Algorithm: Cuckoo Search for Demand Side Management Input: Number of nests N, Discovery rate Pa, Max generations Genmax Output: Principal Cuckoo Nest Position for Peak Load Reduction 1: Initialize nests Xi randomly for i = 1 to N 2: Evaluate the fitness of each nest 3: while (gen < Genmax) do 4: Get a cuckoo (i.e., solution) randomly by Lévy flights 5: Choose a nest j randomly and evaluate its fitness 6: if (fitness (Xi) > fitness (Xj)) then 7: Replace j with the new solution Xi 8: end if 9: Abandon a fraction Pa of worse nests and build new ones 10: Keep the best solutions (nests) and perform local searches 11: Rank the nests and find the current best 12: gen = gen + 1 13: end while 14: Output the best nest which is the DSM schedule

Authors

• Person: Not available Organization: PLOS ONE
  Demand side management using optimization strategies for efficient ...

Sources

• Demand side management using optimization strategies for efficient ... journals.plos.org PLOS ONE via serper

Referenced by nodes (1)

• Cuckoo Search concept