Smart Microgrid Energy Management Using a Novel Artificial Shark Optimization

Algorithm 1

Initialize the whole Shark population

Random initialization of the positions of each Shark

   while (iter < maximum number of iterations max_iter)

      for each Shark

      Calculate the objective function value of every Shark

      Select the local best position & objective function value of every Shark

      Select the universal best position and objective function value of Sharks

      Update the value of tp

         Iftp <= threshold probability of finding pray

           Speed of a shark is updated by using equation (6)

           Position of a Shark is updated by using equation (7)

         else  Position of a Shark is updated by using equation (9)

         end if

      Check the new position of Shark is within its limit

      Evaluate the direction of the speed of a Shark

      end for

   iter = iter + 1

   end while

return universal best Shark.