Merge branch 'main' into test-simple-efficiency-vectorized

Author: aman-coder03

docs/sphinx/source/whatsnew/v0.15.1.rst

@@ -14,7 +14,9 @@ Deprecations
 
 Bug fixes
 ~~~~~~~~~
-
+* Fix a division-by-zero condition in
+  :py:func:`pvlib.transformer.simple_efficiency` when ``load_loss = 0``.
+  (:issue:`2645`, :pull:`2646`)
 
 Enhancements
 ~~~~~~~~~~~~
@@ -42,4 +44,5 @@ Maintenance
 
 Contributors
 ~~~~~~~~~~~~
+* Aman Srivastava (:ghuser:`aman-coder03`)
 

pvlib/iotools/bsrn.py

@@ -148,9 +148,9 @@ def get_bsrn(station, start, end, username, password,
         <https://bsrn.awi.de/>`_
     .. [2] `BSRN Data Retrieval via FTP
        <https://bsrn.awi.de/data/data-retrieval-via-ftp/>`_
-    .. [4] `BSRN Data Release Guidelines
+    .. [3] `BSRN Data Release Guidelines
        <https://bsrn.awi.de/data/conditions-of-data-release/>`_
-    .. [3] `Update of the Technical Plan for BSRN Data Management, 2013,
+    .. [4] `Update of the Technical Plan for BSRN Data Management, 2013,
        Global Climate Observing System (GCOS) GCOS-174.
        <https://bsrn.awi.de/fileadmin/user_upload/bsrn.awi.de/Publications/gcos-174.pdf>`_
     """  # noqa: E501

pvlib/transformer.py

@@ -111,7 +111,10 @@ def simple_efficiency(
     b = 1
     c = no_load_loss - input_power_normalized
 
-    output_power_normalized = (-b + (b**2 - 4*a*c)**0.5) / (2 * a)
+    # alternative form of the quadratic equation to avoid
+    # divide-by-zero when a == 0
+    disc = (b*b - 4*a*c)**0.5
+    output_power_normalized = 2*c / (-b - disc)
 
     output_power = output_power_normalized * transformer_rating
     return output_power

tests/test_transformer.py

@@ -1,4 +1,5 @@
 import pandas as pd
+import pytest
 
 from numpy.testing import assert_allclose
 
@@ -98,3 +99,22 @@ def test_simple_efficiency_vector_equals_scalar():
     ])
 
     assert_allclose(vector_result, scalar_result)
+@pytest.mark.parametrize(
+    "input_power, no_load_loss, load_loss, transformer_rating, expected",
+    [
+        (1000.0, 0.01, 0.0, 1000.0, 990.0),
+    ],
+)
+def test_simple_efficiency_zero_load_loss(
+    input_power, no_load_loss, load_loss, transformer_rating, expected
+):
+    # for load_loss = 0, the model reduces to:
+    # P_out = P_in - L_no_load * P_nom
+    result = transformer.simple_efficiency(
+        input_power=input_power,
+        no_load_loss=no_load_loss,
+        load_loss=load_loss,
+        transformer_rating=transformer_rating,
+    )
+
+    assert_allclose(result, expected)