Validation 13 - 5 BusΒΆ
In [1]:
from psst.case import read_matpower
In [2]:
case = read_matpower('./../../psst/cases/case5.m')
In [3]:
case.gen
Out[3]:
| GEN_BUS | PG | QG | QMAX | QMIN | VG | MBASE | GEN_STATUS | PMAX | PMIN | PC1 | PC2 | QC1MIN | QC1MAX | QC2MIN | QC2MAX | RAMP_AGC | RAMP_10 | RAMP_30 | RAMP_Q | APF | STARTUP_RAMP | SHUTDOWN_RAMP | MINIMUM_UP_TIME | MINIMUM_DOWN_TIME | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| GenCo0 | Bus1 | 40.00 | 0 | 30.0 | -30.0 | 1 | 100 | 1 | 40 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 40 | 0 | 0 | 0 | 40 | 40 | 0 | 0 |
| GenCo1 | Bus1 | 170.00 | 0 | 127.5 | -127.5 | 1 | 100 | 1 | 170 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 170 | 0 | 0 | 0 | 170 | 170 | 0 | 0 |
| GenCo2 | Bus3 | 323.49 | 0 | 390.0 | -390.0 | 1 | 100 | 1 | 520 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 520 | 0 | 0 | 0 | 520 | 520 | 0 | 0 |
| GenCo3 | Bus4 | 0.00 | 0 | 150.0 | -150.0 | 1 | 100 | 1 | 200 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 200 | 0 | 0 | 0 | 200 | 200 | 0 | 0 |
| GenCo4 | Bus5 | 466.51 | 0 | 450.0 | -450.0 | 1 | 100 | 1 | 600 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 600 | 0 | 0 | 0 | 600 | 600 | 0 | 0 |
In [4]:
case.gencost
Out[4]:
| MODEL | STARTUP | SHUTDOWN | NCOST | COST_2 | COST_1 | COST_0 | |
|---|---|---|---|---|---|---|---|
| GenCo0 | 2 | 0 | 0 | 3 | 0.005 | 14 | 56.90 |
| GenCo1 | 2 | 0 | 0 | 3 | 0.006 | 15 | 0.11 |
| GenCo2 | 2 | 0 | 0 | 3 | 0.010 | 25 | 2267.53 |
| GenCo3 | 2 | 0 | 0 | 3 | 0.012 | 30 | 5.19 |
| GenCo4 | 2 | 0 | 0 | 3 | 0.007 | 10 | 1391.16 |
In [5]:
case.branch
Out[5]:
| F_BUS | T_BUS | BR_R | BR_X | BR_B | RATE_A | RATE_B | RATE_C | TAP | SHIFT | BR_STATUS | ANGMIN | ANGMAX | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Bus1 | Bus2 | 0.00281 | 0.0281 | 0.00712 | 400 | 400 | 400 | 0 | 0 | 1 | -360 | 360 |
| 1 | Bus1 | Bus4 | 0.00304 | 0.0304 | 0.00658 | 0 | 0 | 0 | 0 | 0 | 1 | -360 | 360 |
| 2 | Bus1 | Bus5 | 0.00064 | 0.0064 | 0.03126 | 0 | 0 | 0 | 0 | 0 | 1 | -360 | 360 |
| 3 | Bus2 | Bus3 | 0.00108 | 0.0108 | 0.01852 | 0 | 0 | 0 | 0 | 0 | 1 | -360 | 360 |
| 4 | Bus3 | Bus4 | 0.00297 | 0.0297 | 0.00674 | 0 | 0 | 0 | 0 | 0 | 1 | -360 | 360 |
| 5 | Bus4 | Bus5 | 0.00297 | 0.0297 | 0.00674 | 240 | 240 | 240 | 0 | 0 | 1 | -360 | 360 |
In [6]:
from psst.case.utils import solve_pf
results, _ = solve_pf(case)
In [9]:
import pandas as pd
In [10]:
pd.DataFrame(results['branch'])
Out[10]:
| 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1.0 | 2.0 | 0.00281 | 0.0281 | 0.00712 | 400.0 | 400.0 | 400.0 | 0.0 | 0.0 | 1.0 | -360.0 | 360.0 | 249.773373 | 21.599095 | -248.006760 | -4.637368 |
| 1 | 1.0 | 4.0 | 0.00304 | 0.0304 | 0.00658 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | -360.0 | 360.0 | 186.500142 | -13.612148 | -185.437396 | 23.581606 |
| 2 | 1.0 | 5.0 | 0.00064 | 0.0064 | 0.03126 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | -360.0 | 360.0 | -226.273515 | 22.738212 | 226.604972 | -22.549636 |
| 3 | 2.0 | 3.0 | 0.00108 | 0.0108 | 0.01852 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | -360.0 | 360.0 | -51.993240 | -93.972632 | 52.118657 | 93.394588 |
| 4 | 3.0 | 4.0 | 0.00297 | 0.0297 | 0.00674 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | -360.0 | 360.0 | -28.628657 | 2.650132 | 28.653264 | -3.078060 |
| 5 | 4.0 | 5.0 | 0.00297 | 0.0297 | 0.00674 | 240.0 | 240.0 | 240.0 | 0.0 | 0.0 | 1.0 | -360.0 | 360.0 | -238.188688 | 32.149384 | 239.905028 | -15.659987 |
In [11]:
pd.DataFrame(results['bus'])
Out[11]:
| 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1.0 | 2.0 | 0.0 | 0.00 | 0.0 | 0.0 | 1.0 | 1.000000 | 3.273361 | 230.0 | 1.0 | 1.1 | 0.9 |
| 1 | 2.0 | 1.0 | 300.0 | 98.61 | 0.0 | 0.0 | 1.0 | 0.989261 | -0.759269 | 230.0 | 1.0 | 1.1 | 0.9 |
| 2 | 3.0 | 2.0 | 300.0 | 98.61 | 0.0 | 0.0 | 1.0 | 1.000000 | -0.492259 | 230.0 | 1.0 | 1.1 | 0.9 |
| 3 | 4.0 | 3.0 | 400.0 | 131.47 | 0.0 | 0.0 | 1.0 | 1.000000 | 0.000000 | 230.0 | 1.0 | 1.1 | 0.9 |
| 4 | 5.0 | 2.0 | 0.0 | 0.00 | 0.0 | 0.0 | 1.0 | 1.000000 | 4.112031 | 230.0 | 1.0 | 1.1 | 0.9 |
In [12]:
from psst.model import build_model
In [13]:
model = build_model(case)
In [14]:
model.solve(solver='xpress', verbose=True)
FICO Xpress-Optimizer 64-bit v29.01.10 (Hyper capacity)
(c) Copyright Fair Isaac Corporation 1983-2016. All rights reserved
Using Xpress-Optimizer [/Users/dkrishna/opt/xpressmp/lib/libxprs.dylib]
Reading Problem /tmpgRr1VC.pyomo
Problem Statistics
106 ( 0 spare) rows
87 ( 0 spare) structural columns
239 ( 0 spare) non-zero elements
Global Statistics
5 entities 0 sets 0 set members
Minimizing MILP /tmpgRr1VC.pyomo
Original problem has:
106 rows 87 cols 239 elements 5 globals
Presolved problem has:
16 rows 31 cols 61 elements 5 globals
Will try to keep branch and bound tree memory usage below 5.5Gb
Starting concurrent solve with dual
Concurrent-Solve, 0s
Dual
objective dual inf
D 20013.800 .0000000
------- optimal --------
Concurrent statistics:
Dual: 13 simplex iterations, 0.00s
Optimal solution found
Its Obj Value S Ninf Nneg Sum Dual Inf Time
13 20013.80036 D 0 0 .000000 0
Dual solved problem
13 simplex iterations in 0s
Final objective : 2.001380036213346e+04
Max primal violation (abs / rel) : 2.274e-13 / 2.274e-13
Max dual violation (abs / rel) : 0.0 / 0.0
Max complementarity viol. (abs / rel) : 0.0 / 0.0
All values within tolerances
Starting root cutting & heuristics
Its Type BestSoln BestBound Sols Add Del Gap GInf Time
k 22255.36973 20013.80036 1 10.07% 0 0
*** Search completed *** Time: 0 Nodes: 1
Number of integer feasible solutions found is 1
Best integer solution found is 22255.36973
Best bound is 22255.36973
Uncrunching matrix
In [33]:
s1 = (model.results.angles / 2 / pd.np.pi * 360).T[0]
In [34]:
case.gen['PG'] = model.results.power_generated.T[0]
from psst.case.utils import solve_pf
results, _ = solve_pf(case)
s2 = pd.DataFrame(results['bus'])[8]
In [44]:
np = pd.np
In [45]:
def rms(x):
return np.sqrt(x.dot(x)/x.size)
In [46]:
rms(s1.values - s2.values)
Out[46]:
0.052620045089577835
