Home > matpower6.0 > most > md_init.m

md_init

PURPOSE ^

MD_INIT MOST Data structure Initialization

SYNOPSIS ^

function md = md_init

DESCRIPTION ^

MD_INIT  MOST Data structure Initialization
   MD = MD_INIT

   Creates an empty MOST Data struct (MD) with all fields required for
   MOST, both input and output fields.

CROSS-REFERENCE INFORMATION ^

This function calls: This function is called by:

SOURCE CODE ^

0001 function md = md_init
0002 %MD_INIT  MOST Data structure Initialization
0003 %   MD = MD_INIT
0004 %
0005 %   Creates an empty MOST Data struct (MD) with all fields required for
0006 %   MOST, both input and output fields.
0007 
0008 %   MOST
0009 %   Copyright (c) 2010-2016, Power Systems Engineering Research Center (PSERC)
0010 %   by Carlos E. Murillo-Sanchez, PSERC Cornell & Universidad Nacional de Colombia
0011 %   and Ray Zimmerman, PSERC Cornell
0012 %
0013 %   This file is part of MOST.
0014 %   Covered by the 3-clause BSD License (see LICENSE file for details).
0015 %   See http://www.pserc.cornell.edu/matpower/ for more info.
0016 
0017 
0018 %%-----  start over  -----
0019 md = struct('Delta_T', 1);
0020 md.Storage.UnitIdx                    = [];
0021 md.UC.CommitKey                       = [];   % If empty, no UC dimension; else, must contain key to be used
0022 md.Storage.ExpectedTerminalStorageAim = [];   % expected terminal storage targe
0023 md.Storage.ExpectedTerminalStorageMin = [];   % expected terminal storage LB
0024 md.Storage.ExpectedTerminalStorageMax = [];   % expected terminal storage UB
0025 md.Storage.rho                        = [];   % (i,t), varies bounding of storage dispatches between being
0026                                               % based on worst case (rho=1) vs. expected (rho=0) stored energy
0027                                               % at beginning of period
0028 md.Storage.TerminalChargingPrice0     = [];   % applied to psc_tij0 (end-of-horizon terminal states)
0029 md.Storage.TerminalDischargingPrice0  = [];   % applied to psd_tij0 (end-of-horizon terminal states)
0030 md.Storage.TerminalChargingPriceK     = [];   % applied to psc_tijk (contingency terminal states)
0031 md.Storage.TerminalDischargingPriceK  = [];   % applied to psd_tijk (contingency terminal states)
0032 
0033 
0034 % %%-----  problem input data  -----
0035 % md = struct('OpenEnded', 1);  % default = no terminal dispatch ramping constraints
0036 % md.QCoordination  = 0;    % Create Qg variables for coordination if 1.
0037 % md.TerminalPg     = [];   % dispatch to ramp to from the final period
0038 % md.InitialPg      = [];   % dispatch to ramp from in the initial period
0039 %
0040 % % used only when most.storage.terminal_target option is 1
0041 % md.Storage.ExpectedTerminalStorageAim     = [];   % expected terminal storage targe
0042 % md.Storage.ExpectedTerminalStorageMin     = [];   % expected terminal storage LB
0043 % md.Storage.ExpectedTerminalStorageMax     = [];   % expected terminal storage UB
0044 %
0045 % md.mpc.baseMVA    = [];
0046 % md.mpc.bus        = [];
0047 % md.mpc.gen        = [];
0048 % md.mpc.branch     = [];
0049 % md.mpc.gencost    = [];
0050 % %md.offer(1).gencost                           = []; (deprecated)
0051 % md.offer(1).PositiveActiveReservePrice        = [];   % (t)
0052 % md.offer(1).PositiveActiveReserveQuantity     = [];
0053 % md.offer(1).NegativeActiveReservePrice        = [];
0054 % md.offer(1).NegativeActiveReserveQuantity     = [];
0055 % md.offer(1).PositiveActiveDeltaPrice          = [];
0056 % md.offer(1).NegativeActiveDeltaPrice          = [];
0057 % %md.offer(1).PositiveReactiveReservePrice      = [];
0058 % %md.offer(1).PositiveReactiveReserveQuantity   = [];
0059 % %md.offer(1).NegativeReactiveReservePrice      = [];
0060 % %md.offer(1).NegativeReactiveReserveQuantity   = [];
0061 % %md.offer(1).PositiveReactiveDeltaPrice        = [];
0062 % %md.offer(1).NegativeReactiveDeltaPrice        = [];
0063 % md.offer(1).PositiveLoadFollowReservePrice    = [];
0064 % md.offer(1).PositiveLoadFollowReserveQuantity = [];
0065 % md.offer(1).NegativeLoadFollowReservePrice    = [];
0066 % md.offer(1).NegativeLoadFollowReserveQuantity = [];
0067 % md.RampWearCostCoeff = [];    % (i,t) note different scheme!
0068 %                                 % the first column is the cost from initial
0069 %                                 % state to t=1; if there's a terminal
0070 %                                 % state, then there must be nt+1 columns
0071 % md.UC.CommitSched                     = [];   % if UC: solution on output; if not UC (mdi.CommitKey empty) then
0072 %                                                 % must contain UC status
0073 %                                                 % (i, t)
0074 % md.UC.CommitKey                       = [];   % If empty, no UC dimension; else, must contain key to be used
0075 %                                                 % for UC problem as follows:
0076 %                                                 % Must run        : 2
0077 %                                                 % Available for UC: 0, 1
0078 %                                                 % Offline:        : -1
0079 %                                                 % (i, t)
0080 % md.UC.InitialState                    = [];   % If positive, number of uptime periods;
0081 %                                                 % if negative, number of downtime periods at t = 0
0082 %                                                 % (ng)
0083 % md.UC.MinUp                           = [];   % Minimum uptime (i)
0084 % md.UC.MinDown                         = [];   % Minimum downtime (i)
0085 % md.UC.CyclicCommitment                = [];   % 1 if Commit restrictions roll over
0086 % md.UC.c00                             = [];   % (i,t)
0087 % md.Delta_T                            = 1;    % length of each period in hours
0088 % md.Storage.UnitIdx                    = [];
0089 % md.Storage.MinStorageLevel            = [];   % (i,t) These are applied to the
0090 % md.Storage.MaxStorageLevel            = [];   % (i,t) bounds.
0091 % md.Storage.InitialStorage             = [];
0092 % md.Storage.InitialStorageLowerBound   = [];   % initial s- value, or (if ForceCyclicStorage) lower bound on s0
0093 % md.Storage.InitialStorageUpperBound   = [];   % initial s+ value, or (if ForceCyclicStorage) upper bound on s0
0094 % md.Storage.OutEff                     = [];   % (i,t), output efficency (if empty defaults to 1)
0095 % md.Storage.InEff                      = [];   % (i,t), output efficency (if empty defaults to 1)
0096 % md.Storage.InitialStorageCost         = [];   % this is the cost of s0 (not adjusted for output efficiency)
0097 % md.Storage.TerminalStoragePrice       = [];   % applied to psc_tij0, psd_tij0 (non-terminal states)
0098 % md.Storage.TerminalChargingPrice0     = [];   % applied to psc_tij0 (end-of-horizon terminal states)
0099 % md.Storage.TerminalDischargingPrice0  = [];   % applied to psd_tij0 (end-of-horizon terminal states)
0100 % md.Storage.TerminalChargingPriceK     = [];   % applied to psc_tijk (contingency terminal states)
0101 % md.Storage.TerminalDischargingPriceK  = [];   % applied to psd_tijk (contingency terminal states)
0102 % md.Storage.LossFactor                 = [];   % (i,t), fraction of storage lost per hour
0103 %                                                 % if empty, defaults to lossless (all zeros)
0104 % md.Storage.rho                        = [];   % (i,t), varies bounding of storage dispatches between being
0105 %                                                 % based on worst case (rho=1) vs. expected (rho=0) stored energy
0106 %                                                 % at beginning of period
0107 % % Note: MinStorageLevel, MaxStorageLevel, InEff, OutEff, LossFactor and rho
0108 % %       are optionally expanded automatically in most() from scalar,
0109 % %       ns x 1, or 1 x nt to ns x nt matrix.
0110 %
0111 % md.idx.nt                             = [];
0112 % md.cont(1,1).contab                   = [];
0113 % md.tstep(1).OpCondSched(1).tab        = [];
0114 % md.tstep(1).TransMat = [];    % tstep(t).TransMat(j(t), j(t-1)).
0115 %                                 % Note that for cyclic or terminal state
0116 %                                 % problems, data for t=nt+1 is needed for
0117 %                                 % this matrix!
0118 % md.tstep(1).TransMask = [];   % Same format as TransMat, mask indicating
0119 %                                 % whether to include transition in ramp reserve.
0120 % md.tstep(1).Li = sparse(0,0); % These 8 for computing expected storage states
0121 % md.tstep(1).Lf = sparse(0,0);
0122 % md.tstep(1).Mg = sparse(0,0);
0123 % md.tstep(1).Mh = sparse(0,0);
0124 % md.tstep(1).Ng = sparse(0,0);
0125 % md.tstep(1).Nh = sparse(0,0);
0126 % md.tstep(1).G  = sparse(0,0);
0127 % md.tstep(1).H  = sparse(0,0);
0128 % md.tstep(1).E  = sparse(0,0); % To compute expected injections in t-th period
0129 %
0130 % md.dstep(1).A = sparse(0,0);
0131 % md.dstep(1).B = sparse(0,0);
0132 % md.dstep(1).C = sparse(0,0);
0133 % md.dstep(1).D = sparse(0,0);
0134 % md.dstep(1).zmax = [];
0135 % md.dstep(1).zmin = [];
0136 % md.dstep(1).ymax = [];
0137 % md.dstep(1).ymin = [];
0138 % md.idx.ntds = []; % Number of periods in the dynamical system horizon
0139 % md.z1 = [];       % Initial state (t=1)
0140 %
0141 % %%-----  internally created data:  -----
0142 % %% (1) Indexing mechanism
0143 % md.idx.nj         = [];
0144 % md.idx.nc         = [];
0145 % md.idx.nb         = [];
0146 % md.idx.nb_total   = [];
0147 % md.idx.ng         = [];
0148 % md.idx.nf_total   = [];
0149 % md.idx.ns         = [];
0150 % md.idx.ns_total   = [];
0151 % md.idx.nzds       = [];       % size of state vector for dynamical system
0152 % md.idx.nyds       = [];
0153 % md.idx.ntramp     = [];       % number of periods of load following reserves
0154 % % md.idx.thbas      = [];
0155 % % md.idx.thend      = [];
0156 % % md.idx.pbas       = [];
0157 % % md.idx.pend       = [];       % (t,j,k)
0158 % % md.idx.dppbas     = [];       % (t,j,k)
0159 % % md.idx.dppend     = [];       % (t,j,k)
0160 % % md.idx.dpmbas     = [];       % (t,j,k)
0161 % % md.idx.dpmend     = [];       % (t,j,k)
0162 % % md.idx.ybas       = [];       % (t,j,k)
0163 % % md.idx.yend       = [];       % (t,j,k)
0164 % % md.idx.pcbas      = [];       % (t)
0165 % % md.idx.pcend      = [];       % (t)
0166 % % md.idx.rppbas     = [];       % (t)
0167 % % md.idx.rppend     = [];       % (t)
0168 % % md.idx.rpmbas     = [];       % (t)
0169 % % md.idx.rpmend     = [];       % (t)
0170 % % md.idx.pscbas     = [];       % (t,j,k)
0171 % % md.idx.pscend     = [];       % (t,j,k)
0172 % % md.idx.psdbas     = [];       % (t,j,k)
0173 % % md.idx.psdend     = [];       % (t,j,k)
0174 % % md.idx.rrpbas     = [];       % (t)
0175 % % md.idx.rrpend     = [];       % (t)
0176 % % md.idx.rrmbas     = [];       % (t)
0177 % % md.idx.rrmend     = [];       % (t)
0178 % % md.idx.spbas      = [];       % (t)
0179 % % md.idx.spend      = [];       % (t)
0180 % % md.idx.smbas      = [];       % (t)
0181 % % md.idx.smend      = [];       % (t)
0182 % % md.idx.s0bas      = [];       % (1:ns)
0183 % % md.idx.s0end      = [];       % (i:ns)
0184 % % md.idx.ubas       = [];       % (t)
0185 % % md.idx.uend       = [];       % (t)
0186 % % md.idx.wbas       = [];       % (t)
0187 % % md.idx.wend       = [];       % (t)
0188 % % md.idx.vbas       = [];       % (t)
0189 % % md.idx.vend       = [];       % (t)
0190 % % md.idx.qbas       = [];       % (t)
0191 % % md.idx.qend       = [];       % (t)
0192 % % md.idx.netbas     = [];       % (t,j,k)
0193 % % md.idx.netend     = [];       % (t,j,k)
0194 % % md.idx.lfbas      = [];       % (t,j,k)
0195 % % md.idx.lfend      = [];       % (t,j,k)
0196 % % md.idx.lstibas    = [];       % (t,j,k)
0197 % % md.idx.lstiend    = [];       % (t,j,k)
0198 % % md.idx.Aybas      = [];       % (t,j)
0199 % % md.idx.Ayend      = [];       % (t,j)
0200 % % md.idx.lc1bas     = [];       % (t)
0201 % % md.idx.lc1end     = [];       % (t)
0202 % % md.idx.lc2bas     = [];       % (t)
0203 % % md.idx.lc2end     = [];       % (t)
0204 % % md.idx.lc3bas     = [];       % (t,j,k)
0205 % % md.idx.lc3end     = [];       % (t,j,k)
0206 % % md.idx.lc5bas     = [];       % (t,j,k)
0207 % % md.idx.lc5end     = [];       % (t,j,k)
0208 % % md.idx.lc6bas     = [];       % (t,j,k)
0209 % % md.idx.lc6end     = [];       % (t,j,k)
0210 % % md.idx.lc7bas     = [];       % (t,j,k)
0211 % % md.idx.lc7end     = [];       % (t,j,k)
0212 % % md.idx.lc8bas     = [];       % (t,j,k)
0213 % % md.idx.lc8end     = [];       % (t,j,k)
0214 % % md.idx.lc9bas     = [];       % (t,j,k)
0215 % % md.idx.lc9end     = [];       % (t,j,k)
0216 % % md.idx.lc10bas    = [];       % (t,j,k)
0217 % % md.idx.lc10end    = [];       % (t,j,k)
0218 % % md.idx.lc21bas    = [];       % (t,jt,j(t+1))
0219 % % md.idx.lc21end    = [];       % (t,jt,j(t+1))
0220 % % md.idx.lc22bas    = [];       % (t)
0221 % % md.idx.lc22end    = [];       % (t)
0222 % % md.idx.lc23bas    = [];       % (t,jt,j(t+1))
0223 % % md.idx.lc23end    = [];       % (t,jt,j(t+1))
0224 % % md.idx.lc24bas    = [];       % (t)
0225 % % md.idx.lc24end    = [];       % (t)
0226 % % md.idx.lc31bas    = [];       % (t)
0227 % % md.idx.lc31end    = [];       % (t)
0228 % % md.idx.lc32bas    = [];       % (t)
0229 % % md.idx.lc32end    = [];       % (t)
0230 % % md.idx.lc33bas    = [];       % (t)
0231 % % md.idx.lc33end    = [];       % (t)
0232 % % md.idx.lc34bas    = [];       % (t,j)
0233 % % md.idx.lc34end    = [];       % (t,j)
0234 % % md.idx.lc35bas    = [];       % (t,j)
0235 % % md.idx.lc35end    = [];       % (t,j)
0236 % % md.idx.lc36bas    = [];       % (t,j)
0237 % % md.idx.lc36end    = [];       % (t,j)
0238 % % md.idx.lc37bas    = [];       % (t,j)
0239 % % md.idx.lc37end    = [];       % (t,j)
0240 % % md.idx.lc38bas    = [];       %
0241 % % md.idx.lc38end    = [];       %
0242 % % md.idx.lc40bas    = [];       % (t)
0243 % % md.idx.lc40end    = [];       % (t)
0244 % % md.idx.lc41bas    = [];       % (t)
0245 % % md.idx.lc41end    = [];       % (t)
0246 % % md.idx.lc50bas    = [];       % (t)
0247 % % md.idx.lc50end    = [];       % (t)
0248 % % md.idx.lc51bas    = [];       % (i,t)
0249 % % md.idx.lc51end    = [];       % (i,t)
0250 % % md.idx.lc52bas    = [];       % (i,t)
0251 % % md.idx.lc52end    = [];       % (i,t)
0252 % % md.idx.lc53bas    = [];       % (t,j,k)
0253 % % md.idx.lc53end    = [];       % (t,j,k)
0254 % % md.idx.lc54bas    = [];       % (t,j,k)
0255 % % md.idx.lc54end    = [];       % (t,j,k)
0256 % % md.idx.lc55bas    = [];       % (t,j,k)
0257 % % md.idx.lc55end    = [];       % (t,j,k)
0258 % % md.idx.lc56bas    = [];       % (t,j,k)
0259 % % md.idx.lc56end    = [];       % (t,j,k)
0260 %
0261 % md.flow(1,1,1).mpc = md.mpc;
0262 % md.DCMODEL              = [];   % DC flow used to model the network as opposed
0263 %                                 % to simple generation = demand constraint
0264 %                                 % (set via mpopt.most.dc_line)
0265 % md.SecurityConstrained  = [];   % contingencies cases considered
0266 %                                 % (set via mpopt.most.security_constraints and
0267 %                                 %  presence (or not) of contingency data)
0268 % md.Storage.ForceExpectedTerminalStorage   = [];     % flag, 0 or 1, terminal storage target included
0269 % md.Storage.ForceCyclicStorage             = [];     % 1 = includes cyclic constraint (initial storage
0270 %                                                     % is a var = final expected storage), 0 = does not include
0271 % md.UC.run               = [];   % 1 = run the unit commitment, 0 = don't
0272 % md.alpha                = [];   % defines when during period contingencies happen
0273 %
0274 % %% (2) QP problem
0275 % md.QP.A       = sparse(0,0);
0276 % md.QP.l       = [];
0277 % md.QP.u       = [];
0278 % md.QP.xmin    = [];
0279 % md.QP.xmax    = [];
0280 % md.QP.vtype   = '';
0281 % md.QP.H       = sparse(0,0);
0282 % md.QP.C1      = [];
0283 % md.QP.c1      = [];
0284 % md.QP.C       = [];
0285 % md.QP.Cfstor  = [];
0286 % md.CoordCost.Huser    = sparse(0,0);
0287 % md.CoordCost.Cuser    = [];
0288 % md.CoordCost.cuser    = [];
0289 % md.QP.x           = [];
0290 % md.QP.f           = [];
0291 % md.QP.exitflag    = [];
0292 % md.QP.output      = [];
0293 % md.QP.lambda      = [];
0294 % md.QP.opt         = [];
0295 %
0296 % %%-----  result data  -----
0297 % md.results.f      = [];
0298 % md.results.Pc     = [];
0299 % md.results.Rpp    = [];
0300 % md.results.Rpm    = [];
0301 % md.results.Rrp    = [];
0302 % md.results.Rrm    = [];
0303 % md.results.Sp     = [];
0304 % md.results.Sm     = [];
0305 % md.results.GenPrices          = [];
0306 % md.results.CondGenPrices      = [];
0307 % md.results.RrpPrices          = [];
0308 % md.results.RrmPrices          = [];
0309 % md.results.ExpectedRampCost   = [];
0310 % md.results.SetupTime          = [];
0311 % md.results.SolveTime          = [];
0312 % md.results.Z                  = [];
0313 % md.results.Y                  = [];
0314 %
0315 % md.CostWeights    = [];   % (k,j,t) !!!! NOTE order! So that (:,:,t)
0316 %                             % refers to t-th period
0317 % md.CostWeightsAdj = [];   % (k,j,t) !!!! NOTE order! So that (:,:,t)
0318 %                             % refers to t-th period
0319 % md.StepProb       = [];   % (t)  - probability of making it to the t-th step
0320 % md.Storage.ExpectedStorageState       = [];
0321 % md.Storage.ExpectedStorageDispatch    = [];

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