old_contents: def opf_settings():
      opf_settings = {
          # name of postmethod, right now this is just the scenario name and every scenario is handle in one problem setup
          # the so-called postmethod
          # for future extension define multiple postmethods in different julia files which will be call by the scenarioname
          "scenario": "nep",
          # objective function, DEFAULT "nep", future extension might include "generation costs" "storage costs" etc.
          "objective": "nep",
          # chosen relaxation, DEFAULT: "none", options: "none", "soc", "soc_cr", "cr", relaxation are described in
          # masterthesis "MULTIPERIOD OPTIMAL POWER FLOW PROBLEM IN DISTRIBUTION SYSTEM PLANNING" by Jaap Pedersen
          "relaxation": "none",
          # upper bound on network expansion, int, DEFAULT: 10
          "max_exp": 10,
          # number of time steps considered in optimization
          "time_horizon": 2,
          # length of time step in hours
          "time_elapsed": 1.0,
          # storage units are considered, DEFAULT:False, if true storage units will be located either at buses given in
          # "storage_buses" or if "storage_buses"=[] all buses are considered as possible locations
          "storage_units": False,
          # positioning of storage units, if empty list, all buses are potential positions of storage units and
          # capacity is optimized, entries of list need to be type "int"
          "storage_buses": [],
          # total storage capacity in the network, sizing of storages is a decision variable and will be found in optimization
          "total_storage_capacity": 0.0,
          # Requirements for curtailment in every time step is considered, DEFAULT: False
          "curtailment_requirement": False,
          # List of total curtailment for each time step, len(list)== "time_horizon"
          "curtailment_requirement_series": [],
          # An overall allowance of curtailment is considered DEFAULT: False,
          "curtailment_allowance": False,
          # Maximal allowed curtailment over entire time horizon,
          # DEFAULT: 0.0, float
          "curtailment_total": 0.0,
          # Solver options
          # DEFAULT: IPOPT, right now only option
          "solver": "Ipopt",
          "solver_tol": 1e-8,
          # estimated working space for MUMPS if IPOPT,
          # smaller values might reduce required memory requirements, DEFAULT: 1000
          # see: https://coin-or.github.io/Ipopt/OPTIONS.html
          "mumps_mem_percent": 1000,
          "clusters" : {}
          }
      return opf_settings
  
new_contents: def opf_settings():
      opf_settings = {
          # name of postmethod, right now this is just the scenario name and every scenario is handle in one problem setup
          # the so-called postmethod
          # for future extension define multiple postmethods in different julia files which will be call by the scenarioname
          "scenario": "nep",
          # objective function, DEFAULT "nep", future extension might include "generation costs" "storage costs" etc.
          "objective": "nep",
          # chosen relaxation, DEFAULT: "none", options: "none", "soc", "soc_cr", "cr", relaxation are described in
          # masterthesis "MULTIPERIOD OPTIMAL POWER FLOW PROBLEM IN DISTRIBUTION SYSTEM PLANNING" by Jaap Pedersen
          "relaxation": "none",
          # Dictionary of linked time steps in the format {linked step => original step}
          "clusters" : {},
          # upper bound on network expansion, int, DEFAULT: 10
          "max_exp": 10,
          # number of time steps considered in optimization
          "time_horizon": 2,
          # length of time step in hours
          "time_elapsed": 1.0,
          # storage units are considered, DEFAULT:False, if true storage units will be located either at buses given in
          # "storage_buses" or if "storage_buses"=[] all buses are considered as possible locations
          "storage_units": False,
          # positioning of storage units, if empty list, all buses are potential positions of storage units and
          # capacity is optimized, entries of list need to be type "int"
          "storage_buses": [],
          # total storage capacity in the network, sizing of storages is a decision variable and will be found in optimization
          "total_storage_capacity": 0.0,
          # Requirements for curtailment in every time step is considered, DEFAULT: False
          "curtailment_requirement": False,
          # List of total curtailment for each time step, len(list)== "time_horizon"
          "curtailment_requirement_series": [],
          # An overall allowance of curtailment is considered DEFAULT: False,
          "curtailment_allowance": False,
          # Maximal allowed curtailment over entire time horizon,
          # DEFAULT: 0.0, float
          "curtailment_total": 0.0,
          # Solver options
          # DEFAULT: IPOPT, right now only option
          "solver": "Ipopt",
          "solver_tol": 1e-8,
          # estimated working space for MUMPS if IPOPT,
          # smaller values might reduce required memory requirements, DEFAULT: 1000
          # see: https://coin-or.github.io/Ipopt/OPTIONS.html
          "mumps_mem_percent": 1000,
          }
      return opf_settings
  
subject: Add comment for cluster parameter