Saving xlsx files that arent corrupted via openpyxl

Question

I am generating around 10000 xlsx files to run a Monte Carlo simulation using a program called AMPL.

To generate these files I am using the below python script using openpyxl. The xlsx file that results needs to still be opened and "save as" and replaced as the same xlsx in order for AMPL to recognize it.

I only know how to do this by hand but am looking into suggestions on:

1) What can I modify in the python script to avoid the file corruption so I don't have to save and replace this file by hand.

2) How to "Save as" a batch of xlsx files to the same name xlsx files.

Here is the code

"""
Created on Mon Mar  2 14:59:43 2020
USES OPENPYXL to generate mc tables WITH NAMED RANGE
@author: rsuthar
"""

import openpyxl
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import math
import scipy.stats as stats
#import seaborn as sns

for k in range(1,2):
    wb = openpyxl.Workbook() 
    sheet = wb.active

    #named range for COL table so that AMPL can read it
    new_range = openpyxl.workbook.defined_name.DefinedName('COL', attr_text='Sheet!$A$1:$D$64')
    wb.defined_names.append(new_range)

    #Probability
    #Storage temp as truncated normal
    #temperature as normal mean 55 with 5F variation
    storagetempfarenht = 55.4
    storagetempkelvin = (storagetempfarenht + 459.67) * (5.0/9.0)
    highesttemp=60.8
    lowesttemp=50
    sigma = ((highesttemp + 459.67) * (5.0/9.0)) - storagetempkelvin
    mu, sigma = storagetempkelvin, sigma
    lower, upper = mu-2*sigma , mu+2*sigma
    temp = stats.truncnorm.rvs((lower - mu) / sigma, (upper - mu) / sigma, loc=mu, scale=sigma, size=1)

    #Generate the color after each condition with temp uncertainty
    kterm=0.0019*math.exp((170604/8.314)*((1/288.15)-(1/temp)))
    Hterm = '=16.949*EXP((-0.025)*(42 +((124-42)/(1+((EXP(%f*A2:A64*(124-42)))*(124-(16.949*EXP((-0.025)*C2:C64))/((16.949*EXP((-0.025)*C2:C64)-42))))))))' % kterm


    #First column
    sheet['A1'] = 'DAYD'
    number_of_repeats = 5
    days=range(1,13)
    current_cell_num = 2

    for repeat in range(number_of_repeats):
        for day in days:
            cell_string = 'A%d' % current_cell_num
            sheet[cell_string] = day
            current_cell_num = current_cell_num + 1
        if repeat == number_of_repeats - 1:
            for day in range(13,16,1):
                cell_string = 'A%d' % current_cell_num
                sheet[cell_string] = day
                current_cell_num = current_cell_num + 1

    #Second Column
    sheet['B1'] = 'CROP'                   
    for i, rowOfCellObjects in enumerate(sheet['B2':'B64']):
        for n, cellObj in enumerate(rowOfCellObjects):
            cellObj.value = 'TA'  

    #Third Column
    sheet['C1'] = 'QUAL'     
    for i, rowOfCellObjects in enumerate(sheet['C2':'C13']):
        for n, cellObj in enumerate(rowOfCellObjects):
            cellObj.value = 2

    sheet['C1'] = 'QUAL'     
    for i, rowOfCellObjects in enumerate(sheet['C14':'C25']):
        for n, cellObj in enumerate(rowOfCellObjects):
            cellObj.value = 3

    sheet['C1'] = 'QUAL'     
    for i, rowOfCellObjects in enumerate(sheet['C26':'C37']):
        for n, cellObj in enumerate(rowOfCellObjects):
            cellObj.value = 4

    sheet['C1'] = 'QUAL'     
    for i, rowOfCellObjects in enumerate(sheet['C38':'C49']):
        for n, cellObj in enumerate(rowOfCellObjects):
            cellObj.value = 5

    sheet['C1'] = 'QUAL'     
    for i, rowOfCellObjects in enumerate(sheet['C50':'C64']):
        for n, cellObj in enumerate(rowOfCellObjects):
            cellObj.value = 1

    #fourth Column

    sheet['D1'] = 'COL'     

    for i, rowOfCellObjects in enumerate(sheet['D2':'D64']):
        for n, cellObj in enumerate(rowOfCellObjects):
            cellObj.value = Hterm

    #save the file everytime
    wb.save(filename='COL' + str(k) + '.xlsx')