Dynamic Stabilization of DC Microgrids Using ANN-Based Model Predictive Control

Akpolat, Alper Nabi; Habibi, Mohammad Reza; Baghaee, Hamid Reza; Dursun, Erkan; Kuzucuoğlu, Ahmet Emin; Yang, Yongheng; Dragičević, Tomislav; Blaabjerg, Frede

doi:10.1109/tec.2021.3118664

Cited by 35 publications

(10 citation statements)

References 44 publications

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“…MPC tries to produce proper output signals by predicting the states of the system and the future value of that. MPC can be deployed in different types of applications, e.g., energy management of an electrified powertrain to climate control [42], control of three-phase dual-active-bridge converters [43], control of drive systems [44], control of the energy storage systems [45], improvement of the cybersecurity of DC microgrids [46], and sensorless control of DC microgrids [47]. There are some types of MPC-based controllers, and based on the application, the proper type of MPC can be selected.…”

Section: Control Of Pe Applicationsmentioning

confidence: 99%

Power and Energy Applications Based on Quantum Computing: The Possible Potentials of Grover’s Algorithm

et al. 2022

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In quantum computing, calculations are achieved using quantum mechanics. Typically, two main phenomena of quantum mechanics (i.e., superposition and entanglement) allow quantum computing to solve some problems more efficiently than classical algorithms. The most well-known advantage of quantum computing is the speedup of some of the calculations, which have been performed before by classical applications. Scientists and engineers are attempting to use quantum computing in different fields of science, e.g., drug discovery, chemistry, computer science, etc. However, there are few attempts to use quantum computing in power and energy applications. This paper tries to highlight this gap by discussing one of the most famous quantum computing algorithms (i.e., Grover’s algorithm) and discussing the potential applications of this algorithm in power and energy systems, which can serve as one of the starting points for using Grover’s algorithm in power and energy systems.

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Section: Control Of Pe Applicationsmentioning

confidence: 99%

Power and Energy Applications Based on Quantum Computing: The Possible Potentials of Grover’s Algorithm

et al. 2022

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“…To overcome the limitations of linear controllers, a model predictive controller (MPC) was proposed in [24] to minimize the impact of pulse load on a DCMG. Using the same approach, the power balance in a DCMG was ensured in [25,26]. However, the application of these control mechanisms is limited due to the necessity for lengthy and pointless computations.…”

Section: Literature Reviewmentioning

confidence: 99%

Design of Robust Integral Terminal Sliding Mode Controllers with Exponential Reaching Laws for Solar PV and BESS-Based DC Microgrids with Uncertainties

2022

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In this paper, an integral terminal sliding mode controller (ITSMC) based on a modified exponential reaching law (MERL) is developed for providing large-signal DC-bus voltage stability while smoothing power flow in DC microgrids (DCMGs). It is worth mentioning that this control approach is not employed in DCMG applications yet to adjust the DC-bus voltage while preserving power balance. The proposed DCMG is made up of a solar photovoltaic (PV) unit, a battery energy storage system (BESS), and DC loads. A DC-DC boost converter (DDBC) and a bidirectional DC-DC converter (BDDC) are employed to connect the solar PV and BESS, respectively, with the DC-bus, which not only controls the output power of these units but also regulates the DC-bus voltage. First, a detailed dynamical model including external disturbances is developed for each component, i.e., the solar PV and BESS. Then, the proposed control approach is employed on these units to get their corresponding control signals. Afterward, the overall stability of each unit is ensured using the Lyapunov stability theory. Moreover, to ensure the robustness of the proposed controller, external disturbances are also bounded based on the value of user-defined constants. Finally, simulation results are used to evaluate the effectiveness of the proposed control approach in a variety of operational scenarios. Additionally, simulation results of the proposed control strategy are compared to those of existing controllers to demonstrate its superiority.

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“…ANN based MPC control scheme is used for the stabilization of DC microgrid and the results are compared with conventional cascaded-proportional-integral (PI)-trained ANN control for PV batterybased grid connected DC microgrids [6]. Distributed droop-controlled DC microgrid, Local power controller with economic power dispatch algorithm and voltage controller with average bus voltage observation algorithm are used to regulate bus voltage and power sharing [7].…”

Section: Introductionmentioning

confidence: 99%

DC Bus Voltage Control of Islanded Microgrid using Renewable Energy Based Distributed Generation

Fawad Azeem,

Hasan A. Zidan

2024

ARAM

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DC bus voltage control in DC islanded microgrids is essential for the power quality and reliability. There are various algorithms being used in the literature review to control the bus voltages of DC microgrids. However, most of the research works controlled the generation side that requires high performance devices such as super capacitors etc., On the other hand, battery storage systems are also being used to regulate the bus voltage. In this research work, a separate strategy was developed in which battery storage was implemented at the load side to maintain stability of DC bus voltage. The load management scheme is introduced in which during the voltage instability, the loads are cutoff from the main supply and local installed storage system feed the loads. A particle swarm optimization (PSO) technique was used to optimally decide for the load in watts to be operated. A DC microgrid hardware was designed to test the control algorithm. The loads are not connected to the main system until the power supply is stable again. The load management scheme not only reduces the cost of the system but also stabilizes the overall system with 60% charge available in the batteries using the proposed load management scheme. The results were achieved while performing experiments on developed DC Microgrid hardware.

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Dynamic Stabilization of DC Microgrids Using ANN-Based Model Predictive Control

Cited by 35 publications

References 44 publications

Power and Energy Applications Based on Quantum Computing: The Possible Potentials of Grover’s Algorithm

Power and Energy Applications Based on Quantum Computing: The Possible Potentials of Grover’s Algorithm

Design of Robust Integral Terminal Sliding Mode Controllers with Exponential Reaching Laws for Solar PV and BESS-Based DC Microgrids with Uncertainties

DC Bus Voltage Control of Islanded Microgrid using Renewable Energy Based Distributed Generation

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