Adaptive droop control using adaptive virtual impedance for microgrids with variable PV outputs and load demands
- Authors: Li, Zilin , Chan, Ka , Hu, Jiefeng , Guerrero, Josep
- Date: 2021
- Type: Text , Journal article
- Relation: IEEE Transactions on Industrial Electronics Vol. 68, no. 10 (2021), p. 9630-9640
- Full Text: false
- Reviewed:
- Description: In microgrids, intermittency of renewable energy sources (RES) and uncertain state-of-charge (SoC) of energy storage systems (ESS) can cause power deficiency to some distributed generation units (DGs). In this case, DGs with power deficiency may not meet the power demand, resulting in voltage collapse or frequency divergence. Unfortunately, this is seldom considered in inverter control design in existing literature. Thus, in-depth investigation into the microgrid performance under renewable energy resource fluctuations and appropriate control methods are urgently needed. In this article, an adaptive droop and adaptive virtual impedance control strategy is proposed. Unlike conventional droop control where the droop coefficients are fixed by assuming the DGs can always meet the load demand, the droop coefficients here are adjusted according to actual solar PV power output. In this way, proper power sharing among DGs can be achieved under renewable energy variation. Furthermore, the impact of varying DG capacities on system stability is mathematically investigated. An adaptive virtual impedance is then incorporated into the adaptive droop method to deal with the system instability caused by renewable energy variations. The proposed strategy is analyzed theoretically and validated in MATLAB/Simulink simulation and laboratory experiments. The results demonstrate the advantages of the proposed method over conventional approaches under various scenarios. © 1982-2012 IEEE.
Model predictive control for microgrids : from power electronic converters to energy management
- Authors: Hu, Jiefeng , Guerrero, Josep , Islam, Syed
- Date: 2021
- Type: Text , Book
- Relation: IET Energy Engineering Series, Vol. 199
- Full Text: false
- Reviewed:
- Description: Microgrids have emerged as a promising solution for accommodating the integration of renewable energy resources. But the intermittency of renewable generation is posing challenges such as voltage/frequency fluctuations, and grid stability issues in grid-connected modes. Model predictive control (MPC) is a method for controlling a process while satisfying a set of constraints. It has been in use for chemical plants and in oil refineries since the 1980s, but in recent years has been deployed for power systems and electronics as well. This concise work for researchers, engineers and graduate students focuses on the use of MPC for distributed renewable power generation in microgrids. Fluctuating outputs from renewable energy sources and variable load demands are covered, as are control design concepts. The authors provide examples and case studies to validate the theory with both simulation and experimental results and review the shortcomings and future developments. Chapters treat power electronic converters and control; modelling and hierarchical control of microgrids; use of MPC for PV and wind power; voltage support; parallel PV-ESS microgrids; secondary restoration capability; and tertiary power flow optimization. © The Institution of Engineering and Technology 2021.
Model predictive control of microgrids – An overview
- Authors: Hu, Jiefeng , Shan, Yinghao , Guerrero, Josep , Ioinovici, Adrian , Chan, Ka , Rodriguez, Jose
- Date: 2021
- Type: Text , Journal article , Review
- Relation: Renewable and Sustainable Energy Reviews Vol. 136, no. (2021), p.
- Full Text: false
- Reviewed:
- Description: The development of microgrids is an advantageous option for integrating rapidly growing renewable energies. However, the stochastic nature of renewable energies and variable power demand have created many challenges like unstable voltage/frequency and complicated power management and interaction with the utility grid. Recently, predictive control with its fast transient response and flexibility to accommodate different constraints has presented huge potentials in microgrid applications. This paper provides a comprehensive review of model predictive control (MPC) in individual and interconnected microgrids, including both converter-level and grid-level control strategies applied to three layers of the hierarchical control architecture. This survey shows that MPC is at the beginning of the application in microgrids and that it emerges as a competitive alternative to conventional methods in voltage regulation, frequency control, power flow management and economic operation optimization. Also, some of the most important trends in MPC development have been highlighted and discussed as future perspectives. © 2020 Elsevier Ltd
- Description: This work was supported by School of Engineering, IT and Physical Sciences, Federation University Australia , under Project RGS20-5 .