Optimization with PYPOWER

Warning

The optimization with pypower functionality does not have the best convergence properties. Therefore, even if the network configuration is appropriate as an optimization problem, e.g. easily checked by pandapower.opf_task(), pandapower.runopp() may not converge.

You can run an Optimal Power Flow using the PYPOWER OPF

AC OPF

pandapower.runopp(net, verbose=False, calculate_voltage_angles=True, check_connectivity=True, suppress_warnings=True, switch_rx_ratio=2, delta=1e-10, init='flat', numba=True, trafo3w_losses='hv', consider_line_temperature=False, **kwargs)

Runs the pandapower Optimal Power Flow. Flexibilities, constraints and cost parameters are defined in the pandapower element tables.

Flexibilities can be defined in net.sgen / net.gen /net.load / net.storage /net.ext_grid net.sgen.controllable if a static generator is controllable. If False, the active and reactive power are assigned as in a normal power flow. If True, the following flexibilities apply:

  • net.gen.min_p_mw / net.gen.max_p_mw

  • net.gen.min_q_mvar / net.gen.max_q_mvar

  • net.sgen.min_p_mw / net.sgen.max_p_mw

  • net.sgen.min_q_mvar / net.sgen.max_q_mvar

  • net.dcline.max_p_mw

  • net.dcline.min_q_to_mvar / net.dcline.max_q_to_mvar / net.dcline.min_q_from_mvar / net.dcline.max_q_from_mvar

  • net.ext_grid.min_p_mw / net.ext_grid.max_p_mw

  • net.ext_grid.min_q_mvar / net.ext_grid.max_q_mvar

  • net.load.min_p_mw / net.load.max_p_mw

  • net.load.min_q_mvar / net.load.max_q_mvar

  • net.storage.min_p_mw / net.storage.max_p_mw

  • net.storage.min_q_mvar / net.storage.max_q_mvar

Controllable loads behave just like controllable static generators. It must be stated if they are controllable. Otherwise, they are not respected as flexibilities. Dc lines are controllable per default

Network constraints can be defined for buses, lines and transformers the elements in the following columns:

  • net.bus.min_vm_pu / net.bus.max_vm_pu

  • net.line.max_loading_percent

  • net.trafo.max_loading_percent

  • net.trafo3w.max_loading_percent

If the external grid ist controllable, the voltage setpoint of the external grid can be optimized within the voltage constraints by the OPF. The same applies to the voltage setpoints of the controllable generator elements.

How these costs are combined into a cost function depends on the cost_function parameter.

Parameters:

  • network (**net** - The pandapower format)

  • **verbose** (bool, False)

  • **suppress_warnings** (bool, True) – If set to True, warnings are disabled during the loadflow. Because of the way data is processed in pypower, ComplexWarnings are raised during the loadflow. These warnings are suppressed by this option, however keep in mind all other pypower warnings are suppressed, too.

  • **init** (str, "flat") – Starting solution vector (x0) for opf calculations is determined by this flag. Options are: “flat” (default): starting vector is (upper bound - lower bound) / 2 “pf”: a power flow is executed prior to the opf and the pf solution is the starting vector. This may improve convergence, but takes a longer runtime (which are probably neglectible for opf calculations) “results”: voltage magnitude vector is taken from result table

  • **delta** (float, 1e-10)

  • **trafo3w_losses** (str, "hv")

  • **consider_line_temperature** (bool, False)

  • arguments (**kwargs** - Pypower / Matpower keyword)

  • OPF_VIOLATION (-)

  • PDIPM_COSTTOL (-)

  • PDIPM_GRADTOL (-)

  • PDIPM_COMPTOL (-)

  • PDIPM_FEASTOL (-)

  • PDIPM_MAX_IT (-)

  • SCPDIPM_RED_IT (-)

The internal solver uses the interior point method. By default, the initial state is the center of the operational constraints. Another option would be to initialize the optimisation with a valid loadflow solution. For optimization of a timeseries, this warm start possibility could imply a significant speedup. This is not yet provided in the actual version, but could be an useful extension in the future.

References:

  • “On the Computation and Application of Multi-period Security-Constrained Optimal Power Flow for Real-time Electricity Market Operations”, Cornell University, May 2007.

  • H. Wang, C. E. Murillo-Sanchez, R. D. Zimmerman, R. J. Thomas, “On Computational Issues of Market-Based Optimal Power Flow”, IEEE Transactions on Power Systems, Vol. 22, No. 3, Aug. 2007, pp. 1185-1193.

  • R. D. Zimmerman, C. E. Murillo-Sánchez, and R. J. Thomas, “MATPOWER: Steady-State Operations, Planning and Analysis Tools for Power Systems Research and Education,” Power Systems, IEEE Transactions on, vol. 26, no. 1, pp. 12-19, Feb. 2011.

DC OPF

The dc optimal power flow is a linearized optimization of the grid state. It offers two cost function options, that are fitting special use cases. To understand the usage, the DC OPF tutorial is recommended.

pandapower.rundcopp(net, verbose=False, check_connectivity=True, suppress_warnings=True, switch_rx_ratio=0.5, delta=1e-10, trafo3w_losses='hv', **kwargs)

Runs the pandapower Optimal Power Flow. Flexibilities, constraints and cost parameters are defined in the pandapower element tables.

Flexibilities for generators can be defined in net.sgen / net.gen. net.sgen.controllable / net.gen.controllable signals if a generator is controllable. If False, the active and reactive power are assigned as in a normal power flow. If yes, the following flexibilities apply: - net.sgen.min_p_mw / net.sgen.max_p_mw - net.gen.min_p_mw / net.gen.max_p_mw - net.load.min_p_mw / net.load.max_p_mw

Network constraints can be defined for buses, lines and transformers the elements in the following columns: - net.line.max_loading_percent - net.trafo.max_loading_percent - net.trafo3w.max_loading_percent

Parameters:

  • network (**net** - The pandapower format)

  • **verbose** (bool, False)

  • **suppress_warnings** (bool, True) – If set to True, warnings are disabled during the loadflow. Because of the way data is processed in pypower, ComplexWarnings are raised during the loadflow. These warnings are suppressed by this option, however keep in mind all other pypower warnings are suppressed, too.

  • **delta** (float, 1e-10)

  • **trafo3w_losses** (str, "hv")

Flexibilities, costs and constraints (except voltage constraints) are handled as in the Optimisation problem. Voltage constraints are not considered in the DC OPF, since voltage magnitudes are not part of the linearized power flow equations.

Note

If you are interested in the pypower casefile that pandapower is using for power flow, you can find it in net[“_ppc_opf”]. However all necessary information is written into the pandapower format net, so the pandapower user should not usually have to deal with pypower.