
The comparison needs a defined scope
A capability or benchmark result is not a universal promise for a different workload.
Evaluate the selected input, resource budget, complete cost and required certificate against your baseline.
WHAT YOU GET
A defined capability. A useful result.
01
Selected solving capability
Solve AC optimal power flow with an interior-point method and exact sparse Hessians.
02
Original-input result
Generator dispatch and bus voltages, checked by an independent branch-level power-balance verifier.
03
Common access
Run it as garmo powerflow opf or through the garmo-mcp server; headless execution fits scripts and automated workflows.
04
Checked result
Power balance is rechecked from branch physics without the solver's own admittance matrix.
GARMO SOLVERS / MEASURED RESULT
Measured: case2869 in 7.8 s
PGLib-OPF case5 to case2869 match the published AC optimum. case2869 solves in 7.8 s on CPU against the PGLib published Ipopt time of 13 s (different machine); case9241 solves on the GPU in 27.5 s. Large RTE cases still diverge.
Source: Garmo Labs benchmark campaign, October 2026. Results apply to the stated inputs, hardware and conditions; they are not universal competitor rankings.
A customer has a supported model and wants an accepted result without adopting every other module.
Illustrative customer use—not a new benchmark or completed customer deployment.
01→
Provide the original input and define the useful outcome.
02→
Run the selected module under its supported resource and interface scope.
03→
Review the returned answer, original-input checks and completion state.
FIT & ACCEPTANCE
Start with the task. Agree the useful outcome.
What you bring
An AC optimal power flow case in MATPOWER format (PGLib-OPF).
What a useful evaluation measures
+Accepted original-model result
+Appropriate certificate or disclosed uncertified state
+Total time, memory and operating cost
Delivery
License the selected capability, commission an implementation, or agree an operated service. Infrastructure and additional engineering are specified separately.
QUESTIONS BEFORE BUYING
A clear scope. A clear relationship.
What is the important boundary?−
Large RTE cases still diverge; those are open work, not supported results.
How is it priced?+
No new standalone price is supplied for this product; request a scoped proposal. The platform plans buy qualified workflows and capacity, not a second charge every time a compatible method is selected. Existing bundle inclusions do not expand automatically.
How do we get access?+
Available through garmo CLI and garmo-mcp, including headless execution. Product-specific inputs, runtime dependencies, budgets and result checks remain explicit.
PUT THE PRODUCT TO WORK
Tell us what needs to improve.
Bring a task, an accepted outcome and the environment in which the product needs to work.
Select the capability you need directly or include its compatible role in a qualified platform workflow. Production scope identifies release, environment, capacity and support; a product count is not an entitlement.
