/TLBO-FR4DN

Primary LanguagePython

TLBO-FR4DN

Teaching Learning Based Optimization Algorithm for Fault Recovery of Distribution Network with Distributed Genaration

Dataset: IEEE33-node system

  • Table 1: IEEE33 node data
  • Table 2: IEEE33 node voltage
  • Table 3: IEEE33 node load

Modified IEEE33-node distribution system

Other Data Description

  • Table 1: Daily power demand of different types of loads
  • Table 2: Node load recovery priority factor
  • Table 3: Distributed DG Power
  • Table 4: Node load at 13:00 and 19:00
  • Table 5: Node load type
  • Table 6: Importance level of node

Use of Source Code

GA

  • island.py

    • Function: This file aims to recover the first phase of power grid restoration strategy, and divide the power grid into islands.
    • Input: Fault network information
    • Output: Power grid after the first phase of restoration

  • base_on_tulun.py

    • Function: This file aims to modify and improve an infeasible solution, and output a feasible solution which is called by pso.py.
    • Input: Infeasible solution
    • Output: A feasible solution

  • fitness.py

    • Function: his file aims to calculate the network loss objective function of the power grid, and output the network loss, which is called by pso.py.
    • Input: Power grid information
    • Output: Objective function

  • ga.py

    • Function: This file aims to perform genetic algorithm calculation on the power grid to obtain the optimal solution. It is the main function file that calls other files.
    • Input: Fault network information
    • Output: Feasible solution

  • satisfy_condition.py

    • Function: This file aims to impose some constraint conditions on the power grid, and constrain the power grid in terms of current, voltage and topology. It is called by pso.py.
    • Input: Power grid information
    • Output: Returns a boolean value

  • x_solution.py

    • Function: Calculates the initial population for the fault network and is called by pso.py.
    • Input: Power grid information
    • Output: Produces initial population

PSO

  • island.py

    • Function: This file aims to recover the first phase of power grid restoration strategy, and divide the power grid into islands.
    • Input: Fault network information
    • Output: Power grid after the first phase of restoration

  • base_on_tulun.py

    • Function: This file aims to modify and improve an infeasible solution, and output a feasible solution which is called by pso.py.
    • Input: Infeasible solution
    • Output: A feasible solution

  • fitness.py

    • Function: This file aims to calculate the network loss objective function of the power grid, and output the network loss, which is called by pso.py.
    • Input: Power grid information
    • Output: Objective function

  • pso.py

    • Function: This file aims to perform particle swarm algorithm calculation on the power grid to obtain the optimal solution. It is the main function file that calls other files.
    • Input: Fault network information
    • Output: Feasible solution

  • satisfy_condition.py

    • Function: This file aims to impose some constraint conditions on the power grid, and constrain the power grid in terms of current, voltage and topology. It is called by pso.py.
    • Input: Power grid information
    • Output: Returns a boolean value

  • x_solution.py

    • Function: Calculates the initial population for the fault network and is called by pso.py.
    • Input: Power grid information
    • Output: Produces initial population

TLBO

  • island.py

    • Function: This file aims to recover the first phase of power grid restoration strategy, and divide the power grid into islands.
    • Input: Fault network information
    • Output: Power grid after the first phase of restoration

  • base_on_tulun.py

    • Function: This file aims to modify and improve an infeasible solution, and output a feasible solution which is called by pso.py.
    • Input: Infeasible solution
    • Output: A feasible solution

  • fitness.py

    • Function: This file aims to calculate the network loss objective function of the power grid, and output the network loss, which is called by pso.py.
    • Input: Power grid information
    • Output: Objective function

  • main.py

    • Function: This file aims to perform TLBO algorithm calculation on the power grid to obtain the optimal solution. It is the main function file that calls other files.
    • Input: Fault network information
    • Output: Feasible solution

  • satisfy_condition.py

    • Function: This file aims to impose some constraint conditions on the power grid, and constrain the power grid in terms of current, voltage and topology. It is called by pso.py.
    • Input: Power grid information
    • Output: Returns a boolean value

  • x_solution.py

    • Function: Calculates the initial population for the fault network and is called by pso.py.
    • Input: Power grid information
    • Output: Produces initial population

Experimental Results

Island division result at time period 13:00

Island division result at time period 19:00

Fault recovery scheme at time period 13:00

Fault recovery scheme at time period 19:00