Decentralized Virtual Impedance- Conventional Droop Control for Power Sharing for Inverter-Based Distributed Energy Resources of a Microgrid

Buraimoh, Elutunji; Aluko, Anuoluwapo; Oni, Oluwafemi E.; Davidson, Innocent E.

doi:10.3390/en15124439

Cited by 16 publications

(8 citation statements)

References 35 publications

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“…The virtual impedance method is defined as transient virtual impedance in [69]. The other solution for differential calculations ignores the dq-axis current differentiation, and the virtual impedance form becomes:…”

Section: Virtual Impedance Techniquementioning

confidence: 99%

Secondary-Frequency and Voltage-Regulation Control of Multi-Parallel Inverter Microgrid System

Dong

Gong²,

Bao³

et al. 2022

Energies

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As an important form of distributed renewable energy utilization and consumption, the multi-parallel inverter microgrid system works in both an isolated and grid-connected operation mode. Secondary-frequency and voltage-regulation control are very important in solving problems that appears in these systems, such as the distributed secondary-frequency regulation real-time scheme, voltage and reactive power balancing, and the secondary-frequency regulation control under the disturbances and unbalanced conditions of a microgrid system. This paper introduces key technologies related to these issues, such as the consensus algorithm and event-triggered technique, the dynamic and adaptive virtual impedance technique, and the robust and self-anti-disturbance control technique. Research and design methods such as small-signal state-space analysis, the Lyapunov function design method, the impedance analysis method, μ-synthesis design, and the LMI matrix design method are adopted to solve the issues in secondary-frequency regulation and voltage regulation. As the number of inverters increases, the structure of the microgrid becomes more and more complex. Suggestions and prospects for future research are provided to realize control with low-communication technology and a distributed scheme. Finally, for the case study, the droop-control model and primary frequency/voltage deviation of a multi-parallel inverter microgrid system is analyzed, and a state-space model of a multi-parallel inverter microgrid system with a droop-control loop is established. Then, the quantitative relationship between the primary frequency/voltage deviation and the active and reactive power output in the system is discussed. The methods and problems of centralized and decentralized secondary-frequency regulation methods, secondary-frequency regulation methods based on a consensus algorithm and an event-triggered mechanism, reactive power and voltage equalization, power distribution, and small-signal stability of the multiple parallel inverter microgrid system regarding the virtual impedance loop are analyzed.

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Section: Virtual Impedance Techniquementioning

confidence: 99%

Secondary-Frequency and Voltage-Regulation Control of Multi-Parallel Inverter Microgrid System

Dong

Gong²,

Bao³

et al. 2022

Energies

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“…The rising popularity of small-scale energy production devices is anticipated to enhance global power capacity and facilitate the integration of renewable energy sources into the existing system. Microgrids offer a viable solution for addressing the challenges of integrating renewable energy sources by establishing a localized electric grid incorporating distributed energy generating and energy storage devices [22]. Various countries are currently engaged in the research and development of microgrids that rely on renewable energy sources.…”

Section: Introductionmentioning

confidence: 99%

Design and implementation of Hybrid Renewable energy (PV/Wind/Diesel/Battery) Microgrids for rural areas.

M G Almihat,

MTE Kahn

2023

jsesd

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This study examines the variation in sensitivity of a microgrid system comprised of photovoltaics, wind turbines, diesel engines, and batteries. The primary objective is to increase our knowledge of renewable energy resources (RERs) and their technical and economic factors in the context of the conceptual design of a microgrid system. The investigation employs Typhoon HIL software for simulation and testing, concentrating on hybrid PV/Wind/Diesel/Battery systems and devising a perturb & observe (P&O) maximum power point tracking (MPPT) strategy. Additionally, the study investigates the Optimal Power Controlling MPPT technique and the development and implementation of hybrid renewable energy resources (HRES). The Typhoon HIL system is utilized in the power, automotive, and aerospace industries, among others, to simulate and test control systems in real-time. This study presents a control strategy for a microgrid system that combines renewable energy sources such as solar and wind power with reserve power options such as diesel generators and batteries. The coordinated control technique is implemented by employing a centralized control method, effectively managing the flow of electricity from diverse distributed energy resources (DER) and ensuring the microgrid's stability. The findings indicated that the coordinated control method and dynamic models could be utilized to design and optimize microgrid systems. Future research can concentrate on refining the accuracy of the models and verifying the proposed coordinated control method in microgrid systems that operate in the real world.

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“…By assuming the role of both consumers and producers, they contribute to a decentralization of electrical energy production [3,4]. Although beneficial for the environment, the integration of distributed energy resources into the electrical grid poses new challenges due to the variability of endogenous resources and the changes to the paradigm for which distribution networks were designed (i.e., distributing energy from upstream to downstream) [5]. Currently, one of the most popular solutions to this problem is Renewable Energy Communities (RECs) [6].…”

Section: Introductionmentioning

confidence: 99%

Optimal Sizing of Renewable Energy Communities: A Multiple Swarms Multi-Objective Particle Swarm Optimization Approach

Faria,

Marques,

Pombo

et al. 2023

Energies

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Renewable energy communities have gained popularity as a means of reducing carbon emissions and enhancing energy independence. However, determining the optimal sizing for each production and storage unit within these communities poses challenges due to conflicting objectives, such as minimizing costs while maximizing energy production. To address this issue, this paper employs a Multi-Objective Particle Swarm Optimization (MOPSO) algorithm with multiple swarms. This approach aims to foster a broader diversity of solutions while concurrently ensuring a good plurality of nondominant solutions that define a Pareto frontier. To evaluate the effectiveness and reliability of this approach, four case studies with different energy management strategies focused on real-world operations were evaluated, aiming to replicate the practical challenges encountered in actual renewable energy communities. The results demonstrate the effectiveness of the proposed approach in determining the optimal size of production and storage units within renewable energy communities, while simultaneously addressing multiple conflicting objectives, including economic viability and flexibility, specifically Levelized Cost of Energy (LCOE), Self-Consumption Ratio (SCR) and Self-Sufficiency Ratio (SSR). The findings also provide valuable insights that clarify which energy management strategies are most suitable for this type of community.

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Decentralized Virtual Impedance- Conventional Droop Control for Power Sharing for Inverter-Based Distributed Energy Resources of a Microgrid

Cited by 16 publications

References 35 publications

Secondary-Frequency and Voltage-Regulation Control of Multi-Parallel Inverter Microgrid System

Secondary-Frequency and Voltage-Regulation Control of Multi-Parallel Inverter Microgrid System

Design and implementation of Hybrid Renewable energy (PV/Wind/Diesel/Battery) Microgrids for rural areas.

Optimal Sizing of Renewable Energy Communities: A Multiple Swarms Multi-Objective Particle Swarm Optimization Approach

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