Dynamic User Constraint across DAYNITE and SEASON

[UCL_Will]

I am trying to implement a dynamic user constraint to make the in/out flow of energy from night-storage heaters more realistic in our model.  At present, our model chooses to release heat mainly during the peak timeslice, which is unrealistic for a night-storage heater which releases heat gradually throughout the day.  This actually has far-reaching implications in our model, and shaves demand off the peak.

I've set about using a dynamic UserConstraint to do this, but am having trouble with the VEDA syntax.

In essence, I want something like this:

So here, the output flow (of heat) from the night storage heater is ACT, indexed by season (W,A,S,P) and daynite time slices (Peak,Evening,Night,Day) and is apportioned according the fraction of the representative day the timeslice represents.  On the RHS, we have the charge going into the storage heater, which only happens during the Night timeslice.

Attached is a zip of the excel spreadsheet and my attempts at the UC.  If anyone could help, I would greatly appreciate it!

Will :o)

[Antti-L]

There are some confusing elements here.

If you want to have a predefined load load curve for night-storage processes (or for any other demand technologies), the easiest way to do that is to define the technology at the annual level, and define the load curve for the output commodity (or commodities). If you want a flat load curve in each season, as you seemed to suggest, you only need to define the seasonal load curve. But usually an electric night storage heating boilers produce both space heat and hot water, and in that case the load curve for hot water should rarely be flat.

Could you comment on why not pursuing this approach?

Anyway, if you still want to have the technology modeled as a genuine storage process (on the DAYNITE level), then the general idea in TIMES is that the process can optimize its output load curve, instead of being fixed to a predefined load curve. In order to force a predefined load curve for the output, you could define user constraints, as you suggest. But because storage processes do not normally have VAR_FLO variables, you cannot use UC_FLO unless you introduce auxiliary storage flows.

With auxiliary storage flows you could thus accomplish, for example,  the formulation of your example equation.

[UCL_Will]

Antti;

Thanks very much for your reply.

The night storage heaters I refer to are relics of the kind you must only find in our dilapidated and severely outmoded buildings we call 'homes' in the UK.  They are essentially bricks around electric resistive wire in a beige metal box.  They have no controls.  They 'charge up' at night on cheaper electricity and they release their stored energy as heat slowly during the day, depending upon the temperature differences etc.

For these technologies, it does not make sense for TIMES to try to match a load curve, as the production of heat by the technology is entirely a function of time, temperature and other non-controllable factors.  Hence my question.

However, I have started working with commodities and technologies defined at seasonal level, which seems to be producing satisfactory results.

Kind regards,

Will

[Antti-L]

Ok, it was my misunderstanding. But anyway, I guess you could well assume a predefined load curve for this kind of a technology, as opposed to letting the model optimize it.

I myself don't know how to model such a night storage capability with a seasonal level technology. It would be nice if you could share your solution here.

[UCL_Will]

Hi Antti;

You kindly attached a demo spreadsheet in your previous reply on the 20th November, but in a subsequent edit you've removed the link.  Would you be able to reinstate it, as it was a useful reference for me, and I think for others?

Kind regards,

Will