Clarifying the description of the "selfDischargeLoss" parameter to match the way it functions in the "q_balance" equation.

NOTE! This is a rather unconvetional way to impelement self-discharge, as typically these values are given as percentage of state lost over some time interval. However, the way it had been (accidentally) implemented in the code is actually more robust for possible changes in the length of the timestep.

Various changes required for running both the building model, the dispatch model, and the combined model. IMPORTANT! The modelsInit.gms is key, when defining multiple models.

Because some of the parameters in the model definition file don't have the "mType" dimension, multiple model declarations result in overwriting previous model settings by the newer ones. For this reason, it becomes necessary to define the models in a certain order to avoid errors. This issue will probably need to be fixed at some point.

Fixing an issue with replacing missing time series data using the ct(t). Needs defining in e.g. periodicInit.gms to function properly.

Bratio should be < 1 so that the model will use advanced basis. Important when scheduling and only little changes between solves.

# Conflicts:
#	inc/2b_equations.gms

Fixing problems in using forecasts and reserves. May include some ad hoc changes that need to be cleared up later.

Conflicts:
	inc/2b_equations.gms

A version with commitment of units into reserves plus release of tertiary reserves in the operating hour.

A version with commitment of units into reserves plus release of tertiary reserves in the operating hour.

Possible problem here - when forecast branches were combined (with mft_bind and mt_bind) then online units were forced to equal 0 if the unit did not have online variable in the time period to be bound to.

# Conflicts:
#	Backbone.json

Reimplemented the "boundAll" conditional for the "q_balance" constraint to avoid unnecessary "vq_gen" variables for nodes with fully bound nodes.

Also added diagnostic result vectors "d_cop" and "d_eff" that calculate the realized COP of energy conversion units and the efficiency of fuel units. These are mainly used for testing and debug purposes, as the COP and efficiency time series for norman operation aren't all that interesting.

Now considers the "ts_nodeState" as well as "ts_influx" when finding the maximum length of time series.

Lambdas are now calculated using v_online variable for fuel use section (no load fuel use). If lowest operating point is zero, the user can define the section or the operating point where the first cross between p_unit efficiency curve and approximated efficiency curve takes place. Section takes precedence.

This avoids the issue, where the efficiency stayed constant until the first non-zero 'rb' defined in the efficiency data.

Making it possible for "maxGen" to be negative, which is a special case currently required by cooling equipment.

Cooling equipment are quite irregular when it comes to Backbone's node-unit-structure, as they consume energy in order to get rid of energy elsewhere. In this commit, the desired behavior is achieved by defining both the "maxGen" and "slope" of the cooling units as negative, which results in the input "v_gen" still being drawn as normal, but the output "v_gen" is converted into "negative energy" with the negative "slope".

Another possible approach would have been to define cooling equipment as sort of heat pumps (which they sort of are in reality), defining both the electrican grid and the cooled heat node as input nodes and constraining their input ratios. However, this would have required creating a heat sink node where the heat is transported, and giving that node the "v_spill" variable. All in all, this method was simpler for the time being.