LT Plan Chronology

Units:	-
Default Value:	2
Validation Rule:	In (2,3,4)
Description:	Type of chronology used
Detail:

LT Plan Chronology controls the level of detail used in representing the Horizon. The settings can take these values:

Partial (value = 2): Load (or Price) duration curves are formed for each day/week/month/year (as controlled by the LDC Type setting). Each LDC/PDC contains Block Count number of simulation periods. For example, 12 blocks with monthly LDC gives 144 simulation periods per year rather than 8760 for hourly simulation. Note that:

You can reduce the number of blocks used in each curve later in the Horizon using the Last Block Count setting.
Finer control is available over the slicing with the Global Slicing Block property. This is particularly useful for a system with a high concentration of solar generation because it allows you to force periods of similar solar concentration to be kept together in the same LDC block.

Fitted (value = 3): The input Load (or Price) series is fitted with a step function using the weighted least-squares technique so that the total number of simulation periods per day/week/month/quarter/year (as controlled by the LDC Type setting) is equal to the Block Count setting. For example, fitting 50 blocks per week gives 2650 simulation periods per year. Simulation periods preserve their chronology and full chronological detail is available e.g. generator start up and shutdown, ramping rate constraints, battery energy storage, etc. This setting defines a single resolution across the entire Horizon. However, you can vary the resolution in one of two ways:

Reduce the number of blocks fitted down to a minimum defined by Last Block Count; or
Define multiple resolutions that apply to different periods of time using the Resolution Type, Interval Count and Block Count parameters described in Hidden Parameters and first introduced in PLEXOS 8.0.

Sampled (value = 4): Samples are taken of the days/weeks/months (as controlled by the Sample Type setting). The number of samples taken is set by the Reduced Sample Count and/or Reduction Relative Accuracy. Sampling is done statistically such that 'like' periods (days/weeks/months) are removed leaving a sample set that is representative of the variation in the original Load (or Price) series. The sample reduction technique is similar to that used in the Stochastic Reduced Sample Count.; Please note that after sampling a rescaling process is performed, which detects wind, solar, load, etc. profiles (i.e.. highly variable data) and rescales them such that the total energy equals their original input amount. When rescaling the sampled profile, the same method is used as the Load Forecasting. The base profile (that gets rescaled) is the profile that is produced by the sampling process, and the sum/max/min targets come from the original input data for the sampling interval. By default, the linear growth method is used to calculate the scaling factors, and it will automatically switch to quadratic method when linear method produces negative values. The loads in the formulation are the weighted average of the reduced and rescaled samples. To switch off the rescaling process please use the undocumented parameter "SuppressRescalingSampledData" under "Model" class.

Under the "Partial" option (using duration curves) chronology is maintained only between duration curves, not within the curves i.e. for weekly curves, constraints such as Storage Max Volume are tracked only between weeks, and most technical limits such as ramp constraints, and generator start up and shutdown are not tracked.

For both the "Fitted" and "Sampled" options, full chronological modelling is done. The key difference is that under the "Fitted" option the duration of each time period can vary depending on how the underlying intervals are grouped together, whereas under the "Sampled" option the simulation periods are all the 'native' duration controlled by the Horizon Periods per Day setting.

For energy type models, "Fitted" and "Sampled" options query the Region Load or Market Price (for energy markets) along with adjustment factors such as Generator Load Subtracter.

For Universal models you should associate LT Plan with one or more Variable objects using the Variables collection. The Profile property of those Variable objects is then summed to produce the 'shape' for all chronology types to slice, fit and sample.