OpenMDAO add a list entry as a design variable

Is it possible to optimize a single list entry in OpenMDAO 1.X? In this example, I desire to add/optimize the first entry of z. In my real problem, it is impossible for me to add the entire vector as a design variable (I'm using NREL's DAKOTA driver). I thought I could make dummy variables connected to z, but looks like 1.X does not support connecting variables to list entries.

ppb.py:

from __future__ import print_function
import numpy as np
from dakota_driver.driver import pydakdriver
from openmdao.api import ScipyOptimizer
from openmdao.api import IndepVarComp, Component, Problem, Group

class Paraboloid(Component):
    """ Evaluates the equation f(x,y) = (x-3)^2 + xy + (y+4)^2 - 3 """

    def __init__(self):
        super(Paraboloid, self).__init__()

        self.add_param('x', val=6.0)
        self.add_param('y', val=-7.0)
        self.add_param('z', val=np.array([2., 2., 2.]))

        self.add_output('f_xy', val=0.0)

    def solve_nonlinear(self, params, unknowns, resids):
        """f(x,y) = (x-3)^2 + xy + (y+4)^2 - 3
        """

        x = params['x']
        y = params['y']
        z = params['z']

        unknowns['f_xy'] = z[0]*(x-3.0)**2 + x*y + (y+4.0)**2 - 3.0 + abs(z[0]-4)

    def linearize(self, params, unknowns, resids):
        """ Jacobian for our paraboloid."""

        x = params['x']
        y = params['y']
        z = params['z']
        J = {}

        J['f_xy', 'x'] = 2.0*x - 6.0 + y
        J['f_xy', 'y'] = 2.0*y + 8.0 + x
        J['f_xy', 'z'] = (x-3.0)**2 + 1
        return J
top = Problem()

root = top.root = Group()

root.add('p1', IndepVarComp('x', 13.0))
root.add('p2', IndepVarComp('y', -14.0))
root.add('p3', IndepVarComp('z', np.array([0.0, 0., 0.])))
root.add('p', Paraboloid())

root.connect('p1.x', 'p.x')
root.connect('p2.y', 'p.y')
root.connect('p3.z', 'p.z')


top.driver = ScipyOptimizer()
top.driver.options['optimizer'] = 'Powell'


top.driver.add_desvar('p3.z[0]', lower=-30., upper=30.) # <--- Is it possible to do this?

top.driver.add_objective('p.f_xy')

top.setup()

top['p1.x'] = 3.0
top['p2.y'] = -4.0
#top['p3.z'] = 2.0
top['p3.z'] = np.array([0., 0., 0.])

top.run()

Run Results:

$ python ppb.py 
Traceback (most recent call last):
  File "ppb.py", line 75, in <module>
    top.setup()
  File "/scratch/jquick/1.0/lib/python2.7/site-packages/openmdao/core/problem.py", line 586, in setup
    raise NameError("Can't find param of interest '%s'." % v)
NameError: Can't find param of interest 'p3.z[0]'.