KPG Run Overview

KPG Run is a cross-platform desktop application that provides an intuitive interface for solving various power system optimization problems. It integrates production-grade solvers into a modern, user-friendly UI and includes built-in tools for visualizing optimization results. KPG Run also exports standardized result files that can be opened in KPG View.

flowchart LR
    A["Test System Data"] --> C["KPG Run GUI"]
    B["User Configuration"] --> C
    C --> D["Solver Selection"]
    D  --> |Simple| E["Economic Dispatch"]
    D -- Scheduling --> F["Unit Commitment"]
    D -- Network (DC) --> G["DC-OPF"]
    D -- Network (AC) --> H["AC-OPF"]
    E --> I["Results"]
    F --> I
    G --> I
    H --> I
    I --> J["Visualization"]

Test System Data

KPG Run solves the power system optimization problems with KPG 193 test system data and visualizes the key results. KPG 193 is a synthetic Korean transmission grid model constructed from publicly available data and intended as a benchmark for studies of the Korean power system.

→ KPG Test System Details

Available Optimization Models

KPG Run includes four optimization models covering a range of power system analysis needs:

1. Economic Dispatch (ED)

Simplest model for cost-minimized generation dispatch without network constraints.

Type: Linear Programming / Quadratic Programming (LP/QP)
Solver: Gurobi
Use Cases:
- Screening studies
- Teaching examples
- Quick dispatch analysis
- Merit order calculation

→ ED Formulation Details

2. Unit Commitment (UC)

Day-ahead scheduling with generator commitment decisions and temporal constraints.

Type: Mixed-Integer Linear Programming (MILP)
Solver: Gurobi
Use Cases:
- Day-ahead market clearing
- Multi-period scheduling
- Reserve requirement planning
- Startup/shutdown optimization

Key Features:

Minimum up/down time constraints
Startup and shutdown costs
Ramp rate limits
Reserve requirements
24+ hour optimization horizons

→ UC Formulation Details

3. DC Optimal Power Flow (DC-OPF)

Network-constrained dispatch using linearized power flow equations.

Type: Linear Programming / Quadratic Programming (LP/QP)
Solver: Gurobi
Use Cases:
- Market simulation
- Locational marginal price (LMP) calculation
- Congestion analysis
- Fast multi-scenario studies

Key Features:

Transmission line limits
Angle difference constraints
Network topology representation
Congestion rent calculation
Fast solution times

→ DC-OPF Formulation Details

4. AC Optimal Power Flow (AC-OPF)

Full AC power flow with voltage and reactive power considerations.

Type: Nonlinear Programming (NLP)
Solver: Ipopt
Use Cases:
- Detailed feasibility analysis
- Voltage stability assessment
- Reactive power planning
- Accurate loss calculation

Key Features:

AC power flow equations
Voltage magnitude constraints
Reactive power limits
Generator capability curves
Transmission losses

→ AC-OPF Formulation Details

Custom Solvers

KPG Run supports custom solver implementations written in Julia.

Existing solver .jl files can be used as templates to understand the expected KPG Run configuration and interface. By following the same structure and conventions, users can implement their own custom solvers and run personal optimization models through KPG Run.

For details on using Julia and JuMP, refer to the resources listed below.

Julia Documentation: docs.julialang.org
JuMP Documentation: jump.dev

Model Comparison

Feature	ED	UC	DC-OPF	AC-OPF
Problem Type	LP/QP	MIP	LP/QP	NLP
Network Model	None	None	DC	AC
Time Periods	Single	Multiple	Single	Single
Commitment	Continuous	Binary	Continuous	Continuous