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 confused about these 
> points:
> 
> 1-     The contract value "Pc": I understood that it is obtained in the 1st 
> stage optimization solution and the deviations from it "P+" & "P-" are 
> obtained 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 give optimization solution for only one stage, so we 
> got solutions of stage1 (in one run) and use the values of stage 1 to run 
> MOST again for stage2 solution. Am I right 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 
<http://www.pserc.cornell.edu/matpower/docs/MATPOWER-manual-6.0.pdf>, 
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 
> <http://www.pserc.cornell.edu/matpower/docs/MOST-manual-1.0.pdf>. See my 
> responses below for more comments  ...
> 
>> On May 20, 2018, at 5:43 PM, ⁨‫Shady Mamdouh‬ ‫⁩ 
>> <⁨[email protected] <mailto:[email protected]>⁩> wrote:
>> 
>> Hello Dear, 
>> Regarding the problem formulation in MOST program, I have these questions 
>> that I am confused about.
>>  
>> 1- Difference between zonal reserve and contingency reserve : I understand 
>> that zonal reserve are some constant amount of reserve specified before the 
>> solution, but what is the definition of "zone" and how can I specify zones? 
>> and what is the difference between zone and area in bus data? And what is 
>> the difference between zonal reserve and contingency reserve?
> 
> See section 3.2 of the MOST User’s Manual 
> <http://www.pserc.cornell.edu/matpower/docs/MOST-manual-1.0.pdf>, along with 
> section 7.5.1 in the MATPOWER User’s Manual 
> <http://www.pserc.cornell.edu/matpower/docs/MATPOWER-manual-6.0.pdf>. 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 is meant 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 
> <http://www.pserc.cornell.edu/matpower/docs/MOST-manual-1.0.pdf>. 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 contingency reserve 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 load following 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 and utility or what?)
>> and how its value be determined? (After MOST solution or the user specifies 
>> its value?) and what about the deviations from it ? 
>> From my reading on the manual and the papers "Secure Planning and Operations 
>> of Systems with Stochastic Sources, Energy Storage, and Active Demand" & 
>> "Stochastically Optimized, Carbon-Reducing Dispatch of Storage, Generation, 
>> and Loads", I understand that we have 2 stages, stage 1 determines the 
>> contract value and stage 2 determines the deviations from this value as a 
>> recourse 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 functions Cp(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 of probabilities in the objective functions:
>> ψα: probability of contingency used in cost of dispatch and redispatch 
>> function f(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 to period 't' (what does "it" refer to here?) 
>> and why this probability used 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 model instead of nonlinear network network the 
>> problem is converted from MINLP to MIQP, 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 energy prices" mean? and what is the difference between 
>> it and "shadow prices" 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 used to model transmission systems and one can 
>> add wind and storage sources, but if I want to model a Microgrid, how can I 
>> use MOST to model it? And what about adding 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 transmission congestion and its effect on nodal energy 
>> prices, storage, and min up&down times?
> 
> 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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