This study proposes, a swarm intelligence memorybased new multi-objectivedragonfly (MMOD) algorithm. Analyze to optimize active power loss, total investment on reactive power sources and total voltage variations in ...
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This study proposes, a swarm intelligence memorybased new multi-objectivedragonfly (MMOD) algorithm. Analyze to optimize active power loss, total investment on reactive power sources and total voltage variations in distribution systems. MMOD algorithm is implemented for a number of cycles repeatedly and in each cycle dragonflies are made to memorize available Pareto-optimal solutions. The memorized Pareto-optimal solutions are used as initial solutions and only the remaining swarm is reinitialized. Usefulness of the MMODA algorithm is established by solving MORPD problem in the two cases. Cases are standard IEEE-30 bus test system and another IEEE-69 bus radial distribution systems integrated with DGs and RPS units system. Comparing MORPD results for IEEE 33 bus are more suitable for Power loss 11.42986 kW, voltage profile 0.094375pu and reactive power capacity $599.8718k with respective other algorithm like NSGA-II, MODE, MODA, and MDE algorithm. Similarly for IEEE-69 bus radial distribution system found Power loss minimum 4.3964 kW, voltage profile 0.05474pu reactive power capacity $553.061k.
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