Asymmetric /Three Phase Power Flow¶
pandapower uses Sequence Frame to solve three phase power flow :
runpp_3ph(net, calculate_voltage_angles=True, init='auto', max_iteration='auto', tolerance_mva=1e-08, trafo_model='t', trafo_loading='current', enforce_q_lims=False, numba=True, recycle=None, check_connectivity=True, switch_rx_ratio=2.0, delta_q=0, v_debug=False, **kwargs)¶
runpp_3ph: Performs Unbalanced/Asymmetric/Three Phase Load flow
net - The pandapower format network
algorithm (str, “nr”) - algorithm that is used to solve the power flow problem.
The following algorithms are available:
“nr” Newton-Raphson (pypower implementation with numba
Used only for positive sequence network
Zero and Negative sequence networks use Current Injection method
Vnew = Y.inv * Ispecified ( from s_abc/v_abc old)
Icalculated = Y * Vnew
calculate_voltage_angles (bool, “auto”) - consider voltage angles in loadflow calculation
If True, voltage angles of ext_grids and transformer shifts are considered in the loadflow calculation. Considering the voltage angles is only necessary in meshed networks that are usually found in higher voltage levels. calculate_voltage_angles in “auto” mode defaults to:
True, if the network voltage level is above 70 kV
The network voltage level is defined as the maximum rated voltage of any bus in the network that is connected to a line.
max_iteration (int, “auto”) - maximum number of iterations carried out in the power flow algorithm.
In “auto” mode, the default value depends on the power flow solver:
10 for “nr”
For three phase calculations, its extended to 3 * max_iteration
tolerance_mva (float, 1e-8) - loadflow termination condition referring to P / Q mismatch of node power in MVA
trafo_model - transformer equivalent models
“t” - transformer is modeled as equivalent with the T-model.
“pi” - This is not recommended, since it is less exact than the T-model.
So, for three phase load flow, its not
trafo_loading (str, “current”) - mode of calculation for transformer loading
Transformer loading can be calculated relative to the rated current or the rated power. In both cases the overall transformer loading is defined as the maximum loading on the two sides of the transformer.
“current”- transformer loading is given as ratio of current
flow and rated current of the transformer. This is the recommended setting, since thermal as well as magnetic effects in the transformer depend on the current. - “power” - transformer loading is given as ratio of apparent power flow to the rated apparent power of the transformer.
enforce_q_lims (bool, False)
(Not tested with 3 Phase load flow) - respect generator reactive power limits
If True, the reactive power limits in net.gen.max_q_mvar/min_q_mvar are respected in the loadflow. This is done by running a second loadflow if reactive power limits are violated at any generator, so that the runtime for the loadflow will increase if reactive power has to be curtailed.
Note: enforce_q_lims only works if algorithm=”nr”!
check_connectivity (bool, True) - Perform an extra connectivity test after the conversion from pandapower to PYPOWER
If True, an extra connectivity test based on SciPy Compressed Sparse Graph Routines is perfomed. If check finds unsupplied buses, they are set out of service in the ppc
voltage_depend_loads (bool, True)
(Not tested with 3 Phase load flow) - consideration of voltage-dependent loads. If False, net.load.const_z_percent and net.load.const_i_percent are not considered, i.e. net.load.p_mw and net.load.q_mvar are considered as constant-power loads.
consider_line_temperature (bool, False)
(Not tested with 3 Phase load flow) - adjustment of line impedance based on provided line temperature. If True, net.line must contain a column “temperature_degree_celsius”. The temperature dependency coefficient alpha must be provided in the net.line.alpha
column, otherwise the default value of 0.004 is used
numba (bool, True) - Activation of numba JIT compiler in the newton solver
If set to True, the numba JIT compiler is used to generate matrices for the powerflow, which leads to significant speed improvements.
switch_rx_ratio (float, 2)
(Not tested with 3 Phase load flow) - rx_ratio of bus-bus-switches. If impedance is zero, buses connected by a closed bus-bus switch are fused to model an ideal bus. Otherwise, they are modelled as branches with resistance defined as z_ohm column in switch table and this parameter
(Not tested with 3 Phase load flow) - Reactive power tolerance for option “enforce_q_lims” in kvar - helps convergence in some cases.
(Not tested with 3 Phase load flow) - defines where open loop losses of three-winding transformers are considered. Valid options are “hv”, “mv”, “lv” for HV/MV/LV side or “star” for the star point.
v_debug (bool, False)
(Not tested with 3 Phase load flow) - if True, voltage values in each newton-raphson iteration are logged in the ppc
init_vm_pu (string/float/array/Series, None)
(Not tested with 3 Phase load flow) - Allows to define initialization specifically for voltage magnitudes. Only works with init == “auto”!
“auto”: all buses are initialized with the mean value of all
voltage controlled elements in the grid - “flat” for flat start from 1.0 - “results”: voltage magnitude vector is taken from result table - a float with which all voltage magnitudes are initialized - an iterable with a voltage magnitude value for each bus (length and order has to match with the buses in net.bus) - a pandas Series with a voltage magnitude value for each bus (indexes have to match the indexes in net.bus)
init_va_degree (string/float/array/Series, None)
(Not tested with 3 Phase load flow)-
Allows to define initialization specifically for voltage angles. Only works with init == “auto”!
“auto”: voltage angles are initialized from DC power flow
if angles are calculated or as 0 otherwise - “dc”: voltage angles are initialized from DC power flow - “flat” for flat start from 0 - “results”: voltage angle vector is taken from result table - a float with which all voltage angles are initialized - an iterable with a voltage angle value for each bus (length and order has to match with the buses in net.bus) - a pandas Series with a voltage angle value for each bus (indexes have to match the indexes in net.bus)
recycle (dict, none)
(Not tested with 3 Phase load flow) - Reuse of internal powerflow variables for time series calculation
Contains a dict with the following parameters: _is_elements: If True in service elements are not filtered again and are taken from the last result in net[“_is_elements”] ppc: If True the ppc is taken from net[“_ppc”] and gets updated instead of reconstructed entirely Ybus: If True the admittance matrix (Ybus, Yf, Yt) is taken from ppc[“internal”] and not reconstructed
neglect_open_switch_branches (bool, False)
(Not tested with 3 Phase load flow) - If True no auxiliary buses are created for branches when switches are opened at the branch. Instead branches are set out of service
If you are interested in the pypower casefile that pandapower is using for power flow internally, you can find it in net[“_ppc0”],net[“_ppc1”], net[“_ppc2”].
However all necessary informations are written into the pandpower format net, so the pandapower user should not usually have to deal with pypower.