Thanks for your reply,
I have some questions about section 3.4 (page 20, 21) in MOST manual:
The different approaches to define scenarios in multi period stochastic
problems.
I want to understand what meant by:
1. Defining each scenario asrealization of all uncertainties, defining a
full trajectory.
2. Non anticipativity of recourse decisions sinceuncertainty is revealed
period by period.
3. Markovian structure
4. Probability transition matrix
5. Are contingency cases are includedin the probability transition matrix or
it is limited to base case scenariosonly?
6. What is the difference when definea base case and a contingency case?
(where I can define the probabilities ofcontingencies?)
7. Can I use another scenario generationtechnique then use MOST's prob
transition matrix for my generated scenarios?
Thanks in advance.
من: Ray Zimmerman <[email protected]>
إلى: MATPOWER discussion forum <[email protected]>
تاريخ الإرسال: الثلاثاء 22 مايو، 2018 6:54 م
الموضوع: Re: Issues about Problem Formulation in MOST
See responses below ...
Ray
On May 22, 2018, at 11:58 AM, Shady Mamdouh
<[email protected]> wrote:
Thanks for your appreciated answers but I'm still little confusedabout these
points:
1- The contract value"Pc": I understood that it is obtained in the 1st stage
optimizationsolution and the deviations from it "P+" & "P-" areobtained at the
2nd stage. Am I right?
MOST does not define two stages. But if you use it to solve two stages, e.g. a
day-ahead unit commitment problem, followed by a real-time re-dispatch, then
the day-ahead problem could include both a reference dispatch Pc that you could
use to define some day-ahead contract, and the “what-if” incremental and
decremental dispatches (P+ and P-) that would be required as deviations from
that reference point if particular scenarios are realized.
2- Each run of MOST giveoptimization solution for only one stage, so we got
solutions of stage1 (in onerun) and use the values of stage 1 to run MOST again
for stage2 solution. Am Iright here?
This is a very reasonable way to use MOST. However, given that a second stage
(e.g. real-time re-dispatch) will hopefully have more up-to-date information
available as inputs, the dispatches coming out of this problem need not match
the dispatches of any of the probabilistic states considered in the day-ahead
problem.
3- Definition of "zones"in zonal reserve and how to specify them.
A zone is simply a subset of generators, defined by the mpc.reserves.zones
matrix as described in Section 7.5.1 of the MATPOWER User’s Manual, especially
see Table 7-4. See also the description in Section 7.2 on page 66.
4- Meaning of ramping costs(wear and tear).
These are intended to model real physical costs incurred due to ramping from
one period to the next, modeled as C_∂ * (P_t - P_t+1)^2.
Thanks in advance
من: Ray Zimmerman <[email protected]>
إلى: MATPOWER discussion forum <[email protected]>
تاريخ الإرسال: الإثنين 21 مايو، 2018 3:49 م
الموضوع: Re: Issues about Problem Formulation in MOST
The main thing I would recommend is to study the mathematical formulation in
Chapter 4 of the MOST User’s Manual. See my responses below for more comments
...
On May 20, 2018, at 5:43 PM, Shady Mamdouh
<[email protected]> wrote:
Hello Dear, Regarding the problem formulationin MOST program, I have these
questions that I am confused about. 1- Difference between zonal reserveand
contingency reserve : I understand that zonal reserve are some constantamount
of reserve specified before the solution, but what is the definition of"zone"
and how can I specify zones? and what is the difference betweenzone and area in
bus data? And what is the difference between zonal reserve andcontingency
reserve?
See section 3.2 of the MOST User’s Manual, along with section 7.5.1 in the
MATPOWER User’s Manual. The BUS_AREA column of the bus matrix is used for area
summaries in the pretty printed output of MATPOWER and also can be used by a
few other functions such as scale_load() and apply_changes() to make area-wide
modifications to a case. The ZONE column is a loss zone identifier originally
from IEEE and/or PSS/E formats, but is not currently used at all by MATPOWER or
MOST.
2- Contingency reserves: what ismeant by it? and how can this reserve amount
be determined or calculated? is its value determined after MOST solution or
pre-specified?
See section 3.2 of the MOST User’s Manual. It is determined by the MOST
solution and is defined as the maximum upward and downward deviations across
all base and contingency dispatches from the reference dispatch.
3-Difference between contingencyreserve limits and physical ramping limits?
Physical ramping limits are used to constrain all base dispatches in one period
with respect to all base dispatches in adjacent periods. Contingency reserves
are limited by both physical capabilities and offered reserve capacity and are
determined by the optimization (and thus also depend on the cost) and they
apply only within a given period to the deviations across base and contingency
cases from the reference dispatch for that period. See also Figure 3-3.
4- Difference between loadfollowing ramping (wear & tear) and load following
ramp reserves?
See section 3.5 and Figure 3-6. Load following ramp is used to impose a
probability-weighted quadratic cost on all base-case transitions.
Load-following ramp reserve quantities are (like contingency reserves) outputs
of the optimization determined by the cost of the maximum ramps from a base
state in one period to a base state in the next and the quantity can be
restricted by physical ramp limits as well as an offered ramping capacity.
5-Active contract value"Pc": what does it mean? (Is this a contract between
consumers andutility or what?)and how its value be determined? (AfterMOST
solution or the user specifies its value?) and what about the deviationsfrom it
? From my reading on the manual andthe papers "Secure Planning and Operations
of Systems withStochastic Sources, Energy Storage, and Active Demand" &
"StochasticallyOptimized, Carbon-Reducing Dispatch of Storage, Generation,
andLoads", I understand that we have 2 stages, stage 1 determines thecontract
value and stage 2 determines the deviations from this value as arecourse action.
MOST solves the problem with the formulation given in Chapter 4 of the manual.
This can be used to implement a two stage market (e.g. day-ahead that
determines the contract value and real-time that determines recourse deviations
from the contract) by using it to solve separate problems for each stage, but
any given run of MOST is simply solving a problem which is (potentially a
subset) of the form given in Chapter 4. In this formulation, Pc only has
meaning for stochastic problems where you have multiple base cases and/or
contingencies. Pc is an optimization variable which is simply the reference
dispatch from which upward and downward deviations are defined for inc/dec
costs and contingency reserves. In a day ahead problem, for example, it could
be used as the day-ahead contract quantity between the ISO and the generators,
but this is a matter of market design. It’s value need not be used at all. The
full range from Pc – downward contingency reserves to Pc + upward contingency
reserves is required to be able to meet the contingencies. The value of Pc
simply determines how much of the reserves are “upward” and how much are
“downward” and, depending on the problem, may not even be well-defined.
6- Details about the cost functionsCp(P), CR(r), Cδ(δ)….. : the form of the
equations,is it a quadratic or what type? And the coefficient needed to specify
them?
These are specified in the xGenData as described in Table 5-1. C_P() and C_R()
are linear and C_∂() is quadratic.
7-Confusion about the usage ofprobabilities in the objective functions:
ψα: probability of contingency used in cost of dispatch and redispatch
functionf(p,p+,p-).(why it used in this cost function only?)
Because the summations in this term are over all individual states, each of
which has it’s own probability of occurring. Dispatch and deviation variables
are per state.
ϒ: probability of making it toperiod 't' (what does "it" refer to here?) and
why this probabilityused in all objective functions except the cost of dispatch
& redispatch f(p,p+,p-)?
Other cost terms are summed over period only, so the probability is of “making
it to period t” or to put it another way “the probability of avoiding all
contingencies before arriving at period t”. For example, reserve variables are
per-period, not per-state, so there is no summation over the states in period t
for reserve costs. The summations are only over period.
8-When using the DC network modelinstead of nonlinear network network the
problem is converted from MINLP toMIQP, How does this happen? (Why not
converted to MILP problem?)
MOST does not implement the AC network model case, so the choice is between a
DC network or no network. With a DC network there are two cost terms that can
be quadratic, one is the generator costs themselves and the other is the
ramping wear-and-tear costs. This makes it a MIQP problem. If you don’t want to
do unit commitment it turns into a QP. If you have linear generator costs and
no ramping wear-and-tear costs it is an MILP. And with no UC, linear gen costs
and no ramping wear-and-tear costs, it becomes a simple LP.
9- What does "Nodal energyprices" mean? and what is the difference between it
and "shadowprices" and "marginal prices”?
Shadow price is a general term referring to the Kuhn-Tucker/Lagrange multiplier
on any given constraint. Nodal energy prices refers to the expected marginal
prices of energy at a node and is the sum of the shadow prices on the power
balance constraints for that node across the states in that period (adjusted by
the probability of making it to that period).
10- I understand that MOST is usedto model transmission systems and one can add
wind and storage sources, but ifI want to model a Microgrid, how can I use MOST
to model it? And what aboutadding PV generation?
If a DC model is appropriate, there should be no difference. You could model PV
as an uncertain source of generation, just like wind.
11- What meant by transmissioncongestion and its effect on nodal energy
prices, storage, and min up&downtimes?
Transmission congestion simply refers to binding branch flow constraints. The
presence or absence of binding transmission flow limits can affect the entire
solution, including all prices, dispatches and commitments.
Hope this helps,
Ray
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