Optimum Energy Management in the Radial Distribution Network by Considering Multiple Microgrids, Uncertainties, and Resilience Index Using the Modified Harris Hawk Optimization Algorithm
Subject Areas : Power Engineering
Marzieh Poshtyafteh
1
,
Hassan Barati
2
,
Ali Darvish Falehi
3
1 - Department of Electrical Engineering, Dezful Branch, Islamic Azad University, Dezful, Iran
2 - Department of Electrical Engineering, Dezful Branch, Islamic Azad University, Dezful, Iran
3 - Department of Computer Engineering, Shadegan Branch, Islamic Azad University, Shadegan, Iran
Keywords: Multiple-microgrids, Uncertainties, Modified Harris Hawk optimization, Resilience, Reconfiguration,
Abstract :
This paper proposes optimal energy management for multiple microgrids (MMG) connected to a distribution network (DN), in which various objective functions including network cost, pollutant reduction and losses, and distribution network resilience are considered. Also, the effect of the placement of distributed generation sources and the distribution network's reconfiguration in the optimization process to reduce losses, increasing reliability and resilience are considered. Uncertainties are formulated using Information Gap Decision Theory (IGDT). The decision variables, including the location of resources and microgrids, installation capacity, power factor, and uncertainty radius, have been optimally determined using the Modified Harris Hawk Optimization algorithm (MHHO) and the CPLEX solver. In the MHHO algorithm, the rabbit energy parameter (E) changes dynamically with the behavior and value of the objective function. Finally, the proposed method on the IEEE 33-bus Radial Distribution System in the first stage in a 24-hour time horizon including three micro-grids with different renewable energy sources to determine the structure of the network due to the buses connecting micro-grids and scattered sources by the placement algorithm and in the next stage in time Different resilience indicators are investigated due to the disconnection of the distribution network with the upstream network. The simulation results show the MHHO algorithm's optimal performance in placing microgrids, distributed generation sources, and network reconfiguration to improve the optimal energy management and resilience index.
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