optimise_schedule: Optimise a schedule with an iterating approach
In henobe/flexoptr: Optimise Energy Flexibilities

Description Usage Arguments Details Value See Also

The optimal possible schedule considering a set of prices a pre-existing schedule and physical constraints of a storage is calculated.

1	optimise_schedule(schedule, prices, parameters, shift, blocked = NULL)

`schedule`	a numeric vector of the current schedule.
`prices`	a list of available prices. When an element consists only of NA-values (or a single), then that hour will not be iterated. When some price values inside a list element are NA, this will be interpreted to mean that only those hours are not tradeable.
`parameters`	a named vector of integers, including values for charge_rate, loss_rate, starting_state, and capacity.
`shift`	an integer, indicates the difference to the the sum of the `current_schedule` that is added or subtracted each iteration.
`blocked`	A logical vector indicating whether the schedule for that hour should be kept as is and not changed by the optimisation, same length as schedule.

A current schedule is taken, the corresponding constraints are generated and then the optimal schedule in these constraints is calculated. The necessary trades are then recorded. This procedure is repeated as coded in the prices parameter.

The approach allows for overlapping optimisations, where the result of the previous run influences the outcome of the next - as is the case during a typical intra day optimisation.

Non-overlapping time frames are also handled, as is the case during a day ahead process where the shift represents the energy loss over 24 hours.

A list with three elements, an optimised schedule, the states of the storage according to that new schedule and a data frame of corresponding trades.

build_constraints

henobe/flexoptr documentation built on March 11, 2021, 6:04 p.m.