Merge branch 'develop' of https://github.com/e2nIEE/pandapower into d…

…evelop

pandapower/converter/pypower/to_ppc.py

@@ -45,7 +45,7 @@ def to_ppc(net, calculate_voltage_angles=False, trafo_model="t", switch_rx_ratio
         **switch_rx_ratio** (float, 2) - 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 
+        switch table and this parameter
 
         **check_connectivity** (bool, True) - Perform an extra connectivity test after the
         conversion from pandapower to PYPOWER

pandapower/create.py

@@ -297,7 +297,7 @@ def create_empty_network(name="", f_hz=50., sn_mva=1, add_stdtypes=True):
             ('order', "float64"),
             ('level', dtype(object)),
             ('initial_run', "bool"),
-            ("recycle", "bool"),
+            ("recycle", dtype(object)),
         ],
         # geodata
         "line_geodata": [("coords", dtype(object))],
@@ -3345,10 +3345,6 @@ def create_measurement(net, meas_type, element_type, value, std_dev, element, si
         4.5 MVar line measurement with 0.1 MVar standard deviation on the "to_bus" side of line 2
         create_measurement(net, "q", "line", 2, 4.5, 0.1, "to")
     """
-    if meas_type in ("p", "q") and element_type == "bus":
-        logger.warning("Attention! Signing system of P,Q measurement of buses now changed to load "
-                       "reference (match pandapower res_bus pq)!")
-
     if meas_type not in ("v", "p", "q", "i", "va", "ia"):
         raise UserWarning("Invalid measurement type ({})".format(meas_type))
 

pandapower/estimation/algorithm/base.py

@@ -60,7 +60,7 @@ def initialize(self, eppci: ExtendedPPCI):
         self.pp_meas_indices = eppci.pp_meas_indices
         self.check_observability(eppci, eppci.z)
 
-    def estimate(self, ppci: ExtendedPPCI, **kwargs):
+    def estimate(self, eppci: ExtendedPPCI, **kwargs):
         # Must be implemented individually!!
         pass
 
@@ -76,7 +76,7 @@ def __init__(self, tolerance, maximum_iterations, logger=std_logger):
         self.H = None
         self.hx = None
 
-    def estimate(self, eppci, **kwargs):
+    def estimate(self, eppci: ExtendedPPCI, **kwargs):
         self.initialize(eppci)
         # matrix calculation object
         sem = BaseAlgebra(eppci)
@@ -129,7 +129,7 @@ def estimate(self, eppci, **kwargs):
 
 
 class WLSZeroInjectionConstraintsAlgorithm(BaseAlgorithm):
-    def estimate(self, eppci, **kwargs):
+    def estimate(self, eppci: ExtendedPPCI, **kwargs):
         # state vector built from delta, |V| and zero injections
         # Find pq bus with zero p,q and shunt admittance
         if not np.any(eppci["bus"][:, bus_cols + ZERO_INJ_FLAG]):
@@ -199,7 +199,7 @@ def estimate(self, eppci, **kwargs):
 
 
 class IRWLSAlgorithm(BaseAlgorithm):
-    def estimate(self, eppci, estimator="wls", **kwargs):
+    def estimate(self, eppci: ExtendedPPCI, estimator="wls", **kwargs):
         self.initialize(eppci)
 
         # matrix calculation object

pandapower/estimation/algorithm/estimator.py

@@ -64,7 +64,7 @@ def create_cost_jacobian(self, E):
         # dr/dE = drho / dr * d(z-hx) / dE
         # dr/dE = (drho/dr) * - (d(hx)/dE)
         # 2 * rx * (1/sigma**2)* -(dhx/dE)
-        rx = self.create_rx(E) 
+        rx = self.create_rx(E)
         hx_jac = self.create_hx_jacobian(E)
         drho_dr = 2 * (rx * (1/self.sigma**2))
         jac = - np.sum(drho_dr.reshape((-1, 1)) * hx_jac, axis=0)
@@ -83,11 +83,11 @@ def __init__(self, eppci: ExtendedPPCI, **hyperparameters):
 
     def create_phi(self, E):
         r = self.create_rx(E)
-        chi2_res, w = self.weight(E)
+        _, w = self.weight(E)
         rsi = r / (w * self.sigma)
         phi = 1/(self.sigma**2)
         condition_mask = np.abs(rsi)>self.a
-        phi[condition_mask] = (1/(self.sigma**2) * np.abs(self.a / rsi))[condition_mask] 
+        phi[condition_mask] = (1/(self.sigma**2) * np.abs(self.a / rsi))[condition_mask]
         return np.diagflat(phi)
 
     def weight(self, E):
@@ -97,7 +97,8 @@ def weight(self, E):
         ps = self._ps(H)
         return chi2_res, np.min(np.c_[(chi2_res/ps)**2, np.ones(ps.shape)], axis=1)
 
-    def _ps(self, H):
+    @staticmethod
+    def _ps(H):
         omega = np.dot(H, H.T)
 
         x = np.zeros(omega.shape[0]-1)
@@ -180,7 +181,7 @@ def create_cost_jacobian(self, E):
 
 class QLEstimatorOpt(BaseEstimatorOpt):
     def __init__(self, eppci, **hyperparameters):
-        super(QLEstimatorOpt, self).__init__(eppci, **hyperparameters)     
+        super(QLEstimatorOpt, self).__init__(eppci, **hyperparameters)
         assert 'a' in hyperparameters
         self.a = hyperparameters['a']
 
@@ -203,6 +204,6 @@ def create_cost_jacobian(self, E):
         drho_dr = 2 * (rx * (1/self.sigma)**2)
         large_dev_mask = np.abs(rx/self.sigma) > self.a
         if np.any(large_dev_mask):
-            drho_dr[large_dev_mask] = (np.sign(rx)* (1/self.sigma))[large_dev_mask] 
-        jac = - np.sum(drho_dr.reshape((-1, 1)) * hx_jac, axis=0)  
+            drho_dr[large_dev_mask] = (np.sign(rx)* (1/self.sigma))[large_dev_mask]
+        jac = - np.sum(drho_dr.reshape((-1, 1)) * hx_jac, axis=0)
         return jac

pandapower/estimation/algorithm/lp.py

@@ -7,12 +7,13 @@
 from scipy.optimize import linprog
 import warnings
 
+from pandapower.estimation.ppc_conversion import ExtendedPPCI
 from pandapower.estimation.algorithm.base import BaseAlgorithm
 from pandapower.estimation.algorithm.matrix_base import BaseAlgebra
 
 
 class LPAlgorithm(BaseAlgorithm):
-    def estimate(self, eppci, **kwargs):
+    def estimate(self, eppci: ExtendedPPCI, **kwargs):
         if "estimator" in kwargs and kwargs["estimator"].lower() != "lav":  # pragma: no cover
             self.logger.warning("LP Algorithm supports only LAV Estimator!! Set to LAV!!")
 
@@ -49,7 +50,8 @@ def estimate(self, eppci, **kwargs):
         self.check_result(current_error, cur_it)
         return eppci
 
-    def solve_lp(self, H, x, r):
+    @staticmethod
+    def solve_lp(H, x, r):
         n, m = H.shape[1], H.shape[0]
         zero_n = np.zeros((n, 1))
         one_m = np.ones((m, 1))

pandapower/estimation/algorithm/matrix_base.py

@@ -3,13 +3,10 @@
 # Copyright (c) 2016-2021 by University of Kassel and Fraunhofer Institute for Energy Economics
 # and Energy System Technology (IEE), Kassel. All rights reserved.
 
-import warnings
 import numpy as np
-from scipy.sparse import vstack, hstack, diags
-from scipy.sparse import csr_matrix as sparse
+from scipy.sparse import vstack, hstack
 
 from pandapower.pypower.idx_brch import F_BUS, T_BUS
-from pandapower.pypower.makeYbus import makeYbus
 from pandapower.pypower.dSbus_dV import dSbus_dV
 from pandapower.pypower.dSbr_dV import dSbr_dV
 from pandapower.pypower.dIbr_dV import dIbr_dV
@@ -21,6 +18,7 @@
 
 class BaseAlgebra:
     def __init__(self, eppci: ExtendedPPCI):
+        """Object to calculate matrices required in state-estimation iterations."""
         self.eppci = eppci
 
         self.fb = eppci['branch'][:, F_BUS].real.astype(int)
@@ -140,11 +138,13 @@ def _dSbr_dv(self, V):
         dSf_dth, dSf_dv, dSt_dth, dSt_dv, _, _ = dSbr_dV(self.eppci['branch'], self.Yf, self.Yt, V)
         return dSf_dth, dSf_dv, dSt_dth, dSt_dv
 
-    def _dvmbus_dV(self, V):
+    @staticmethod
+    def _dvmbus_dV(V):
         dvm_dth, dvm_dv = np.zeros((V.shape[0], V.shape[0])), np.eye(V.shape[0], V.shape[0])
         return dvm_dth, dvm_dv
 
-    def _dvabus_dV(self, V):
+    @staticmethod
+    def _dvabus_dV(V):
         dva_dth, dva_dv = np.eye(V.shape[0], V.shape[0]), np.zeros((V.shape[0], V.shape[0]))
         return dva_dth, dva_dv
 
@@ -160,7 +160,7 @@ def _dimiabr_dV(self, V):
         difa_dv = (np.angle(1e-5 * dif_dv + If.reshape((-1, 1))) - np.angle(If.reshape((-1, 1))))/1e-5
         dita_dth = (np.angle(1e-5 * dit_dth + It.reshape((-1, 1))) - np.angle(It.reshape((-1, 1))))/1e-5
         dita_dv = (np.angle(1e-5 * dit_dv + It.reshape((-1, 1))) - np.angle(It.reshape((-1, 1))))/1e-5
-        return difm_dth, difm_dv, ditm_dth, ditm_dv, difa_dth, difa_dv, dita_dth, dita_dv   
+        return difm_dth, difm_dv, ditm_dth, ditm_dv, difa_dth, difa_dv, dita_dth, dita_dv
 
 
 class BaseAlgebraZeroInjConstraints(BaseAlgebra):

pandapower/estimation/algorithm/optimization.py

@@ -5,23 +5,22 @@
 
 from scipy.optimize import minimize
 
+from pandapower.estimation.ppc_conversion import ExtendedPPCI
 from pandapower.estimation.algorithm.base import BaseAlgorithm
 from pandapower.estimation.algorithm.estimator import BaseEstimatorOpt, get_estimator
 
 # DEFAULT_OPT_METHOD = "Newton-CG"
 DEFAULT_OPT_METHOD = "TNC"
-
-
 # DEFAULT_OPT_METHOD = "SLSQP"
 # DEFAULT_OPT_METHOD = 'L-BFGS-B'
 
 
 class OptAlgorithm(BaseAlgorithm):
-    def estimate(self, eppci, estimator="wls", **opt_vars):
-        opt_method = DEFAULT_OPT_METHOD if 'opt_method' not in opt_vars else opt_vars['opt_method']
+    def estimate(self, eppci: ExtendedPPCI, estimator="wls", **kwargs):
+        opt_method = DEFAULT_OPT_METHOD if 'opt_method' not in kwargs else kwargs['opt_method']
 
         # matrix calculation object
-        estm = get_estimator(BaseEstimatorOpt, estimator)(eppci, **opt_vars)
+        estm = get_estimator(BaseEstimatorOpt, estimator)(eppci, **kwargs)
 
         jac = estm.create_cost_jacobian
         res = minimize(estm.cost_function, x0=eppci.E,

pandapower/estimation/ppc_conversion.py

@@ -413,7 +413,7 @@ def pp2eppci(net, v_start=None, delta_start=None,
 
 class ExtendedPPCI(UserDict):
     def __init__(self, ppci):
-        # Initialize ppci with measurements
+        """Initialize ppci object with measurements."""
         self.data = ppci
 
         # Measurement relevant parameters

pandapower/estimation/state_estimation.py

@@ -50,19 +50,19 @@ def estimate(net, algorithm='wls',
 
         **calculate_voltage_angles** - (boolean) - Take into account absolute voltage angles and phase
         shifts in transformers, if init is 'slack'. Default is True
-        
+
         **zero_injection** - (str, iterable, None) - Defines which buses are zero injection bus or the method
-        to identify zero injection bus, with 'wls_estimator' virtual measurements will be added, with 
+        to identify zero injection bus, with 'wls_estimator' virtual measurements will be added, with
         'wls_estimator with zero constraints' the buses will be handled as constraints
             "auto": all bus without p,q measurement, without p, q value (load, sgen...) and aux buses will be
-                identified as zero injection bus  
+                identified as zero injection bus
             "aux_bus": only aux bus will be identified as zero injection bus
             None: no bus will be identified as zero injection bus
             iterable: the iterable should contain index of the zero injection bus and also aux bus will be identified
                 as zero-injection bus
 
-        **fuse_buses_with_bb_switch** - (str, iterable, None) - Defines how buses with closed bb switches should 
-        be handled, if fuse buses will only fused to one for calculation, if not fuse, an auxiliary bus and 
+        **fuse_buses_with_bb_switch** - (str, iterable, None) - Defines how buses with closed bb switches should
+        be handled, if fuse buses will only fused to one for calculation, if not fuse, an auxiliary bus and
         auxiliary line will be automatically added to the network to make the buses with different p,q injection
         measurements identifieble
             "all": all buses with bb-switches will be fused, the same as the default behaviour in load flow

pandapower/estimation/util.py

@@ -183,7 +183,7 @@ def add_virtual_pmu_meas_from_loadflow(net, v_std_dev=0.001, i_std_dev=0.1,
                         'trafo3w': {'side': ('hv', 'mv', 'lv'),
                                     'meas_type': ('i_ka', 'ia_degree', 'p_mw', 'q_mvar')}}
 
-    # Added degree result for branches    
+    # Added degree result for branches
     for br_type in branch_meas_type.keys():
         for side in branch_meas_type[br_type]['side']:
             p, q, vm, va = net["res_" + br_type]["p_%s_mw" % side].values, \

pandapower/plotting/collections.py

@@ -314,8 +314,9 @@ def _create_complex_branch_collection(coords, patch_maker, size=1, infos=None, r
         infos_pc = list(np.repeat(infos, repeat_infos[0]))
         infos_lc = list(np.repeat(infos, repeat_infos[1]))
 
-    lines, patches, popped_keywords = patch_maker(coords, size, patch_facecolor=patch_facecolor,
-                                                  patch_edgecolor=patch_edgecolor, linewidths=linewidths, **kwargs)
+    lines, patches, popped_keywords = patch_maker(
+        coords, size, patch_facecolor=patch_facecolor, patch_edgecolor=patch_edgecolor,
+        linewidths=linewidths, **kwargs)
     for kw in set(popped_keywords) & set(kwargs.keys()):
         kwargs.pop(kw)
     patch_coll = PatchCollection(patches, match_original=True, picker=picker, **kwargs)
@@ -908,7 +909,7 @@ def create_gen_collection(net, gens=None, size=1., infofunc=None, orientation=np
     """
     gens = get_index_array(gens, net.gen.index)
     infos = [infofunc(i) for i in range(len(gens))] if infofunc is not None else []
-    node_coords = net.bus_geodata.loc[:, ["x", "y"]].values[net.gen.loc[gens, "bus"].values]
+    node_coords = net.bus_geodata.loc[net.gen.loc[gens, "bus"].values, ["x", "y"]].values
     gen_pc, gen_lc = _create_node_element_collection(
         node_coords, gen_patches, size=size, infos=infos, orientation=orientation,
         picker=picker, **kwargs)
@@ -950,16 +951,18 @@ def create_sgen_collection(net, sgens=None, size=1., infofunc=None, orientation=
         picker=picker, **kwargs)
     return sgen_pc, sgen_lc
 
-def create_storage_collection(net, storages=None, size=1., infofunc=None, orientation=np.pi, picker=False,
-                           **kwargs):
+
+def create_storage_collection(net, storages=None, size=1., infofunc=None, orientation=np.pi,
+                              picker=False, **kwargs):
     """
     Creates a matplotlib patch collection of pandapower storage element.
 
     Input:
         **net** (pandapowerNet) - The pandapower network
 
     OPTIONAL:
-        **storages** (list of ints, None) - the net.storage.index values to include in the collection
+        **storages** (list of ints, None) - the net.storage.index values to include in the
+        collection
 
         **size** (float, 1) - patch size
 
@@ -984,6 +987,7 @@ def create_storage_collection(net, storages=None, size=1., infofunc=None, orient
         picker=picker, **kwargs)
     return storage_pc, storage_lc
 
+
 def create_ext_grid_collection(net, size=1., infofunc=None, orientation=0, picker=False,
                                ext_grids=None, ext_grid_buses=None, **kwargs):
     """

pandapower/plotting/patch_makers.py

@@ -210,8 +210,7 @@ def gen_patches(node_coords, size, angles, **kwargs):
         polys.append(
             Arc(p2 + np.array([size / 6.2, size / 2.6]), size / 2, size, theta1=245, theta2=300,
                 ec=edgecolors[i]))
-        print("Arc:", polys[-1])
-        lines.append((node_geo, p2 + np.array([0, size])))
+        lines.append((node_geo, p2 + _rotate_dim2(np.array([0, size]), -all_angles[i])))
     return lines, polys, {"offset", "patch_edgecolor", "patch_facecolor"}
 
 

pandapower/plotting/plotly/mapbox_plot.py

@@ -67,8 +67,10 @@ def geo_data_to_latlong(net, projection):
         logger.warning('Geo-coordinates check cannot be peformed because pyproj package not available \n\t--> '
                        'if geo-coordinates are not in lat/lon format an empty plot may appear...')
         return
+
     if projection == 'epsg:4326':
         return
+
     wgs84 = Proj(init='epsg:4326')  # lat/long
 
     try:

pandapower/pypower/makeLODF.py

@@ -7,8 +7,8 @@
 # Copyright (c) 2016-2021 by University of Kassel and Fraunhofer Institute for Energy Economics
 # and Energy System Technology (IEE), Kassel. All rights reserved.
 
-"""Builds the line outage distribution factor matrix.
-"""
+# Builds the line outage distribution factor matrix.
+
 
 from numpy import ones, diag, r_, arange
 import numpy as np

pandapower/pypower/makePTDF.py

@@ -7,8 +7,8 @@
 # Copyright (c) 2016-2021 by University of Kassel and Fraunhofer Institute for Energy Economics
 # and Energy System Technology (IEE), Kassel. All rights reserved.
 
-"""Builds the DC PTDF matrix for a given choice of slack.
-"""
+# Builds the DC PTDF matrix for a given choice of slack.
+
 
 from sys import stderr