Optimal Power Flow
For further information on this topic, please see the AC Optimal Power Flow or DC Optimal Power Flow sections of the Manual. Below, we have provided a list of functions that can be utilized for optimal power flow analysis.
To load optimal power flow API functionalities into the current scope, one can employ the following command:
using JuliaGrid, Ipopt
AC Optimal Power Flow
DC Optimal Power Flow
AC Optimal Power Flow
JuliaGrid.acOptimalPowerFlow
— FunctionacOptimalPowerFlow(system::PowerSystem, optimizer;
iteration, tolerance, bridge, name, magnitude, angle, active, reactive, verbose)
The function sets up the optimization model for solving the AC optimal power flow problem.
Arguments
The function requires the PowerSystem
type to establish the framework. Next, the optimizer
argument is also required to create and solve the optimization problem. Specifically, JuliaGrid constructs the AC optimal power flow using the JuMP package and provides support for commonly employed solvers. For more detailed information, please consult the JuMP documentation.
Keywords
Users can configure the following parameters:
iteration
: Specifies the maximum number of iterations.tolerance
: Specifies the allowed deviation from the optimal solution.bridge
: Manage the bridging mechanism (default:false
).name
: Manage the creation of string names (default:true
).verbose
: Controls the output display, ranging from silent mode (0
) to detailed output (3
).
Additionally, users can modify variable names used for printing and writing through the keywords magnitude
, angle
, active
, and reactive
. For instance, users can choose magnitude = "V"
and angle = "θ"
to display equations in a more readable format.
Updates
If the AC model has not been created, the function automatically initiates an update within the ac
field of the PowerSystem
type.
Returns
The function returns an instance of the ACOptimalPowerFlow
type, which includes the following fields:
voltage
: The bus voltage magnitudes and angles.power
: The variable allocated to store the active and reactive powers.current
: The variable allocated to store the currents.method
: The JuMP model, references to the variables, constraints, and objective.
Example
system = powerSystem("case14.h5")
acModel!(system)
analysis = acOptimalPowerFlow(system, Ipopt.Optimizer; iteration = 50, verbose = 1)
JuliaGrid.solve!
— Methodsolve!(system::PowerSystem, analysis::ACOptimalPowerFlow)
The function solves the AC optimal power flow model, computing the active and reactive power outputs of the generators, as well as the bus voltage magnitudes and angles.
Updates
The calculated active and reactive powers, as well as voltage magnitudes and angles, are stored in the power.generator
and voltage
fields of the ACOptimalPowerFlow
type.
Example
system = powerSystem("case14.h5")
acModel!(system)
analysis = acOptimalPowerFlow(system, Ipopt.Optimizer)
solve!(system, analysis)
JuliaGrid.setInitialPoint!
— MethodsetInitialPoint!(source::Union{PowerSystem, Analysis}, target::ACOptimalPowerFlow)
The function can reset the initial point of the AC optimal power flow to values from the PowerSystem
type. It can also initialize the AC optimal power flow based on results from the Analysis
type, whether from an AC or DC analysis.
The function assigns the active and reactive power outputs of the generators, along with the bus voltage magnitudes and angles in the target
argument, using data from the source
argument. This allows users to initialize primal values as needed. Additionally, if source
is of type ACOptimalPowerFlow
, the function also assigns initial dual values in the target
argument based on data from source
.
If source
comes from a DC analysis, only the active power outputs of the generators and bus voltage angles are assigned in the target
argument, while the reactive power outputs of the generators and bus voltage magnitudes remain unchanged. Additionally, if source
is of type DCOptimalPowerFlow
, the corresponding dual variable values are also assigned in the target
argument.
Updates
This function may modify the voltage
, generator
, and method.dual
fields of the ACOptimalPowerFlow
type.
Examples
Reset the initial point of the AC optimal power flow:
system = powerSystem("case14.h5")
acModel!(system)
analysis = acOptimalPowerFlow(system, Ipopt.Optimizer)
solve!(system, analysis)
updateBus!(system, analysis; label = 14, reactive = 0.13, magnitude = 1.2, angle = -0.17)
setInitialPoint!(system, analysis)
solve!(system, analysis)
Use the AC power flow results to initialize the AC optimal power flow:
system = powerSystem("case14.h5")
acModel!(system)
powerFlow = newtonRaphson(system)
powerFlow!(system, powerFlow)
analysis = acOptimalPowerFlow(system, Ipopt.Optimizer)
setInitialPoint!(powerFlow, analysis)
solve!(system, analysis)
JuliaGrid.powerFlow!
— MethodpowerFlow!(system::PowerSystem, analysis::ACOptimalPowerFlow;
iteration, tolerance, power, current, verbose)
The function serves as a wrapper for solving AC optimal power flow and includes the functions:
It computes the active and reactive power outputs of the generators, as well as the bus voltage magnitudes and angles, with an option to compute the powers and currents related to buses and branches.
Keywords
Users can use the following keywords:
iteration
: Specifies the maximum number of iterations.tolerance
: Specifies the allowed deviation from the optimal solution.power
: Enables the computation of powers (default:false
).current
: Enables the computation of currents (default:false
).verbose
: Controls the output display, ranging from the default silent mode (0
) to detailed output (3
).
Example
system = powerSystem("case14.h5")
acModel!(system)
analysis = acOptimalPowerFlow(system, Ipopt.Optimizer)
powerFlow!(system, analysis; power = true, verbose = 1)
DC Optimal Power Flow
JuliaGrid.dcOptimalPowerFlow
— FunctiondcOptimalPowerFlow(system::PowerSystem, optimizer;
iteration, tolerance, bridge, name, angle, active, verbose)
The function sets up the optimization model for solving the DC optimal power flow problem.
Arguments
The function requires the PowerSystem
type to establish the framework. Next, the optimizer
argument is also required to create and solve the optimization problem. Specifically, JuliaGrid constructs the DC optimal power flow using the JuMP package and provides support for commonly employed solvers. For more detailed information, please consult the JuMP documentation.
Keywords
Users can configure the following parameters:
iteration
: Specifies the maximum number of iterations.tolerance
: Specifies the allowed deviation from the optimal solution.bridge
: Manage the bridging mechanism (default:false
).name
: Manage the creation of string names (default:true
).verbose
: Controls the output display, ranging from the default silent mode (0
) to detailed output (3
).
Additionally, users can modify variable names used for printing and writing through the keywords angle
and active
. For instance, users can choose angle = "θ"
to display equations in a more readable format.
Updates
If the DC model has not been created, the function automatically initiates an update within the dc
field of the PowerSystem
type.
Returns
The function returns an instance of the DCOptimalPowerFlow
type, which includes the following fields:
voltage
: The variable allocated to store the bus voltage angle,power
: The variable allocated to store the active powers,method
: The JuMP model, references to the variables, constraints, and objective.
Example
system = powerSystem("case14.h5")
dcModel!(system)
analysis = dcOptimalPowerFlow(system, Ipopt.Optimizer)
JuliaGrid.solve!
— Methodsolve!(system::PowerSystem, analysis::DCOptimalPowerFlow)
The function solves the DC optimal power flow model, computing the active power outputs of the generators, as well as the bus voltage angles.
Updates
The calculated active powers, as well as voltage angles, are stored in the power.generator
and voltage
fields of the DCOptimalPowerFlow
type.
Example
system = powerSystem("case14.h5")
dcModel!(system)
analysis = dcOptimalPowerFlow(system, Ipopt.Optimizer)
solve!(system, analysis)
JuliaGrid.setInitialPoint!
— MethodsetInitialPoint!(source::Union{PowerSystem, Analysis}, target::DCOptimalPowerFlow)
The function can reset the initial point of the DC optimal power flow to values from the PowerSystem
type. It can also initialize the DC optimal power flow based on results from the Analysis
type, whether from an AC or DC analysis.
The function assigns the active power outputs of the generators, along with the bus voltage angles in the target
argument, using data from the source
argument. This allows users to initialize primal values as needed. Additionally, if source is of type ACOptimalPowerFlow
or DCOptimalPowerFlow
, the function also assigns initial dual values in the target
argument based on data from source
.
Updates
This function may modify the voltage
, generator
, and method.dual
fields of the DCOptimalPowerFlow
type.
Examples
Reset the initial point of the DC optimal power flow:
system = powerSystem("case14.h5")
dcModel!(system)
analysis = dcOptimalPowerFlow(system, Ipopt.Optimizer)
solve!(system, analysis)
updateBus!(system, analysis; label = 14, active = 0.1, angle = -0.17)
setInitialPoint!(system, analysis)
solve!(system, analysis)
Use the DC power flow results to initialize the DC optimal power flow:
system = powerSystem("case14.h5")
dcModel!(system)
powerFlow = dcPowerFlow(system)
solve!(system, powerFlow)
analysis = dcOptimalPowerFlow(system, Ipopt.Optimizer)
setInitialPoint!(powerFlow, analysis)
solve!(system, analysis)
JuliaGrid.powerFlow!
— MethodpowerFlow!(system::PowerSystem, analysis::DCOptimalPowerFlow;
iteration, tolerance, power, verbose)
The function serves as a wrapper for solving DC optimal power flow and includes the functions:
It computes the active power outputs of the generators, as well as the bus voltage angles, with an option to compute the powers related to buses and branches.
Keywords
Users can use the following keywords:
iteration
: Specifies the maximum number of iterations.tolerance
: Specifies the allowed deviation from the optimal solution.power
: Enables the computation of powers (default:false
).verbose
: Controls the output display, ranging from the default silent mode (0
) to detailed output (3
).
Example
system = powerSystem("case14.h5")
dcModel!(system)
analysis = dcOptimalPowerFlow(system, Ipopt.Optimizer)
powerFlow!(system, analysis; power = true, verbose = 1)