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Runs an optimal power flow with fixed zonal reserves.
Runs an optimal power flow with the addition of reserve requirements
specified as a set of fixed zonal reserves. See runopf for a
description of the input and output arguments, which are the same, with
the exception that the case file or dict casedata must
define a 'reserves' field, which is a dict with the following fields:
-
zones nrz x ng, zone(i, j) =
1, if gen j belongs to zone i 0,
otherwise
-
req nrz x 1, zonal reserve requirement
in MW
-
cost (ng or ngr) x
1, cost of reserves in $/MW
-
qty (ng or ngr) x
1, max quantity of reserves in MW (optional)
where nrz is the number of reserve zones and
ngr is the number of generators belonging to at least one
reserve zone and ng is the total number of generators.
In addition to the normal OPF output, the results dict
contains a new 'reserves' field with the following fields, in addition to
those provided in the input:
-
R - ng x 1, reserves provided by each
gen in MW
-
Rmin - ng x 1, lower limit on reserves
provided by each gen, (MW)
-
Rmax - ng x 1, upper limit on reserves
provided by each gen, (MW)
-
mu.l - ng x 1, shadow price on reserve
lower limit, ($/MW)
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mu.u - ng x 1, shadow price on reserve
upper limit, ($/MW)
-
mu.Pmax - ng x 1, shadow price on Pg
+ R <= Pmax constraint, ($/MW)
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prc - ng x 1, reserve price for each
gen equal to maximum of the shadow prices on the zonal requirement
constraint for each zone the generator belongs to
See t.t_case30_userfcns for an example case file with fixed
reserves, and toggle_reserves for the implementation.
Calling syntax options:
results = runopf_w_res(casedata)
results = runopf_w_res(casedata, ppopt)
results = runopf_w_res(casedata, ppopt, fname)
results = runopf_w_res(casedata, [popt, fname, solvedcase)
results, success = runopf_w_res(...)
Example:
results = runopf_w_res('t_case30_userfcns')
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