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Abi Afthab Wrote:Thanks a lot for detailed reply. How did you get this maximum and minimum load of this process in each season? Is this calculated by (Var_FIn/(8760*year fraction)) of the process in each time slice? Here in my case, the electricity input is the Var_FIn. I am little confused about this term ''maximum load of the process'". I am very sorry for asking this again. If the capacity is defined by the output (as it was for the electrolyser), the load of the process is the power level of the output flow. The power level of the output flow in each timeslice can be obtained by dividing the corresponding flow (VAR_FLO.L(...)) by the year fraction G_YRFR (and optionally converting it to the capacity unit). For example, for power plants the load at any given time is regularly calculated in this way, usually converted to MW. The maximum load in each season is obtained by taking the maximum (highest) value of these levels over the timeslices in the season, and the minimum is obtained by taking the minimum (smallest) value.
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(08072019, 04:18 PM)AnttiL Wrote: Abi Afthab Wrote:Thanks a lot for detailed reply. How did you get this maximum and minimum load of this process in each season? Is this calculated by (Var_FIn/(8760*year fraction)) of the process in each time slice? Here in my case, the electricity input is the Var_FIn. I am little confused about this term ''maximum load of the process'". I am very sorry for asking this again. If the capacity is defined by the output (as it was for the electrolyser), the load of the process is the power level of the output flow. The power level of the output flow in each timeslice can be obtained by dividing the corresponding flow (VAR_FLO.L(...)) by the year fraction G_YRFR (and optionally converting it to the capacity unit). For example, for power plants the load at any given time is regularly calculated in this way, usually converted to MW. The maximum load in each season is obtained by taking the maximum (highest) value of these levels over the timeslices in the season, and the minimum is obtained by taking the minimum (smallest) value.
Thanks a lot Anti.
So if I model part load efficiencies and the model is adjusting the output flows in such a way that there are no part load efficiencies in any time slice that means there should be a corresponding investment in storage also, right? What I mean is if I model without part load efficiencies, I should have less investment in storage?
Although, the logic you explained is sensible, I feel it makes more sense to model this with MILP so that this can be done in discrete unit sizes. If this was done with MILP, the model would have done more investment in the electrolyser instead of storage, right?
But I have seen the documentation mentioning that this extension of TIMES and MILP results won't vary much if there are large number of units. In my case, the 2050 electrolyser capacity requirement constitutes almost 2500+ hydrogen refuelling stations. What do you think about it? I am trying to find out a point justifying this type of modelling.
Regards
Abi Afthab
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08072019, 06:09 PM
(This post was last modified: 08072019, 06:31 PM by AnttiL.)
As you are modelling this kind of hydrogen production and distribution system, and not me, I think you should know better. But sure, one would certainly expect to have some more storage when the production is less flexible, due to the minimum load levels and avoidance of partial load efficiency losses.
If the electrolysers are meant to be highly distributed and supplying only the local demand at each refuelling station (without interconnections), perhaps one might actually think that they can never be shut down in any season, because there is always some demand in all refuelling stations? I don't know, but maybe you know? If so, then you could force the full capacity to be always online (as discussed before), which might conceivably be more realistic for such a very decentralized production system. But as shown above, I don't think there would be any partial load efficiency losses ever realized with your current parameters, because it would be cheaper to burn any excess hydrogen in a flare than to decrease the load below 59.8%...
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(08072019, 06:09 PM)AnttiL Wrote: As you are modelling this kind of hydrogen production and distribution system, and not me, I think you should know better. But sure, one would certainly expect to have some more storage when the production is less flexible, due to the minimum load levels and avoidance of partial load efficiency losses.
If the electrolysers are meant to be highly distributed and supplying only the local demand at each refuelling station (without interconnections), perhaps one might actually think that they can never be shut down in any season, because there is always some demand in all refuelling stations? I don't know, but maybe you know? If so, then you could force the full capacity to be always online (as discussed before), which might conceivably be more realistic for such a very decentralized production system. But as shown above, I don't think there would be any partial load efficiency losses ever realized with your current parameters, because it would be cheaper to burn any excess hydrogen in a flare than to decrease the load below 59.8%...
Thanks for your valuable insights.
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(08072019, 06:38 PM)MohammedAbiAfthab Wrote: (08072019, 06:09 PM)AnttiL Wrote: As you are modelling this kind of hydrogen production and distribution system, and not me, I think you should know better. But sure, one would certainly expect to have some more storage when the production is less flexible, due to the minimum load levels and avoidance of partial load efficiency losses.
If the electrolysers are meant to be highly distributed and supplying only the local demand at each refuelling station (without interconnections), perhaps one might actually think that they can never be shut down in any season, because there is always some demand in all refuelling stations? I don't know, but maybe you know? If so, then you could force the full capacity to be always online (as discussed before), which might conceivably be more realistic for such a very decentralized production system. But as shown above, I don't think there would be any partial load efficiency losses ever realized with your current parameters, because it would be cheaper to burn any excess hydrogen in a flare than to decrease the load below 59.8%...
Thanks for your valuable insights.
