conv_simulations

Functions

adaptable_new_op(net, init_pcc_pq[, ...])

Calculate FA using previous FA estimation for different operating conditions.

combine_shapes(shapes, pq_steps)

Combine the feasible regions for different discontinuous area setpoints.

combine_shapes_const_flex(shapes, pq_steps, flex)

Combine the feasible regions for different discontinuous area setpoints, in case where no network constraint can be reached.

create_mat_dict_incl_delta(result_dict, dp, ...)

Create matrices, dictionaries, and axes from a result dictionary including delta values.

create_mat_dict_order(result_dict, dp, dq[, ...])

Create matrices and dictionaries from a result dictionary using PyTorch tensors.

create_mat_dict_tensor(result_dict, dp, dq)

Create matrices and dictionaries from a result dictionary using PyTorch tensors.

create_mat_dict_tensorv2(result_dict, dp, dq)

Create matrices and dictionaries from a result dictionary using PyTorch tensors.

create_multi_small_fsp_fas(prof_dict, dp, ...)

Create a multi-flexibility area (MFA) by combining small feasible space profiles.

df_to_mat_tensor_scaled_and_init(df, dp, dq)

Take dataframes of power flow results and create matrices of feasible regions, sensitivities for tensor convolutions.

df_to_mat_tensor_torch(df, dp, dq)

Take dataframes of power flow results and create matrices of feasible regions, sensitivities for tensor convolutions.

df_to_mat_tensor_torchv2(df, dp, dq)

Take dataframes of power flow results and create matrices of feasible regions, sensitivities for tensor convolutions.

enhance_multi_big_fa(fa[, times])

Enhance the size of a multi-flexibility area (MFA) using bilinear interpolation.

find_value_close2list(lst, voi)

Find the index and closest value in a list to a specified value.

get_bus_line_and_trafo_names(net)

Get names of buses, lines, and transformers in a power distribution network.

get_delta(df, dp, dq, init_pq)

Take dataframes of power flow results and create matrices of feasible regions, sensitivities for tensor convolutions, for non-linear FSPS.

get_init_net_state(net)

Calculate initial network component voltage and loading values.

get_multi_conv_key_adapting_new_op(comp, ...)

Calculate flexibility region for component from sensitive FSPs using previous FA estimation for different operating conditions.

get_multi_conv_key_saving(fsps_of_comp, ...)

Calculate flexibility region for component from sensitive FSPs, perform TTD on the tensors and save them locally.

get_multi_conv_key_with_delta(fsps_of_comp, ...)

Calculate flexibility region for component from sensitive FSPs, while having discrete FSPs.

get_multi_conv_torch(fsps_of_comp, ...[, ...])

Calculate flexibility region for component from sensitive FSPs.

get_multi_conv_torch_split(fsps_of_comp, ...)

Calculate flexibility region for component from sensitive FSPs, but merge FSPs until maximum fsps are no_max-1.

get_multi_result_for_0_effective(...)

Estimate flexibility area if no component can reach its constraint.

get_multi_uncertain_fa(pq_mat, large_fa, ...)

Calculate multiple uncertain feasibility areas from given power matrices.

get_new_conv_axes2(list_of_rows, ...)

Combine axes per FSP to get the final flexibility area axes.

get_non_effective_multi_conv(...)

Estimate flexibility area by convolving non-effective fsps with the region from the effective fsps.

get_non_effective_multi_conv_with_delta(...)

Estimate flexibility area by convolving non-effective fsps with the region from the effective fsps, also accounting for non-effective non-linear FSPs.

get_result_for_0_effective_with_delta(...)

Estimate flexibility area if no component can reach its constraint, and non-linear FSPs exist.

numpy_tensor_conv_simulations_saving(net, ...)

Calculate FA using Tensors and Convolutions, while saving the tensors (after TTD) to adapt FA in other operating conditions.

numpy_tensor_conv_simulations_with_delta(...)

Calculate FA using Tensors and Convolutions, when at least 1 fsp can only shift in certain setpoints.

profiles_to_mat(profiles, dp, dq, init_fsp_pq)

Take dataframes of power flow results and create matrices of feasible regions.

reduce_multi_fa_small(fa[, times])

Reduce the size of a multi-flexibility area (MFA) using bi-linear interpolation.

run_all_tensor_flex_areas(net, pq_profiles, ...)

Run power flows for all FSP setpoints given.

split_lin_from_non_lin(comp_dict, non_lin_fsp)

Split linear from non-linear FSPs.

torch_tensor_conv_large_simulations(net, ...)

Calculate FA using Tensors and Convolutions, but merge FSPs in components who have no_max or more FSPs sensitivities, until maximum sensitive FSPs are no_max-1 per component.

torch_tensor_conv_simulations(net, ...[, ...])

Calculate FA using Tensors and Convolutions.

update_conv_pqs(net, fsp_idx, fsp_type, profile)

Update the FSPs to perform power flows.