opf.m

比较经典的matlab的电力系统潮流计算程序

function [bus, gen, branch, f, success, et] = opf(baseMVA, bus, gen, gencost, ...
					branch, Ybus, Yf, Yt, ref, pv, pq, mpopt)
%OPF  Solves an optimal power flow.
%   [bus, gen, branch, f, success, et] = opf(baseMVA, bus, gen, gencost, ...
%                   branch, Ybus, Yf, Yt, ref, pv, pq, mpopt)
%   Assumes that Ybus, Yf, Yt, V, ref, pv, pq are consistent with
%   (or override) data in bus, gen, branch.

%   MATPOWER Version 2.0
%   by Ray Zimmerman & David Gan, PSERC Cornell    12/24/97
%   Copyright (c) 1996, 1997 by Power System Engineering Research Center (PSERC)
%   See http://www.pserc.cornell.edu/ for more info.

%%----- initialization -----
%% default arguments
if nargin < 12
	mpopt = mpoption;		%% use default options
end

%% options
verbose	= mpopt(31);
npts = mpopt(14);		%% number of points to evaluate when converting
						%% polynomials to piece-wise linear

%% define constants
j = sqrt(-1);

%% define named indices into data matrices
[PQ, PV, REF, NONE, BUS_I, BUS_TYPE, PD, QD, GS, BS, BUS_AREA, VM, ...
	VA, BASE_KV, ZONE, VMAX, VMIN, LAM_P, LAM_Q, MU_VMAX, MU_VMIN] = idx_bus;
[GEN_BUS, PG, QG, QMAX, QMIN, VG, MBASE, ...
	GEN_STATUS, PMAX, PMIN, MU_PMAX, MU_PMIN, MU_QMAX, MU_QMIN] = idx_gen;
[PW_LINEAR, POLYNOMIAL, MODEL, STARTUP, SHUTDOWN, N, COST] = idx_cost;

%%-----  check/convert costs, set default algorithm  -----
%% get cost model, check consistency
model = gencost(:, MODEL);
i_pwln = find(model == PW_LINEAR);
i_poly = find(model == POLYNOMIAL);
if any(i_pwln) & any(i_poly) & verbose
	fprintf('not all generators use same cost model, all will be converted to piece-wise linear\n');
end

%% set algorithm
if mpopt(11) == 0
	%% use default for this cost model
	if find(model ~= PW_LINEAR & model ~= POLYNOMIAL)
		error('unknown generator cost model');
	elseif any(i_pwln)		%% some piece-wise linear, use appropriate alg
		mpopt(11) = mpopt(13);
	else					%% must all be polynomial
		mpopt(11) = mpopt(12);
	end
end
alg = mpopt(11);
formulation = opf_form(alg);

%% move Pmin and Pmax limits out slightly to avoid problems
%% caused by rounding errors when corner point of cost
%% function lies at exactly Pmin or Pmax
if any(i_pwln)
	ng = size(gen, 1);
	gen(:, PMIN) = gen(:, PMIN) - 1e-6 * ones(ng, 1);
	gen(:, PMAX) = gen(:, PMAX) + 1e-6 * ones(ng, 1);
end

%% check cost model/algorithm consistency
if any( i_pwln ) & formulation == 1
	error(sprintf('algorithm %d does not handle piece-wise linear cost functions', alg));
	%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
	%%	Eventually put code here to fit polynomials to piece-wise linear as needed.
	%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
end
%% convert polynomials to piece-wise linear
if any(i_poly)  & formulation == 2
	if verbose
		fprintf('converting from polynomial to piece-wise linear cost model\n');
	end
	[pcost, qcost] = pqcost(gencost, size(gen, 1));
	i_poly = find(pcost(:, MODEL) == POLYNOMIAL);
	pcost = poly2pwl(pcost(i_poly, :), gen(i_poly, PMIN), gen(i_poly, PMAX), npts);
	if ~isempty(qcost)
		i_poly = find(qcost(:, MODEL) == POLYNOMIAL);
		qcost = poly2pwl(qcost(i_poly, :), gen(i_poly, QMIN), gen(i_poly, QMAX), npts);
	end
	gencost = [pcost; qcost];
end

%%-----  run opf  -----
%% start timer
t0 = clock;

%% sizes of things
nb = size(bus, 1);
nl = size(branch, 1);
npv	= length(pv);
npq	= length(pq);
ng = npv + 1;			%% number of generators that are turned on

%% initial state
on = find(gen(:, GEN_STATUS));				%% which generators are on?
V	= bus(:, VM) .* exp(sqrt(-1) * pi/180 * bus(:, VA));
V(gen(on, GEN_BUS)) = gen(on, VG) ./ abs(V(gen(on, GEN_BUS))).* V(gen(on, GEN_BUS));
Pg	= gen(on, PG) / baseMVA;
Qg	= gen(on, QG) / baseMVA;

%% check for costs for Qg
[pcost, qcost] = pqcost(gencost, size(gen, 1), on);

%% set up indexing for x
j1 = 1;			j2	= npv;				%% j1:j2	- V angle of pv buses
j3 = j2 + 1;	j4	= j2 + npq;			%% j3:j4	- V angle of pq buses
j5 = j4 + 1;	j6	= j4 + nb;			%% j5:j6	- V mag of all buses
j7 = j6 + 1;	j8	= j6 + npv + 1;		%% j7:j8	- P of generators
j9 = j8 + 1;	j10	= j8 + npv + 1;		%% j9:j10	- Q of generators
% j11 = j10 + 1;	j12	= j10 + npv + 1;	%% j11:j12	- Cp, cost of Pg
% j13 = j12 + 1;	j14	= j12 + npv + 1;	%% j13:j14	- Cq, cost of Qg

%% set up x
if formulation == 1
	Cp = [];
	Cq = [];
else
	Cp = totcost(pcost, Pg * baseMVA);
	Cq = totcost(qcost, Qg * baseMVA);	%% empty if qcost is empty
end
x = [angle(V([pv; pq])); abs(V); Pg; Qg; Cp; Cq];

%% run constrained optimization
[fun, grad]	= fg_names(alg);
mpopt(15)	= 2 * nb;				%% set number of equality constraints

if opf_slvr(alg) == 0			%% use CONSTR
	%% set some options
	if mpopt(19) == 0
		mpopt(19) = 2 * nb + 150;	%% set max number of iterations for constr
	end

	%% set up options for Optim Tbx's constr
	otopt = foptions;				%% get default options for constr
	otopt(1) = (verbose > 0);		%% set verbose flag appropriately
	% otopt(9) = 1;					%% check user supplied gradients?
	otopt(13) = mpopt(15);			%% number of equality constraints
	otopt(14) = mpopt(19);			%% maximum number of iterations
	
	%% run optimization
	[x, otopt, lambda] = constr(fun, x, otopt, [], [], grad, ...
						baseMVA, bus, gen, gencost, branch, Ybus, Yf, Yt, V, ref, pv, pq, mpopt);
	
	%% get final objective function value & constraint values
	[f, g] = feval(fun, x, baseMVA, bus, gen, gencost, branch, Ybus, Yf, Yt, V, ref, pv, pq, mpopt);
	
	%% check for convergence
	if otopt(10) >= otopt(14)	| max(abs(g(1:otopt(13))))			> otopt(4) ...
								| max(g((otopt(13)+1):length(g)))	> otopt(4)
		success = 0;				%% did NOT converge
	else
		success = 1;				%% DID converge
	end
else							%% use LPCONSTR
	%% run load flow to get starting point
	[x, success_lf] = LPeqslvr(x, baseMVA, bus, gen, gencost, branch, Ybus, Yf, Yt, V, ref, pv, pq, mpopt);
	if success_lf ~= 1
		error('Sorry, cannot find a starting point using power flow, please check data!'); 
	end
	
	%% set step size
	cstep = 0;
	if ~isempty(Cp)
		cstep = max(abs(Cp));
		if cstep < 1.0e6, cstep = 1.0e6; end
	end
	step0=[2*ones(nb-1,1);					%% starting stepsize for Vangle
			ones(nb,1);						%% Vmag
			0.6*ones(ng,1);					%% Pg
			0.3*ones(ng,1);					%% Qg
			cstep*ones(length(Cp),1);		%% Cp
			cstep*ones(length(Cq),1)];		%% Cq
	idx_xi = [];

	%% run optimization
	[x, lambda, success] = LPconstr(fun, x, idx_xi, mpopt, step0, [], [], grad, 'LPeqslvr', ...
						baseMVA, bus, gen, gencost, branch, Ybus, Yf, Yt, V, ref, pv, pq, mpopt);

	%% get final objective function value & constraint values
	f = feval(fun, x, baseMVA, bus, gen, gencost, branch, Ybus, Yf, Yt, V, ref, pv, pq, mpopt);
end

%%-----  calculate return values  -----
%% reconstruct V
Va = zeros(nb, 1);
Va([ref; pv; pq]) = [angle(V(ref)); x(j1:j2); x(j3:j4)];
Vm = x(j5:j6);
V = Vm .* exp(j * Va);

%% grab Pg & Qg
Sg = x(j7:j8) + j * x(j9:j10);		%% complex power generation in p.u.

%% update bus, gen, branch with solution info
[bus, gen, branch] = opfsoln(baseMVA, bus, gen, branch, ...
						Ybus, Yf, Yt, V, Sg, lambda, ref, pv, pq, mpopt);

%% compute elapsed time
et = etime(clock, t0);

return;