Hierarchical Control and Economic Optimization of Microgrids Considering the Randomness of Power Generation and Load Demand

Yinghao Shan (), Liqian Ma and Xiangkai Yu
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Yinghao Shan: College of Information Science and Technology, Donghua University, Shanghai 201620, China
Liqian Ma: College of Information Science and Technology, Donghua University, Shanghai 201620, China
Xiangkai Yu: College of Information Science and Technology, Donghua University, Shanghai 201620, China

Energies, 2023, vol. 16, issue 14, 1-23

Abstract: Hierarchical control has emerged as the main method for controlling hybrid microgrids. This paper presents a model of a hybrid microgrid that comprises both AC and DC subgrids, followed by the design of a three-layered control method. An economic objective function is then constructed to account for the uncertainty of power generation and load demand, and the optimal power guidance value is determined using the particle swarm optimization algorithm. The optimized power output is subsequently used to guide the tertiary control in the microgrid, mitigating potential safety and stability issues. Finally, the performance of each control layer is compared under dynamic changes in AC and DC loads, as well as stochastic variations in power generation and load consumption. Simulation results demonstrate that the hybrid microgrid can function stably, ensuring reliable and cost-effective AC and DC bus voltage supply despite the randomness of power generation and load demand.

Keywords: hybrid microgrid; hierarchical control; optimal scheduling; stable power supply; tertiary control (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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