Thermal modeling for transmission lines, in Julia. Compliant with IEEE Standard 738-2012.

From Julia prompt:

]dev https://github.com/kersulis/LineThermalModel.jl

The following functions are exported. Use ? to see input and output descriptions for any function; all are well-documented.

• eq2c_N_Re
• eq3a_q_c1
• eq3b_q_c2
• eq4a_K_angle
• eq6_T_film
• eq8_q_s
• eq9_theta
• eq13a_mu_f
• eq14a_p_f
• eq15a_k_f
• eq_omega
• eq16a_H_c
• eq16b_delta
• eq17a_Z_c
• eq17b_chi
• eqtable2_C
• eq18_Q_s
• eq19_Q_se
• eq20_K_solar
• eq_eta_c
• eq_eta_r

Equations are named according to their numbers in IEEE Standard 738. The equation number is followed by an underscore, then by the name of the parameter returned.

Return a table of ACSR data in English or SI units as follows:

table, labels = acsr_table_english()
table, labels = acsr_table_si()

More importantly, there is a simple lookup algorithm for estimating ACSR conductor type based on a line's current rating (in Amps) and base voltage (in Volts):

a = acsr_interpolation(I_lim, V_base; metric=true)

In the line above, a is an instance of ACSRSpecsMetric; with metric=false, it would be an instance of ACSRSpecsEnglish. Either way, a contains a best-estimate ACSR assignment for the given current limit and base voltage.

Credit to Mads Almassalkhi for ACSR functionality.

The length of a line may be estimated as follows. Use ? or check the source for detailed descriptions of each argument.

length = estimate_length(S_base, V_base, R_pu, R_cond, bundle)

While PowerModels is not a dependency of LineThermalModel.jl, two of its functions are overloaded to work with the network_data dictionary structure described here: acsr_interpolation and estimate_length. When either of these functions is given a network_data dictionary, it will return a dictionary with the same keys as network_data["branch"].