Description of t_most_30b_1_1

0001 function t_most_30b_1_1_17(quiet)
0002 %T_MOST_30B_1_1_17  Tests for MOST.
0003 
0004 %   MOST
0005 %   Copyright (c) 2009-2020, Power Systems Engineering Research Center (PSERC)
0006 %   by Ray Zimmerman, PSERC Cornell
0007 %
0008 %   This file is part of MOST.
0009 %   Covered by the 3-clause BSD License (see LICENSE file for details).
0010 %   See https://github.com/MATPOWER/most for more info.
0011 
0012 if nargin < 1
0013     quiet = 0;
0014 end
0015 
0016 n_tests = 34;
0017 
0018 t_begin(n_tests, quiet);
0019 
0020 casename = 't_case30_most';
0021 fudging = struct( ...       %% paramters for fudging reserve contract for sopf2
0022     'fudge',    0.05, ...   %% initial value (MW)
0023     'step',     0.01, ...   %% if necessary, increase by this amount and retry (MW)
0024     'lim',      0.1);       %% upper limit (MW), give up if no convergence
0025                             %% with fudge equal to this limit
0026 
0027 %% options
0028 algs.dc     = {'DEFAULT'};  %% opf.dc.solver sequence to try for c3sopf (DC run)
0029 algs.ac     = {'DEFAULT'};  %% opf.ac.solver sequence to try for c3sopf (AC run)
0030 mpopt = mpoption('verbose', 0, 'out.all', 0);
0031 mpopt = mpoption(mpopt, 'opf.violation', 5e-7, 'mips.comptol', 5e-8);
0032 mpopt = mpoption(mpopt, 'sopf.force_Pc_eq_P0', 0);  %% don't constrain contracted == base case dispatch
0033 if have_feature('linprog')
0034     if have_feature('linprog_ds')
0035         mpopt = mpoption(mpopt, 'linprog.Algorithm', 'dual-simplex');
0036     else
0037         mpopt = mpoption(mpopt, 'linprog.Algorithm', 'simplex');
0038     end
0039 end
0040 mpoptac = mpoption(mpopt, 'model', 'AC');
0041 mpoptdc = mpoption(mpopt, 'model', 'DC');
0042 mpopt = mpoption(mpopt, 'most.solver', algs.dc{1});
0043 
0044 %% turn off warnings
0045 s7 = warning('query', 'MATLAB:nearlySingularMatrix');
0046 s6 = warning('query', 'MATLAB:nearlySingularMatrixUMFPACK');
0047 warning('off', 'MATLAB:nearlySingularMatrix');
0048 warning('off', 'MATLAB:nearlySingularMatrixUMFPACK');
0049 
0050 %% define named indices into data matrices
0051 [GEN_BUS, PG, QG, QMAX, QMIN, VG, MBASE, GEN_STATUS, PMAX, PMIN, ...
0052     MU_PMAX, MU_PMIN, MU_QMAX, MU_QMIN, PC1, PC2, QC1MIN, QC1MAX, ...
0053     QC2MIN, QC2MAX, RAMP_AGC, RAMP_10, RAMP_30, RAMP_Q, APF] = idx_gen;
0054 [F_BUS, T_BUS, BR_R, BR_X, BR_B, RATE_A, RATE_B, RATE_C, ...
0055     TAP, SHIFT, BR_STATUS, PF, QF, PT, QT, MU_SF, MU_ST, ...
0056     ANGMIN, ANGMAX, MU_ANGMIN, MU_ANGMAX] = idx_brch;
0057 [CT_LABEL, CT_PROB, CT_TABLE, CT_TBUS, CT_TGEN, CT_TBRCH, CT_TAREABUS, ...
0058     CT_TAREAGEN, CT_TAREABRCH, CT_ROW, CT_COL, CT_CHGTYPE, CT_REP, ...
0059     CT_REL, CT_ADD, CT_NEWVAL, CT_TLOAD, CT_TAREALOAD, CT_LOAD_ALL_PQ, ...
0060     CT_LOAD_FIX_PQ, CT_LOAD_DIS_PQ, CT_LOAD_ALL_P, CT_LOAD_FIX_P, ...
0061     CT_LOAD_DIS_P, CT_TGENCOST, CT_TAREAGENCOST, CT_MODCOST_F, ...
0062     CT_MODCOST_X] = idx_ct;
0063 
0064 %% reserve and delta offers
0065 xgd_table.colnames = {
0066     'PositiveActiveReservePrice', ...
0067             'PositiveActiveReserveQuantity', ...
0068                     'NegativeActiveReservePrice', ...
0069                             'NegativeActiveReserveQuantity', ...
0070                                     'PositiveActiveDeltaPrice', ...
0071                                             'NegativeActiveDeltaPrice', ...
0072 };
0073 xgd_table.data = [
0074     10.1    15      10.0    15      0.1     0.0;
0075     10.3    30      10.2    30      0.3     0.2;  
0076     10.5    20      10.4    20      0.5     0.4;  
0077     10.7    25      10.6    25      0.7     0.6;
0078     20.1    25      20.0    25      60.1    60.0; 
0079     20.3    15      20.2    15      15.1    15.0;
0080     20.5    30      20.4    30      60.3    60.2;
0081     20.7    15      20.6    15      15.3    15.2;
0082     30.1    15      30.0    15      60.3    60.4;
0083     30.3    30      30.2    30      30.1    30.0;
0084     30.5    25      30.4    25      60.7    60.6;
0085     30.7    30      30.6    30      30.3    30.2;
0086     0.001   50      0.002   50      0       0;
0087     0.001   50      0.002   50      0       0;
0088     0.001   50      0.002   50      0       0;
0089     0.001   50      0.002   50      0       0;
0090     0.001   50      0.002   50      0       0;
0091     0.001   50      0.002   50      0       0;
0092     0.001   50      0.002   50      0       0;
0093     0.001   50      0.002   50      0       0;
0094     0.001   50      0.002   50      0       0;
0095     0.001   50      0.002   50      0       0;
0096     0.001   50      0.002   50      0       0;
0097     0.001   50      0.002   50      0       0;
0098     0.001   50      0.002   50      0       0;
0099     0.001   50      0.002   50      0       0;
0100     0.001   50      0.002   50      0       0;
0101     0.001   50      0.002   50      0       0;
0102     0.001   50      0.002   50      0       0;
0103     0.001   50      0.002   50      0       0;
0104     0.001   50      0.002   50      0       0;
0105     0.001   50      0.002   50      0       0;
0106 ];
0107 
0108 %% contingency table
0109 % label probty  type        row column      chgtype newvalue
0110 contab = [
0111     1   0.002   CT_TBRCH    1   BR_STATUS   CT_REP  0;      %% line 1-2
0112     2   0.002   CT_TBRCH    2   BR_STATUS   CT_REP  0;      %% line 1-3, all power from gen1 flows via gen2
0113     3   0.002   CT_TBRCH    3   BR_STATUS   CT_REP  0;      %% line 2-4, a path to loads @ buses 7 & 8
0114     4   0.002   CT_TBRCH    5   BR_STATUS   CT_REP  0;      %% line 2-5, a path to loads @ buses 7 & 8
0115     5   0.002   CT_TBRCH    6   BR_STATUS   CT_REP  0;      %% line 2-6, a path to loads @ buses 7 & 8
0116     6   0.002   CT_TBRCH    36  BR_STATUS   CT_REP  0;      %% line 28-27, tie line between areas 1 & 3
0117     7   0.002   CT_TBRCH    15  BR_STATUS   CT_REP  0;      %% line 4-12, tie line between areas 1 & 2
0118     8   0.002   CT_TBRCH    12  BR_STATUS   CT_REP  0;      %% line 6-10, tie line between areas 1 & 3
0119     9   0.002   CT_TBRCH    14  BR_STATUS   CT_REP  0;      %% line 9-10, tie line between areas 1 & 3
0120     10  0.002   CT_TGEN     1   GEN_STATUS  CT_REP  0;      %% gen 1 at bus 1
0121     11  0.002   CT_TGEN     2   GEN_STATUS  CT_REP  0;      %% gen 2 at bus 2
0122     12  0.002   CT_TGEN     3   GEN_STATUS  CT_REP  0;      %% gen 3 at bus 22
0123     13  0.002   CT_TGEN     4   GEN_STATUS  CT_REP  0;      %% gen 4 at bus 27
0124     14  0.002   CT_TGEN     5   GEN_STATUS  CT_REP  0;      %% gen 5 at bus 23
0125     15  0.002   CT_TGEN     6   GEN_STATUS  CT_REP  0;      %% gen 6 at bus 13
0126     20  0.010   CT_TGEN     0   PMIN        CT_REL  1.1;    %% 10% load increase
0127     20  0.010   CT_TGEN     0   QMIN        CT_REL  1.1;
0128     21  0.010   CT_TGEN     0   PMIN        CT_REL  0.9;    %% 10% load decrease
0129     21  0.010   CT_TGEN     0   QMIN        CT_REL  0.9;
0130 ];
0131 clist = unique(contab(:, CT_LABEL));
0132 nc = length(clist);
0133 
0134 %% load the case
0135 mpc = loadcase(casename);
0136 gbus = mpc.gen(:, GEN_BUS);
0137 
0138 %%-----  get c3sopf results  -----
0139 rdc = c3sopf_retry(algs.dc, mpc, xgd_table.data, contab, mpoptdc);
0140 % rac = c3sopf_retry(algs.ac, mpc, xgd_table.data, contab, mpoptac);
0141 % save t_most2_soln rdc rac -v6
0142 % s = load('t_most2_soln');
0143 s.rdc = rdc;
0144 % s.rac = rac;
0145 
0146 %%-----  set up data for DC run (most)  -----
0147 ng = size(mpc.gen, 1);      %% number of gens
0148 xgd = loadxgendata(xgd_table, mpc);
0149 md = loadmd(mpc, [], xgd, [], contab);
0150 
0151 %%-----  do DC run (most)  -----
0152 r = most(md, mpopt);
0153 
0154 %%-----  test the results  -----
0155 t = 'success1';
0156 t_ok(s.rdc.opf_results.success, t);
0157 t = 'success2';
0158 t_ok(r.QP.exitflag, t);
0159 
0160 t = 'f';
0161 t_is(r.results.f, s.rdc.opf_results.f, 4, t);
0162 
0163 t = 'Pg : base';
0164 t_is(r.flow(1,1,1).mpc.gen(:, PG), s.rdc.base.gen(:, PG), 5, t);
0165 t = 'Pg : cont ';
0166 for k = 1:nc
0167     t_is(r.flow(1,1,k+1).mpc.gen(:, PG), s.rdc.cont(k).gen(:, PG), 5, sprintf('%s %d', t, k));
0168 end
0169 
0170 % t = 'gen : base';
0171 % t_is(r.flow(1,1,1).mpc.gen(:,1:MU_PMIN), s.rdc.base.gen(:,1:MU_PMIN), 3, t);
0172 % t = 'gen : cont ';
0173 % for k = 1:nc
0174 %     t_is(r.flow(1,1,k+1).mpc.gen(:,1:MU_PMIN), s.rdc.cont(k).gen(:,1:MU_PMIN), 3, sprintf('%s %d', t, k));
0175 % end
0176 
0177 t = 'energy prices';
0178 t_is(r.results.GenPrices, s.rdc.energy.prc.sum_bus_lam_p(gbus), 6, t);
0179 
0180 t = 'Pc';
0181 t_is(r.results.Pc, s.rdc.energy.Pc, 4, t);
0182 
0183 t = 'Gmin';
0184 t_is(r.results.Pc - r.results.Rpm, s.rdc.energy.Gmin, 4, t);
0185 
0186 t = 'Gmax';
0187 t_is(r.results.Pc + r.results.Rpp, s.rdc.energy.Gmax, 4, t);
0188 
0189 t = 'upward contingency reserve quantities';
0190 t_is(r.results.Rpp, s.rdc.reserve.qty.Rp_pos, 4, t);
0191 
0192 t = 'downward contingency reserve quantities';
0193 t_is(r.results.Rpm, s.rdc.reserve.qty.Rp_neg, 4, t);
0194 
0195 t = 'upward contingency reserve prices';
0196 t_is(r.results.RppPrices, s.rdc.reserve.prc.Rp_pos, 6, t);
0197 
0198 t = 'downward contingency reserve prices';
0199 t_is(r.results.RpmPrices, s.rdc.reserve.prc.Rp_neg, 6, t);
0200 
0201 t = 'contingency physical ramp price';
0202 [vv, ll] = r.om.get_idx();
0203 Ramp_P_max = zeros(ng, nc);
0204 sum_muPmax = zeros(ng, 1);
0205 sum_muPmin = zeros(ng, 1);
0206 for k = 1:nc+1
0207     ii = find(r.flow(1,1,k).mpc.gen(:, GEN_STATUS) > 0);
0208     if k > 1
0209         Ramp_P_max(ii,k-1) = (r.QP.lambda.mu_u(ll.i1.rampcont(1,1,k):ll.iN.rampcont(1,1,k)) - r.QP.lambda.mu_l(ll.i1.rampcont(1,1,k):ll.iN.rampcont(1,1,k))) / mpc.baseMVA;
0210     end
0211     sum_muPmax(ii) = sum_muPmax(ii) + r.flow(1,1,k).mpc.gen(ii, MU_PMAX);
0212     sum_muPmin(ii) = sum_muPmin(ii) + r.flow(1,1,k).mpc.gen(ii, MU_PMIN);
0213 end
0214 t_is(Ramp_P_max, s.rdc.energy.mu.Ramp_P_max, 2, t);
0215 
0216 t = 'sum_muPmax';
0217 t_is(sum_muPmax, s.rdc.energy.sum_muPmax, 1, t);
0218 
0219 t = 'sum_muPmin';
0220 t_is(sum_muPmin, s.rdc.energy.sum_muPmin, 0.9, t);
0221 
0222 t = 'Rpmax_pos';
0223 Rpmax_pos = (r.QP.lambda.upper(vv.i1.Rpp(1):vv.iN.Rpp(1)) - r.QP.lambda.lower(vv.i1.Rpp(1):vv.iN.Rpp(1))) / mpc.baseMVA;
0224 t_is(Rpmax_pos, s.rdc.reserve.mu.Rpmax_pos, 6, t);
0225 
0226 t = 'Rpmax_neg';
0227 Rpmax_neg = (r.QP.lambda.upper(vv.i1.Rpm(1):vv.iN.Rpm(1)) - r.QP.lambda.lower(vv.i1.Rpm(1):vv.iN.Rpm(1))) / mpc.baseMVA;
0228 t_is(Rpmax_neg, s.rdc.reserve.mu.Rpmax_neg, 6, t);
0229 
0230 
0231 
0232 % g1 = s.rdc.base.gen(:, PG);
0233 % g2 = r.flow(1,1,1).mpc.gen(:, PG);
0234 % for k = 1:nc
0235 %     g1 = [ g1 s.rdc.cont(k).gen(:, PG) ];
0236 %     g2 = [ g2 r.flow(1,1,k+1).mpc.gen(:, PG) ];
0237 % end
0238 % [m,n] = size(g1);
0239 % for j = 1:n
0240 %     fprintf('\n');
0241 %     for i = 1:m
0242 %         fprintf('%9.2f  %9.2f\n', g1(i,j), g2(i,j));
0243 %     end
0244 % end
0245 
0246 %%-----  do AC run (most)  -----
0247 %mostac;
0248 
0249 
0250 %% turn warnings back on
0251 warning(s7.state, 'MATLAB:nearlySingularMatrix');
0252 warning(s6.state, 'MATLAB:nearlySingularMatrixUMFPACK');
0253 
0254 t_end;
t_most_30b_1_1_17

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