Adaptive backstepping control for master-slave AC microgrid in smart island

Dehghani, Moslem; Niknam, Taher; Ghiasi, Mohammad; Baghaee, Hamid Reza; Blaabjerg, Frede; Dragičević, Tomislav; Rashidi, Mohammadrashid

doi:10.1016/j.energy.2022.123282

Cited by 24 publications

(9 citation statements)

References 51 publications

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“…Each group of gorillas has its leader (silverback gorilla) that can make decisions and drive them to food sources. The Equation (7) mathematically models this behaviour [34].…”

Section: Exploitation Phasementioning

confidence: 99%

“…This approach requires high-speed communication and controlled skilled links, otherwise, the whole microgrid system will collapse. Moreover, control communication links increase the system's challenges by raising its overall cost [7]. On the other hand, the main advantage of the decentralized control technique is that has more intelligent separate controllers located at the DG units [8].…”

Section: Introductionmentioning

confidence: 99%

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Real‐time implementation and evaluation of gorilla troops optimization‐based control strategy for autonomous microgrids

Maged

Hasanien

Ebrahim

et al. 2022

IET Renewable Power Gen

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The present work develops a novel gorilla troops optimization algorithm (GTO) for optimal control of an autonomous microgrid. The proposed proportional-integral controller parameters are properly designed by the GTO algorithm. It is based on the integral squared error to minimize the system objective function. The suggested islanded microgrid system operates with several decentralized, electronically interfaced energy resources and their local loads. The new optimal controller is applied to regulate its voltage at the different points of common coupling and its frequency despite the load variation. The performance of the new proposal is compared with the PI controller that was designed by a particle swarm optimization algorithm. It is observed that the microgrid functioning operation is improved even more by applying a GTO-based than the other. The control strategy is thoroughly tested using a Matlab/Simulink simpower-system environment under various microgrid operating situations. It is also implemented with OPAL 4510 real-time hardware in the loop and a rapid control prototyping module. The different benchmark experiments serve to show the superiority of the new optimizer.

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“…Each group of gorillas has its leader (silverback gorilla) that can make decisions and drive them to food sources. The Equation (7) mathematically models this behaviour [34].…”

Section: Exploitation Phasementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Real‐time implementation and evaluation of gorilla troops optimization‐based control strategy for autonomous microgrids

Maged

Hasanien

Ebrahim

et al. 2022

IET Renewable Power Gen

View full text Add to dashboard Cite

show abstract

“…In [18] a hierarchical decentralized System of Systems (SoS) architecture for the energy management of a multi-microgrid system is proposed and, accordingly, it is formulated as a bi-level optimization problem. In [19] the authors have proposed an adaptive backstepping controller to stabilize voltage and frequency in a smart grid and also to control current to share power between renewable energy resources in a smart island. Reference [20] has proposed an energy management strategy based on a novel bi-level stochastic multiobjective optimization model to maximize the utility of the consumed power, simultaneously with the cost minimization.…”

Section: 𝑔 𝑖mentioning

confidence: 99%

Transmission and Distribution Substation Energy Management Considering Large-Scale Energy Storage, Demand Side Management and Security-Constrained Unit Commitment

et al. 2022

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In this paper, a bi-level optimization model including the problem of transmission network market and energy management in the distribution substation is presented. In the proposed bi-level model, the lower-level includes the demand-side management (DSM) program and the optimal charge/discharge of large-scale energy storage system (LSESS) at distribution substations to increase grid profits and send decisions to the upper-level transmission market operator. The upper level of the proposed model is a security-constrained unit commitment (SCUC) to minimize production, no-load, startup, shutdown, and active power curtailment costs, and also the unavailability of the generation units. In this paper, to solve the bi-level optimization problem, the Karush-Kuhn-Tucker (KKT) equation modeling method will be used to turn the problem into a single-level problem. One of the advantages of converting a bi-level model to a single-level model compared to the methods of the decomposition algorithms is the lack of use of iterative algorithms, which leads to an increase in problem-solving time. The proposed model is tested on standard distribution substations and transmission networks, which shows that the proposed method is more effective than decomposition algorithms in terms of problem solving time. The simulation results showed that the proposed method can be more efficient in large optimization problems.

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“…Since any estimation mechanism to construct the state vector form the measured output vector is not given in those approaches, their developed controllers necessitate measuring all states. In [20], a model reference adaptive backstepping controller is suggested for voltage mode control of AC MGs. A two-state power system is considered and a state observer is presented.…”

Section: Introductionmentioning

confidence: 99%

Advanced Kalman Filter-Based Backstepping Control of AC Microgrids: A Command Filter Approach

Vafamand

Arefi

Anvari‐Moghaddam

2023

IEEE Systems Journal

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The stability of alternating current microgrids (AC MGs) is significantly affected by the procedure of collecting precise and sufficient information of the system and tightly controlling power inverters. Whereas using many sensors increases AC MG ripples and cost, integrating cost-effective and low number of sensors is preferred. Further, assuring the stability and tracking issue of AC MGs in different operating modes and in the presence of unknown time-varying loads is a hard task. Aiming at these issues, this paper proposes an improved augmented-Kalman filter to estimate the state vector and disturbance inputs and a nonlinear backstepping controller with a command filter to design the control law. Compared to the conventional Kalman filters, the developed approach is able to estimate the external disturbances, which improves the state estimation performance and provides extra information about the power system. The proposed command filter-based backstepping has the key feature of avoiding the calculation of time-derivatives of desired references of virtual inputs, which is a common drawback of conventional approaches. Whereas the dynamics of the disturbance time-varying load are not available, the command filter is utilized to avoid the time derivatives terms of the disturbance inputs. Simulation results illustrate the estimation performance of the augmented Kalman filter and the tracking performance of the command filter-based backstepping controller.

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Adaptive backstepping control for master-slave AC microgrid in smart island

Cited by 24 publications

References 51 publications

Real‐time implementation and evaluation of gorilla troops optimization‐based control strategy for autonomous microgrids

Real‐time implementation and evaluation of gorilla troops optimization‐based control strategy for autonomous microgrids

Transmission and Distribution Substation Energy Management Considering Large-Scale Energy Storage, Demand Side Management and Security-Constrained Unit Commitment

Advanced Kalman Filter-Based Backstepping Control of AC Microgrids: A Command Filter Approach

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