An Improved Strategy for Distributed Generation Control and Power Sharing in Islanded Microgrid

Mahajan, Tejswini; Potdar, M. S.

doi:10.1109/icimia48430.2020.9074930

Cited by 4 publications

(2 citation statements)

References 9 publications

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“…The microgrid has two forms: AC and DC. Unlike the AC microgrid, the DC microgrid provides a number of advantages, such as high efficiency [5], ease of control [6], versatility [7], and reliability [8,9]. Furthermore, in a DC microgrid, there are no issues with reactive power flow, quality, or frequency [10].…”

Section: Introductionmentioning

confidence: 99%

Twin-Delayed Deep Deterministic Policy Gradient Algorithm to Control a Boost Converter in a DC Microgrid

Muktiadji,

Ramli,

Milyani

2024

Electronics

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A stable output voltage of a boost converter is vital for the appropriate functioning of connected devices and loads in a DC microgrid. Variations in load demands and source uncertainties can damage equipment and disrupt operations. In this study, a modified twin-delayed deep deterministic policy gradient (TD3) algorithm is proposed to regulate the output voltage of a boost converter in a DC microgrid. TD3 optimizes PI controller gains, which ensure system stability by employing a non-negative, fully connected layer. To achieve optimal gains, multi-deep reinforcement learning agents are trained. The agents utilize the error signal to obtain the desired output voltage. Furthermore, a new reward function used in the TD3 algorithm is introduced. The proposed controller is tested under load variations and input voltage uncertainties. Simulation and experimental results demonstrate that TD3 outperforms PSO, GA, and the conventional PI. TD3 exhibits less steady-state error, reduced overshoots, fast response times, fast recovery times, and a small voltage deviation. These findings confirm TD3’s superiority and its potential application in DC microgrid voltage control. It can be used by engineers and researchers to design DC microgrids.

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Section: Introductionmentioning

confidence: 99%

Twin-Delayed Deep Deterministic Policy Gradient Algorithm to Control a Boost Converter in a DC Microgrid

Muktiadji,

Ramli,

Milyani

2024

Electronics

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“…These microgrids can be implemented in the form of AC and DC microgrid coupled with power converter. The intensive use of DC-based renewable energy and electronic DC loads (e.g., electric vehicle and data center) have made DC microgrids option more efficient (Mahajan and Potdar, 2020). The DC microgrid has several benefits such as improved reliability, high efficiency with less energy conversion, high controllability without synchronization problem, and economics (Saveen et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Control of Boost Converter Using Observer-Based Backstepping Sliding Mode Control for DC Microgrid

et al. 2022

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The output voltage of a photovoltaic (PV) system relies on temperature and solar irradiance; therefore, the PV system and a load cannot be connected directly. To control the output voltage, a DC-DC boost converter is required. However, regulating this converter is a very complicated problem due to its non-linear time-variant and non-minimum phase circuit. Furthermore, the problem becomes more challenging due to uncertainty about the output voltage of the PV system and variation in the load, which is a non-linear disturbance. In this study, an observer-based backstepping sliding mode control (OBSMC) is proposed to regulate the output voltage of a DC-DC boost converter. The input voltage of the converter can be a DC energy source such as PV-based microgrid systems. An adaptive scheme and sliding mode controller constructed from a dynamic model of the converter is used to design an observer. This observer estimates unmeasured system states such as inductor current, capacitor voltage, uncertainty output voltages of the PV cell, and variation of loads such that the system does not need any sensors. In addition, the backstepping technique has been combined with the SMC to make the controller more stable and robust. In addition, the Lyapunov direct method is employed to ensure the stability of the proposed method. By employing the proposed configuration, the control performance was improved. To verify the effectiveness of the proposed controller, a numerical simulation was conducted. The simulation results show that the proposed method is always able to accurately follow the desired voltage with more robustness, fewer steady-state errors, smaller overshoot, faster recovery time, and faster transient response time. In addition, the proposed method consistently produces the least value of integral absolute error.

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Analysis of voltage profile in microgrids isolated by the insertion of non-conventional generation plants

Benalcazar,

Catota,

Minaya

et al. 2023

2023 9th International Conference on Computer and Communication Engineering (ICCCE)

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An Improved Strategy for Distributed Generation Control and Power Sharing in Islanded Microgrid

Cited by 4 publications

References 9 publications

Twin-Delayed Deep Deterministic Policy Gradient Algorithm to Control a Boost Converter in a DC Microgrid

Twin-Delayed Deep Deterministic Policy Gradient Algorithm to Control a Boost Converter in a DC Microgrid

Control of Boost Converter Using Observer-Based Backstepping Sliding Mode Control for DC Microgrid

Analysis of voltage profile in microgrids isolated by the insertion of non-conventional generation plants

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