initial condition sampling updated

Datasheet.md

@@ -143,7 +143,7 @@ Data generation was orchestrated through Python scripts that interfaced with the
 
 Scenario diversity is achieved through stochastic parameterization of initial conditions and two disturbance categories; these are generated in Python and injected into the simulation models via their respective APIs.
 
-Initial conditions include the power references set-points, grid impedance scale, and grid voltage sag scales. These initial conditions are sampled from uniform distributions. The voltage sag scale is randomly selected from a uniform distribution between 0.8 and 0.99. The grid impedance scale is sampled from a uniform distribution between 1 and 7. The two scales are mutually exclusive, i.e., one is scaled and the other scaling factor remains 1 based on a 50-50% selection chance.
+Initial conditions include the power references set-points, grid impedance scale, and grid voltage sag scales. These initial conditions are sampled from uniform distributions. Active power in both the GFM and GFL modes is uniformly sampled from [0.5-1.7]. Reactive power in the GFL mode is uniformly sampled from [0.2-0.8]. The voltage sag scale is randomly selected from a uniform distribution between 0.8 and 0.99. The grid impedance scale is sampled from a uniform distribution between 1 and 7. The two scales are mutually exclusive, i.e., one is scaled and the other scaling factor remains 1 based on a 50-50% selection chance.
 
 - Load disturbances: A random load of stochastically sampled magnitude is connected to the network at a randomly sampled time and disconnected at a later randomly sampled time. The three-phase random load can be unbalanced across phases in the EMT models. The load parameters are independently drawn from uniform distributions over predefined ranges: R_L ∈ [0.2,2] Ω, L_L ∈ [0.001,0.05] H, and C_L ∈ [1×10^(-6),50×10^(-6)] F. To account for phase imbalance, per-phase parameters are independently resampled from uniform distributions within ±15% of their respective average values, yielding a maximum inter-phase imbalance of 30%. The load connection time is uniformly sampled over the interval [0.5, 5] s.
 - Fault disturbances: Short-circuit events are introduced at randomly sampled occurrence times with randomly sampled durations. The fault type is randomly selected among all the possible 10 three-phase fault types. A A fault ride-through (FRT) behavior is implemented; upon fault detection, the active power reference is set to zero and the inverter prioritizes reactive current injection for voltage support. The fault occurrence time is uniformly sampled over the interval [0.5, 5] s, and the fault duration is uniformly sampled within [0.02, 0.2] s.