Abstract
In this paper, the load frequency control (LFC) for networked microgrids in the presence of delayed electric vehicles (EVs) aggregator and renewable energy sources (RESs) like photovoltaic, wind turbine and fuel cell have been investigated. A linear active disturbance rejection control (LADRC) technique based on the extended state observer (ESO) and nonlinear feedback control law (NLFCL) is proposed to eliminate the frequency variations resulted from the load disturbance and uncertainty of RESs. Since the LADRC parameters could be designed by the ESO and controller bandwidths, the presented controller could have similar performance with the fixed-structured controller. Also, the IMC technique is used for the robust tuning of the LADRC controller. The simulation is carried out on the three-area LFC scheme containing EVs aggregator, RESs, and fuel cell. According to simulation results, the LADRC controller has fewer frequency variations in contrast to other methods presented in the case studies.
Similar content being viewed by others
Availability of data and material
Not applicable.
Code availability
Not applicable.
Abbreviations
- EV:
-
Electric vehicles
- ESO:
-
Extended state observer
- ESS:
-
Energy storage system
- FC:
-
Fuel cell
- IAE:
-
Integral absolute error
- ITAE:
-
Integral time absolute error
- LADRC:
-
Linear active disturbance rejection control
- LFC:
-
Load frequency control
- MPC:
-
Model predictive control
- NMGs:
-
Networked microgrids
- NLFCL:
-
Nonlinear feedback control law
- PV:
-
Photovoltaic panel
- RESs:
-
Renewable energy sources
- SMC:
-
Sliding mode control
- WT:
-
Wind turbine
- K EV :
-
EV Battery gain
- K WT :
-
Wind turbine gain
- K PV :
-
Photovoltaic panel gain
- K ESS :
-
Energy storage system gain
- K FC :
-
Fuel cell gain
- K b :
-
Frequency bias factor
- F p :
-
Fraction of total turbine power
- T FC :
-
Fuel cell time constant
- \({\omega }_{o}\) :
-
Observer bandwidth
- M :
-
Inertia constant
- D :
-
Load-damping factor
- R :
-
Speed regulation
- T g :
-
Governor time constant
- T c :
-
Turbine time constant
- T r :
-
Reheat time constant
- T EV :
-
EV Battery time constant
- T WT :
-
Wind turbine time constant
- T PV :
-
Photovoltaic panel time constant
- T ESS :
-
Energy storage system time constant
- \({\Delta P}_{FC}\) :
-
Fuel cell power variation
- \(\Delta f\) :
-
Frequency variation
- \({\Delta P}_{g}\) :
-
Generator output power variation
- \({\Delta P}_{ESS}\) :
-
Energy storage system power variation
- \({\Delta P}_{PV}\) :
-
Photovoltaic power variation
- \({\Delta P}_{WT}\) :
-
Wind power variation
- \({\Delta P}_{m}\) :
-
Mechanical output power variation
- \({\Delta P}_{EV}\) :
-
EV aggregator power variation
- b :
-
High-frequency gain of controlled system
- d :
-
Total disturbance
- u :
-
Input signal
- L o :
-
Observer gain vector
- K o :
-
Controller gain
- \({\omega }_{c}\) :
-
Controller bandwidth
References
Safari, A., Babaei, F., Farrokhifar, M.: A load frequency control using a PSO-based ANN for micro-grids in the presence of electric vehicles. Int. J. Ambient Energy 42, 688–700 (2021)
Bevrani, H., Habibi, F., Babahajyani, P., Watanabe, M., Mitani, Y.: Intelligent frequency control in an AC microgrid: online PSO-based fuzzy tuning approach. IEEE Trans. Smart Grid 3, 1935–1944 (2012)
Sahu, R.K., Panda, S., Biswal, A., Sekhar, G.C.: Design and analysis of tilt integral derivative controller with filter for load frequency control of multi-area interconnected power systems. ISA Trans. 61, 251–264 (2016)
Dhillon, S.S., Lather, J.S., Marwaha, S.: Multi objective load frequency control using hybrid bacterial foraging and particle swarm optimized PI controller. Int. J. Electr. Power 79, 196–209 (2016)
Khooban, M.H., Niknam, T., Shasadeghi, M., Dragicevic, T., Blaabjerg, F.: Load frequency control in microgrids based on a stochastic noninteger controller. IEEE Trans. Sustain. Energy 9, 853–861 (2017)
Saha, A., Saikia, L.C.: Utilisation of ultra-capacitor in load frequency control under restructured STPP-thermal power systems using WOA optimised PIDN-FOPD controller. IET Gener. Transm. Distrib. 11, 3318–3331 (2017)
Aziz, S., Wang, H., Liu, Y., Peng, J., Jiang, H.: Variable universe fuzzy logic-based hybrid LFC control with real-time implementation. IEEE Access 7, 25535–25546 (2019)
Chuang, N.: Robust H∞ load-frequency control in interconnected power systems. IET Control Theory Appl. 10, 67–75 (2016)
Peng, C., Zhang, J., Yan, H.: Adaptive event-triggering H∞ load frequency control for network-based power systems. IEEE Trans. Ind. Electron. 65, 1685–1694 (2017)
Bevrani, H., Feizi, M.R., Ataee, S.: Robust frequency control in an islanded microgrid: H∞ and μ-synthesis approaches. IEEE Trans. Smart Grid 7, 706–717 (2015)
Wen, S., Yu, X., Zeng, Z., Wang, J.: Event-triggering load frequency control for multiarea power systems with communication delays. IEEE Trans. Ind. Electron. 63, 1308–1317 (2015)
Mi, Y., Fu, Y., Li, D., Wang, C., Loh, P.C., Wang, P.: The sliding mode load frequency control for hybrid power system based on disturbance observer. Int. J. Electr. Power 74, 446–452 (2016)
Cui, Y., Xu, L., Fei, M., Shen, Y.: Observer based robust integral sliding mode load frequency control for wind power systems. Control Eng. Pract. 65, 1–10 (2017)
Liao, K., Xu, Y.: A robust load frequency control scheme for power systems based on second-order sliding mode and extended disturbance observer. IEEE Trans Ind. Inform. 14, 3076–3086 (2017)
Sarkar, M.K., Dev, A., Asthana, P., Narzary, D.: Chattering free robust adaptive integral higher order sliding mode control for load frequency problems in multi-area power systems. IET Control Theory Appl. 12, 1216–1227 (2018)
Li, H., Wang, X., Xiao, J.: Adaptive event-triggered load frequency control for interconnected microgrids by observer-based sliding mode control. IEEE Access 7, 68271–68280 (2019)
Torabi-Farsani, K., Asemani, M.H., Badfar, F., Vafamand, N., Khooban, M.H.: Robust mixed μ-synthesis frequency regulation in AC mobile power grids. IEEE Trans. Transp. Electr. 5, 1182–1189 (2019)
Banis, F., Guericke, D., Madsen, H., Poulsen, N.K.: Load–frequency control in microgrids using target-adjusted MPC. IET Renew. Power Gener. 14, 118–124 (2019)
Dahab, Y.A., Abubakr, H., Mohamed, T.H.: Adaptive load frequency control of power systems using electro-search optimization supported by the balloon effect. IEEE Access. 8, 7408–7422 (2020)
Babaei, F., Safari, A.: SCA based fractional-order PID controller considering delayed EV aggregators. JOAPE 8, 75–85 (2020)
Khooban, M.H., Niknam, T., Blaabjerg, F., Davari, P., Dragicevic, T.: A robust adaptive load frequency control for micro-grids. ISA Trans. 65, 220–229 (2017)
Babaei, F., Safari, A., Salehi, J.: Evaluation of delays-based stability of LFC systems in the presence of electric vehicles aggregator. J Oper Autom Power Eng 10, 165–174 (2021)
Babaei, F., Lashkari, Z.B., Safari, A., Farrokhifar, M., Saleh, J.: SSA based fractional-order PID controller for LFC systems in the presence of delayed EV aggregators. IET Electr. Syst. 10, 259–267 (2020)
Chen, W., Tan, W.: Load frequency control for power systems with wind turbines. In: Proceedings of the 33rd Chinese Control Conference, Nanjing, pp. 4277–4282 (2014)
Annamraju, A., Nandiraju, S.: Robust frequency control in an autonomous microgrid: a two-stage adaptive fuzzy approach. Electr. Power Compon. Syst. 46, 83–94 (2018)
Safari, A., Shahsavari, H., Babaei, F.: Optimal design of controllers for power network connected sofc using of multi-objective PSO. Serb. J. Electr. Eng. 15, 145–163 (2018)
Chen, S., Chen, Z.: On active disturbance rejection control for a class of uncertain systems with measurement uncertainty. IEEE Trans. Ind. Electron. 68, 1475–1485 (2020)
Tan, W., Xu, J.: Damping of low-frequency oscillations via active disturbance rejection control. Electr. Power Compon. Syst. 49, 233–245 (2021)
Garpinger, O., Hägglund, T., Åström, K.J.: Performance and robustness trade-offs in PID control. J. Process Control 24, 568–577 (2014)
Fu, C., Tan, W.: Decentralised load frequency control for power systems with communication delays via active disturbance rejection. IET Gener. Transm. Distrib. 12(6), 1397–1403 (2018)
Ali, H.H., Kassem, A.M., Al-Dhaifallah, M., Fathy, A.: Multi-verse optimizer for model predictive load frequency control of hybrid multi-interconnected plants comprising renewable energy. IEEE Access 8, 114623–114642 (2020)
Funding
Not applicable.
Author information
Authors and Affiliations
Contributions
FB: methodology, software, formal analysis, validation, writing—original draft preparation; NT: validation, writing—review and editing, supervision, formal analysis; AS: validation, writing—review and editing, supervision, formal analysis.
Corresponding author
Ethics declarations
Conflict of interest
Not applicable.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Appendix
Appendix
See Table 3.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Taghizadegan, N., Babaei, F. & Safari, A. A linear active disturbance rejection control technique for frequency control of networked microgrids. Energy Syst 15, 807–826 (2024). https://doi.org/10.1007/s12667-023-00563-6
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12667-023-00563-6