OPF raises exception on array dimensions

[dchassin]

Issue

The attached casefile causes the following exception:

Traceback (most recent call last):
  File "/Users/david/GitHub/dchassin/regrow/model/raw2py.py", line 528, in <module>
    result = runopf(model.case)
  File "/usr/local/opt/gridlabd/4.3.17-250804-develop-darwin_23-x86_64/lib/python3.10/site-packages/pypower/runopf.py", line 31, in runopf
    r = opf(casedata, ppopt)
  File "/usr/local/opt/gridlabd/4.3.17-250804-develop-darwin_23-x86_64/lib/python3.10/site-packages/pypower/opf.py", line 172, in opf
    results, success, raw = opf_execute(om, ppopt)
  File "/usr/local/opt/gridlabd/4.3.17-250804-develop-darwin_23-x86_64/lib/python3.10/site-packages/pypower/opf_execute.py", line 81, in opf_execute
    results, success, raw = pipsopf_solver(om, ppopt)
  File "/usr/local/opt/gridlabd/4.3.17-250804-develop-darwin_23-x86_64/lib/python3.10/site-packages/pypower/pipsopf_solver.py", line 134, in pipsopf_solver
    solution = pips(f_fcn, x0, A, l, u, xmin, xmax, gh_fcn, hess_fcn, opt)
  File "/usr/local/opt/gridlabd/4.3.17-250804-develop-darwin_23-x86_64/lib/python3.10/site-packages/pypower/pips.py", line 266, in pips
    h = hn if Ai is None else r_[hn, Ai * x - bi] # inequality constraints
  File "/usr/local/opt/gridlabd/4.3.17-250804-develop-darwin_23-x86_64/lib/python3.10/site-packages/numpy/lib/index_tricks.py", line 419, in __getitem__
    res = self.concatenate(tuple(objs), axis=axis)
  File "<__array_function__ internals>", line 200, in concatenate
ValueError: all the input arrays must have same number of dimensions, but the array at index 0 has 2 dimension(s) and the array at index 1 has 1 dimension(s)

Remarks

Given the nature of the project in which this occurs, it's quite possible the casefile is invalid. But the case file appears to be well-formatted and the data from PSS/E appears to be ok. In general, any problem with the case data should be diagnosed prior to constructing matrices that cannot be handled by the solver.

wecc240_psse.py

[dchassin]

Diagnosis: the problem occurs because there are no line flow constraints in this particular model and this condition is not handled by the pips setup routine. In the interim, it's easy enough to add a non-zero RATE_A to any of the branches and the problem goes away.

Leaving this open as a long-term outstanding issue.