In order to improve the coordinated control effect of hierarchical power balance of new energy microgrid, this paper applies fuzzy control method to this system, and proposes a hierarchical control strategy based on event-triggered communication. Each DG is regarded as a proxy, and the continuous actual value of output is replaced by the state prediction value. Moreover, two different event trigger condition functions for frequency and voltage are designed based on Lyapunov method respectively. At the same time, each DG only communicates with its neighbor DG aperiodic at the event trigger time, and finally all DG are restored to the reference value provided by the virtual leader. Finally, this paper constructs a coordinated fuzzy control simulation system for hierarchical power balance of new energy microgrid. Combined with the simulation results, the method proposed in this paper is feasible.
DaneshvarM., Mohammadi-IvatlooB., ZareK. and AsadiS., Two-stage robust stochastic model scheduling for transactive energy based renewable microgrids, IEEE Transactions on Industrial Informatics16(11) (2020), 6857–6867.
2.
LinH., SunK., TanZ.H., LiuC., GuerreroJ.M. and VasquezJ.C., Adaptive protection combined with machine learning for microgrids, IET Generation, Transmission & Distribution13(6) (2019), 770–779.
3.
PippiaT., SijsJ. and De SchutterB., A single-level rule-based model predictive control approach for energy management of grid-connected microgrids, IEEE Transactions on Control Systems Technology28(6) (2019), 2364–2376.
4.
MardaniM.M., KhoobanM.H., MasoudianA. and DragičevićT., Model predictive control of DC–DC converters to mitigate the effects of pulsed power loads in naval DC microgrids, IEEE Transactions on Industrial Electronics66(7) (2018), 5676–5685.
5.
ZhaoY., LinZ., DingY., LiuY., SunL. and YanY., A model predictive control based generator start-up optimization strategy for restoration with microgrids as black-start resources, IEEE Transactions on Power Systems33(6) (2018), 7189–7203.
6.
UtkarshK., SrinivasanD., TrivediA., ZhangW. and ReindlT., Distributed model-predictive real-time optimal operation of a network of smart microgrids, IEEE Transactions on Smart Grid10(3) (2018), 2833–2845.
7.
ShuaiZ., PengY., GuerreroJ.M., LiY. and ShenZ.J., Transient response analysis of inverter-based microgrids under unbalanced conditions using a dynamic phasor model, IEEE Transactions on Industrial Electronics66(4) (2018), 2868–2879.
8.
ShanY., HuJ., LiuM., ZhuJ. and GuerreroJ.M., Model predictive voltage and power control of islanded PV-battery microgrids with washout-filter-based power sharing strategy, IEEE Transactions on Power Electronics35(2) (2019), 1227–1238.
9.
DuY. and LiF., Intelligent multi-microgrid energy management based on deep neural network and model-free reinforcement learning, IEEE Transactions on Smart Grid11(2) (2019), 1066–1076.
10.
ZhangX., WangB., ManandharU., GooiH.B. and FooG., A model predictive current controlled bidirectional three-level DC/DC converter for hybrid energy storage system in DC microgrids, IEEE Transactions on Power Electronics34(5) (2018), 4025–4030.
11.
KhanM.R.B., PasupuletiJ., Al-FattahJ. and TahmasebiM., Energy management system for PV-Battery microgrid based on model predictive control, Indonesian Journal of Electrical Engineering and Computer Science15(1) (2019), 20–25.
12.
AlaviS.A., MehranK., HaoY., RahimianA., MirsaeediH. and VahidinasabV., A distributed event-triggered control strategy for DC microgrids based on publish-subscribe model over industrial wireless sensor networks, IEEE Transactions on Smart Grid10(4) (2018), 4323–4337.
13.
AnandutaW., MaestreJ.M., Ocampo-MartinezC. and IshiiH., Resilient distributed model predictive control for energy management of interconnected microgrids, Optimal Control Applications and Methods41(1) (2020), 146–169.
14.
LiY., WangR. and YangZ., Optimal scheduling of isolated microgrids using automated reinforcement learning-based multi-period forecasting, IEEE Transactions on Sustainable Energy13(1) (2021), 159–169.
15.
VergaraP.P., ReyJ.M., LópezJ.C., RiderM.J., da SilvaL.C., ShakerH.R. and JørgensenB.N., A generalized model for the optimal operation of microgrids in grid-connected and islanded droop-based mode, IEEE Transactions on Smart Grid10(5) (2018), 5032–5045.
16.
LiuJ., CaoX., XuZ., GuanX., DongX. and WangC., Resilient operation of multi-energy industrial park based on integrated hydrogen-electricity-heat microgrids, International Journal of Hydrogen Energy46(57) (2021), 28855–28869.
17.
AlghamdiB. and CañizaresC.A., Frequency regulation in isolated microgrids through optimal droop gain and voltage control, IEEE Transactions on Smart Grid12(2) (2020), 988–998.
