Adaptive Alternating Direction Method of Multipliers (Adaptive ADMM)
PowerModelsADA.solve_dopf_adaptive_admm — Functionsolve_dopf_adaptive_admm(data::Dict{String, <:Any}, model_type::DataType, optimizer;
mismatch_method::String="norm", tol::Float64=1e-4, max_iteration::Int64=1000,
print_level::Int64=1, print_optimizer_info::Bool=false, alpha::Real=1000)Solve the distributed OPF problem using adaptive ADMM algorithm.
Arguments:
- data::Dict{String, <:Any} : dictionary contains case in PowerModel format
- model_type::DataType : power flow formulation (PowerModel type)
- optimizer : optimizer JuMP initiation object
- mismatch_method::String="norm" : mismatch calculation method (norm, max)
- tol::Float64=1e-4 : mismatch tolerance
- max_iteration::Int64=1000 : maximum number of iteration
- print_level::Int64=1 : 0 - no print, 1 - print mismatch after each iteration and result summary, 2 - print optimizer output
- alpha::Real=1000 : algorithm parameter
PowerModelsADA.solve_dopf_adaptive_admm_coordinated — Functionsolve_dopf_adaptive_admm(data::Dict{String, <:Any}, model_type::DataType, optimizer;
mismatch_method::String="norm", tol::Float64=1e-4, max_iteration::Int64=1000,
print_level::Int64=1, print_optimizer_info::Bool=false, alpha::Real=1000)Solve the distributed OPF problem using adaptive ADMM algorithm.
Arguments:
- data::Dict{String, <:Any} : dictionary contains case in PowerModel format
- model_type::DataType : power flow formulation (PowerModel type)
- optimizer : optimizer JuMP initiation object
- mismatch_method::String="norm" : mismatch calculation method (norm, max)
- tol::Float64=1e-4 : mismatch tolerance
- max_iteration::Int64=1000 : maximum number of iteration
- print_level::Int64=1 : 0 - no print, 1 - print mismatch after each iteration and result summary, 2 - print optimizer output
- alpha::Real=1000 : algorithm parameter
PowerModelsADA.adaptive_admm_methods — Moduleadaptive ADMM algorithm module contains build and update methods
PowerModelsADA.adaptive_admm_methods.build_method — Methodbuild PowerModel object for the adaptive ADMM algorithm
PowerModelsADA.adaptive_admm_methods.calc_dual_residual_adaptive! — Methodcalc_dual_residual!(data::Dict{String, <:Any}; central::Bool=false)calculate the dual redidual as seen by the area. Set central=true if the algorithm uses the optimality condition of a central coordinator.
PowerModelsADA.adaptive_admm_methods.initialize_method — Methodinitialize the adaptive ADMM algorithm
PowerModelsADA.adaptive_admm_methods.objective_adaptive_admm — Methodadaptive ADMM algorithm objective function
PowerModelsADA.adaptive_admm_methods.solve_method — Methodsolve distributed OPF using adaptive ADMM algorithm
PowerModelsADA.adaptive_admm_methods.update_method — Methodupdate the adaptive ADMM algorithm data after each iteration
PowerModelsADA.adaptive_admm_coordinated_methods — Moduleadaptive ADMM algorithm module contains build and update methods
PowerModelsADA.adaptive_admm_coordinated_methods.build_method_coordinator — Methodbuild PowerModel object for the ADMM algorithm coordinator
PowerModelsADA.adaptive_admm_coordinated_methods.build_method_local — Methodbuild PowerModel object for the adaptive ADMM algorithm
PowerModelsADA.adaptive_admm_coordinated_methods.initialize_method_coordinator — Methodinitialize the adaptive ADMM algorithm
PowerModelsADA.adaptive_admm_coordinated_methods.initialize_method_local — Methodinitialize the adaptive ADMM algorithm
PowerModelsADA.adaptive_admm_coordinated_methods.objective_adaptive_admm_coordinator — Methodadaptive ADMM algorithm objective function
PowerModelsADA.adaptive_admm_coordinated_methods.objective_adaptive_admm_local — Methodadaptive ADMM algorithm objective function
PowerModelsADA.adaptive_admm_coordinated_methods.solve_method — Methodsolve distributed OPF using adaptive ADMM algorithm
PowerModelsADA.adaptive_admm_coordinated_methods.update_method_coordinator — Methodupdate the adaptive ADMM algorithm data after each iteration
PowerModelsADA.adaptive_admm_coordinated_methods.update_method_local — Methodupdate the adaptive ADMM algorithm data after each iteration