When the OPF does not converge successfully, the values contained in the
solution are meaningless.
Ray
> On Feb 4, 2016, at 9:30 AM, Mirish Thakur <[email protected]> wrote:
>
> Dear Prof.Ray,
>
>
>
> I have observed result struct of load2disp whre I found some surprising
> results on the buses where renewable generator and load both are available.
> I kept renewable generation flexible in model so that it should obey the line
> flow limits. I have used zero cost for renewable energy as per my study
> requirement. I obsereved that there is negative dispatch of renewable energy
> and dispatchable load is greater than actual connected load. Please find
> herewith attched Excel file of result of two number of such buses, bus No. 96
> and 164. Where bus no 96 has both renewable generator with 67.97 MW and
> connected load is 113.57+J 20.33. These are some results when solution is not
> converged successfully. In some cases I got perfect convergence. I really
> don't understand why this happens. I really do appreciate your help. Thank
> you for your time.
>
>
>
> Thanks and regards
>
> Mirish Thakur.
>
>
> On Wed, Dec 2, 2015 at 6:19 PM, Mirish Thakur <[email protected]
> <mailto:[email protected]>> wrote:
> Dear Prof. Ray,
>
> Thanks a lot for clarifying my doubts. Actually I forgot to see that loads
> are modeled as negative generator, instead I was focusing on energy prices
> only. And in second one I didn't elaborate properly but I was thinking in the
> same way. Thank you very much for your time.
>
> Regards
> Mirish Thakur
>
> On Wed, Dec 2, 2015 at 6:02 PM, Ray Zimmerman <[email protected]
> <mailto:[email protected]>> wrote:
> 1) It looks like you are setting up gencost correctly. The negative objective
> function value results from the fact that the curtailable loads are being
> modeled as negative generation, with negative costs (positive benefits). So
> rather than simply minimizing generating cost, the OPF is now minimizing the
> negative of the net benefits (i.e. maximizing the net benefits). The
> objective function value is then the negative of the net benefits, so we
> expect it to be a large negative number.
>
> 2) Yes. But to be precise, these curtailments and redispatches are not given
> directly by res.gen(:, PG), but by the deviation of res.gen(:, PG) from the
> corresponding nominal value, i.e. res.gen(:, PMAX) for renewables, res.gen(:,
> PMIN) for dispatchable loads, and the original dispatch reference point for
> conventional generators.
>
> Ray
>
>
>
>> On Dec 1, 2015, at 8:19 PM, Mirish Thakur <[email protected]
>> <mailto:[email protected]>> wrote:
>>
>> Dear Prof. Ray Zimmerman,
>>
>>
>>
>> Thank you very much for your help. I have implemented your suggestion of
>> relaxing constraints over conventional power plants and got successful
>> convergence on both model. While doing so in 2# model I kept minimum value
>> of generation Pmin=0, and instead of using single slack generator output to
>> supply system losses I increased all conventional generators output by 2%
>> means Pmax=(Original Pmax)*1.02. So that losses will be contributed by all
>> generators. But I want to clarify some doubts.
>>
>>
>>
>> 1) My Objective Function Value = -243875269.94 $/hr is highly negative after
>> convergence, that I don’t understand why it’s highly negative. After
>> mpc=load2disp(mycase) I checked mpc.gencost matrix. In my case conventional
>> generators variable cost function is linear e.g. [2 0 0 3 0 10.91 0]
>> and renewable generators and cross border generators cost is zero e.g. [2 0
>> 0 3 0 0 0] and for dispatchable loads I set linear cost function [2 0
>> 0 3 0 5000 0]. Am I using correct values in mpc.gencost matrix? Or I
>> have to use for conventional power plants = [2 0 0 3 0 0 0] and for
>> both renewables and dispatchable loads= [2 0 0 3 0 5000 0] ? Both
>> approach gives negative objective function value.
>>
>>
>>
>> 2) When I perform successfully res=runopf(mpc) all curtailments on renewable
>> / loads / redispatch of conventional power plants will be seen in
>> res.gen(:,2) column (second column of res.gen matrix) right? Thank you very
>> much for your time.
>>
>>
>> Regards
>> Mirish Thakur
>>
>> On Mon, Nov 30, 2015 at 5:54 PM, Ray Zimmerman <[email protected]
>> <mailto:[email protected]>> wrote:
>> Hi Mirish,
>>
>> There is no way to see the load or renewable curtailment until you get a
>> converging OPF. It is possible that you will also have to redispatch the
>> conventional generators in order to get a feasible solution. I would suggest
>> that you combine your option #2 with curtailable loads, relax the active
>> power dispatch constraints on the conventional generators (to their normal
>> limits) and assign piecewise linear costs to those generators with negative
>> or zero marginal cost up to Pg and large positive marginal cost above Pg.
>> This will attempt to minimize deviations from the original dispatch pattern,
>> hopefully moving only those generators necessary to relieve the line
>> overloads.
>>
>> Ray
>>
>>> On Nov 29, 2015, at 7:31 PM, Mirish Thakur <[email protected]
>>> <mailto:[email protected]>> wrote:
>>>
>>> Hello friends,
>>>
>>>
>>>
>>> I’m working on (1000 bus system) reactive power dispatch problem. I have
>>> modeled grid into matpower case file and I’m getting the results of runpf.
>>> But when I use ACOPF it fails to converge.
>>> I have modeled grid into two methods
>>> 1) I used all renewable energy sources generation, pump storage power plant
>>> and cross border energy transfer as negative load. And all conventional
>>> power plants as generators. Dispatch of conventional generators is equal
>>> to residual load so demand is equal to generation. Further I have increased
>>> limits of slack generator to supply system losses and kept rest of
>>> generators dispatch constant by Pmax=Pmin=Pg. Also RATE_A limits should be
>>> unchanged. (Necessary condition for project).
>>>
>>> 2) In other way all renewable energy sources generation, pump storage power
>>> plant and cross border energy transfer are modeled as generators and put
>>> next to all conventional power plants. And in gencost matrix I used zero
>>> variable cost for renewable generation. Slack generator and rest of the
>>> conditions are set as it is in first approach.
>>>
>>>
>>>
>>> My question is in both modeling I got runpf successfully converged but I’m
>>> not getting convergence for ACOPF. So, I checked branch limits on some
>>> branches which I found overloaded by analyzing results of res= runpf
>>> (mymodel). To avoid such overloading I want to change distribution pattern
>>> of load which might be cause of overloading of branches. I tried load2disp
>>> function to get curtailment on load but every time I got failure in
>>> convergence in runopf. I went through below mentioned discussions-
>>>
>>> https://www.mail-archive.com/matpower-l%40cornell.edu/msg04423.html
>>> <https://www.mail-archive.com/matpower-l%40cornell.edu/msg04423.html>
>>> https://www.mail-archive.com/matpower-l%40cornell.edu/msg00790.html
>>> <https://www.mail-archive.com/matpower-l%40cornell.edu/msg00790.html>
>>> https://www.mail-archive.com/matpower-l%40cornell.edu/msg01203.html
>>> <https://www.mail-archive.com/matpower-l%40cornell.edu/msg01203.html>
>>> Is there any way to see curtailment on load or negative generation
>>> (renewable generation/ cross border transfer of energy) so that I can
>>> redistribute that load /negative generation on other bus bars so that I can
>>> avoid overloading of branches and get successful convergence? Many thanks.
>>> Regards
>>> Mirish Thakur
>>>
>>> KIT University
>>
>>
>
>
>
> <res.xlsx>
