Economic Dispatch of Microgrid Incorporating Demand Response using Dragonfly Algorithm

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Economic dispatch has significant importance in power system operation and control. This research presents a novel technique, the dragonfly algorithm (DA), for solving the economic dispatch (ED) problem by incorporating the demand response (DR) model. This work incorporates an incentive-based demand response model into a grid-connected microgrid, including renewable energy sources (solar photovoltaic and wind power) and conventional generators (diesel).
The objective of the presented economic dispatch is to get minimum fuel cost, minimum transferable power cost, and maximum demand response benefit for microgrid operators. The proposed DR model and DA algorithm are verified with the help of case studies. To test the validity of the proposed algorithm, the cases are first solved by particle swarm optimization (PSO), and then the results are compared with the dragonfly algorithm (DA).
Results have proved that the inclusion of the demand response model is adequate for optimal economic dispatch for consumers and the utility. Due to its improved exploration rate, DA has outperformed PSO in terms of finding the best cost for the objective function. Furthermore, the convergence rate of DA is found to be faster as compared to the PSO algorithm due to the high exploitation rate of DA.

Click here for particle swarm optimization Matlab code example and interested to learn more about IEEE 69 bus system data.


14 thoughts on “Economic Dispatch of Microgrid Incorporating Demand Response using Dragonfly Algorithm”

  1. Sir, your videos are a great help for a new beginner in this field. Can you send me the full code file? Extra related material of demand response programs related to microgrids would be a great help to understand better and implement new ideas.

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