test30_2.asv

node insertion power flow

function [baseMVA, bus, gen, branch, areas, gencost] = test30_2(i,bus)
%CASE30    Power flow data for 30 bus, 6 generator case.
%   Please see 'help caseformat' for details on the case file format.
%
%   Based on data from ...
%     Alsac, O. & Stott, B., "Optimal Load Flow with Steady State Security",
%     IEEE Transactions on Power Apparatus and Systems, Vol. PAS 93, No. 3,
%     1974, pp. 745-751.
%   ... with branch parameters rounded to nearest 0.01, shunt values divided
%   by 100 and shunt on bus 10 moved to bus 5, load at bus 5 zeroed out.
%   Generator locations, costs and limits and bus areas were taken from ...
%     Ferrero, R.W., Shahidehpour, S.M., Ramesh, V.C., "Transaction analysis
%     in deregulated power systems using game theory", IEEE Transactions on
%     Power Systems, Vol. 12, No. 3, Aug 1997, pp. 1340-1347.
%   Generator Q limits were derived from Alsac & Stott, using their Pmax
%   capacities. V limits and line |S| limits taken from Alsac & Stott.

%   MATPOWER
%   $Id: case30.m,v 1.7 2004/09/21 02:41:49 ray Exp $

%%-----  Power Flow Data  -----%%
%% system MVA base
baseMVA = 100;
pr=[1.01 1.01 1.01 1.01 1.01];
bus(:,3:4)=bus(:,3:4)*pr(i-1);
%% generator data
%	bus	Pg	Qg	Qmax	Qmin	Vg	mBase	status	Pmax	Pmin
gen = [
	28	23.54	0	150	-20	1	100	1	80	0;
	29	60.97	0	60	-20	1	100	1	80	0;
	19	21.59	0	62.5	-15	1	100	1	50	0;
	11	26.91	0	48.7	-15	1	100	1	55	0;
	4	19.2	0	40	-10	1	100	1	30	0;
	27	37	0	44.7	-15	1	100	1	40	0;
];

%% branch data
%	fbus	tbus	r	x	b	rateA	rateB	rateC	ratio	angle	status
branch = [
	28	29	0.02	0.06	0.03	130	130	130	0	0	1;
	28	25	0.05	0.19	0.02	130	130	130	0	0	1;
	29	23	0.06	0.17	0.02	65	65	65	0	0	1;
	25	23	0.01	0.04	0	130	130	130	0	0	1;
	29	30	0.05	0.2	0.02	130	130	130	0	0	1;
	29	2	0.06	0.18	0.02	65	65	65	0	0	1;
	23	2	0.01	0.04	0	90	90	90	0	0	1;
	30	26	0.05	0.12	0.01	70	70	70	0	0	1;
	2	26	0.03	0.08	0.01	130	130	130	0	0	1;
	2	6	0.01	0.04	0	32	32	32	0	0	1;
	2	5	0	0.21	0	65	65	65	0	0	1;
	2	14	0	0.56	0	32	32	32	0	0	1;
	5	15	0	0.21	0	65	65	65	0	0	1;
	5	14	0	0.11	0	65	65	65	0	0	1;
	23	22	0	0.26	0	65	65	65	0	0	1;
	22	27	0	0.14	0	65	65	65	0	0	1;
	22	21	0.12	0.26	0	32	32	32	0	0	1;
	22	1	0.07	0.13	0	32	32	32	0	0	1;
	22	24	0.09	0.2	0	32	32	32	0	0	1;
	21	1	0.22	0.2	0	16	16	16	0	0	1;
%	24	17	0.08	0.19	0	16	16	16	0	0	1;
	1	3	0.11	0.22	0	16	16	16	0	0	1;
	3	7	0.06	0.13	0	16	16	16	0	0	1;
%	19	16	0.03	0.07	0	32	32	32	0	0	1;
	14	16	0.09	0.21	0	32	32	32	0	0	1;
	14	17	0.03	0.08	0	32	32	32	0	0	1;
	14	18	0.03	0.07	0	32	32	32	0	0	1;
	14	19	0.07	0.15	0	32	32	32	0	0	1;
	18	19	0.01	0.02	0	32	32	32	0	0	1;
	1	4	0.1	0.2	0	16	16	16	0	0	1;
%	19	8	0.12	0.18	0	16	16	16	0	0	1;
	4	8	0.13	0.27	0	16	16	16	0	0	1;
	8	9	0.19	0.33	0	16	16	16	0	0	1;
	9	10	0.25	0.38	0	16	16	16	0	0	1;
	9	11	0.11	0.21	0	16	16	16	0	0	1;
%	20	11	0	0.4	0	65	65	65	0	0	1;
	11	12	0.22	0.42	0	16	16	16	0	0	1;
	11	13	0.32	0.6	0	16	16	16	0	0	1;
	12	13	0.24	0.45	0	16	16	16	0	0	1;
	6	20	0.06	0.2	0.02	32	32	32	0	0	1;
	2	20	0.02	0.06	0.01	32	32	32	0	0	1;
];

%%-----  OPF Data  -----%%
%% area data
areas = [
	1	8;
	2	23;
	3	26;
];

%% generator cost data
%	1	startup	shutdown	n	x0	y0	...	xn	yn
%	2	startup	shutdown	n	c(n-1)	...	c0
gencost = [
	2	0	0	3	0.02	2	0;
	2	0	0	3	0.0175	1.75	0;
	2	0	0	3	0.0625	1	0;
	2	0	0	3	0.00834	3.25	0;
	2	0	0	3	0.025	3	0;
	2	0	0	3	0.025	3	0;
];

return;