I believe your two objectives are conflicting. For example, you can always
reduce losses by reducing the power sent to a charging station. I think you
simply want positive benefit functions for your dispatchable loads, where the
benefit is greater than the cost at the single supply bus (plus cost of
losses). If you use a uniform constant marginal benefit for all charging
points, then you will maximize the total charging power in the system, and
implicitly do it in a way that minimizes the losses for that charging pattern,
since it is supplied through a single source with positive cost (i.e.
increasing losses would increase that cost). However, if it is important to
somehow balance the charging availability across the network, rather than just
maximize the total, then you will need to use decreasing marginal benefit
functions (whose minimum still exceeds the cost at the source). In this case,
you will be making a tradeoff between loss minimization (which tends to reduce
cost) and “balancing” which will tend to increase cost.
Hope this helps,
Ray
> On Jan 8, 2015, at 5:41 AM, Simone Cochi <[email protected]> wrote:
>
> Dear Matpower community,
>
> I’m working on modulation of electric vehicle charging points connected to a
> distribution grid. My first aim is to guarantee the maximum available power
> for every charging station in a range between 43 and 129 kW. To implement
> this target the cost function for every charging point (that is modeled as a
> dispatchable load) should be decreasing with the power available to the
> charging point.
>
> My second target is to try to nullify the reverse power flow from the
> distribution grid to the HV network. While doct. Zimmerman suggested to put a
> cost on the primary substation with the procedure explained here
> https://www.mail-archive.com/[email protected]/msg03440.html
> <https://www.mail-archive.com/[email protected]/msg03440.html>, I found
> easier and effective for the network I’m studying to add a constraint on the
> the slack bus with Pg>0 and a constant generator cost which value is:
>
> COSTslack = n*f(129)
>
> where n is the number of charging point and f the cost function of the single
> charging station.
>
> I would like to know if there is a way to guarantee with this cost functions
> that this solution is also the one with the minimum losses. I read the F.A.Q.
> on the subject and it states to put the same constant gencost on all the
> generators, so in my case I have to put the same costant gencost on the slack
> bus and on the charging points but doing so the maximum available power to
> the stations won’t be guaranteed.
>
> Any suggestions?
>
> Simone
>
