An overview of the operation architectures and energy management system for multiple microgrid clusters

Guan, Yajuan; Wei, Baoze; Guerrero, Josep M.; Vásquez, Juan C.; Gui, Yonghao

doi:10.23919/ien.2022.0035

Cited by 32 publications

(6 citation statements)

References 50 publications

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“…The microgrid system used can be developed with multiple microgrids. However, the appropriate requirements and aspects for multiple microgrids must be met before connecting to the grid [2]. ICESRE Previous research related to multiple microgrids is as follows.…”

Section: Introductionmentioning

confidence: 99%

Increased Load Power With Centralized Control of Multiple Microgrid Resources

Kusmantoro

2024

KSS

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There are many rural areas on remote islands that cannot be reached by electricity sources from the utility grid. However, Indonesia is a country that has an abundant supply of renewable energy. One of the renewable energies that is obtained for free is solar energy sources. Renewable energy has great potential as a source of distributed electricity generation or microgrids. This article proposes a new method for providing large electrical power supplies for rural areas, namely multiple microgrids with a centralized control strategy. The purpose of this method is to provide stability of power supply to the load. In this method, each microgrid has solar panels (SP), batteries, and diesel generators (GD). Multiple microgrids provide power supply to DC loads and AC loads. The centralized controller uses an outseal programmable logic controller (PLC) which functions to regulate the power flow of microgrid 1 (MG1), microgrid 2 (MG2), and microgrid 3 (MG3) to the load alternately. Simulation test results show the performance of a centralized control which is able to provide power supply to the load according to demand or changes in load. Power regulation management for rural areas can be developed for large-scale microgrid systems. Keywords: multiple-microgrid; centralized control; solar panel

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Section: Introductionmentioning

confidence: 99%

Increased Load Power With Centralized Control of Multiple Microgrid Resources

Kusmantoro

2024

KSS

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“…These fault currents fluctuations can adversely impact the protection system's fundamental aspects, including sensitivity, selectivity, reliability, and response speed. Moreover, various layers of protection must be explored within a multi-microgrid system, including converter-and circuit-breaker-based safeguards [21]. Furthermore, ensuring the effectiveness of protection measures across various operational scenarios, including radial and mesh configurations and grid-connected and islanded modes of microgrids, is essential.…”

Section: Introductionmentioning

confidence: 99%

Hardware Implementation of a Resilient Energy Management System for Networked Microgrids

Hussein,

Rafin,

Abdelrahman

et al. 2024

WEVJ

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A networked microgrid is composed of multiple nearby microgrids linked together to gain additional flexibility for resilient operations. Networked microgrids collaborate to prevent power shortages in microgrid clusters by sharing critical renewable and energy storage resources. However, controlling the local resources of each microgrid, including the energy storage systems’ charging and discharging, maintaining the DC bus voltage, and even overseeing the power shared by multiple microgrids, is challenging. Therefore, a microgrid control technique and distributed energy management are used cooperatively in this study to handle the shared power between a system of networked microgrids incorporating photovoltaics and battery energy storage systems. Numerical simulation results from a networked microgrid system verify the accuracy and soundness of the suggested distributed energy management under several operating conditions, including renewable uncertainties and sequential load variations in different zones. The applicability of the suggested technique is confirmed by hardware implementation, and several operational scenarios further evaluate the proposed system on a practical two-microgrid system located in the Florida International University (FIU) testbed.

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“…In order to improve the penetration rate of renewable energy in the distribution grid and optimize the energy structure, multiple photovoltaic (PV) microgrids can be connected to the distribution 10. 3389/fenrg.2023.1297650 grid to become backup energy (Hui et al, 2022;Guan et al, 2022;Liao et al, 2023). Price-based and incentive-based differentiated demand responses are further employed to coordinate the interaction between the distribution grid and PV microgrid and improve the balance between energy generation and consumption.…”

Section: Introductionmentioning

confidence: 99%

Hybrid bilevel optimization-based interaction between the distribution grid and PV microgrids with differentiated demand response

Shao,

Liu,

Yao

et al. 2023

Front. Energy Res.

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Demand response plays an important role in improving the balance of power generation and consumption between the distribution grid and photovoltaic (PV) microgrids. However, due to the uncertainty and volatility of PV output, as well as the different operation goals of PV microgrids, a conventional single-tier optimization approach is infeasible to realize the coordinated interaction between the distribution grid and PV microgrids. To address these challenges, we propose a second-order cone and improved consensus algorithm-based hybrid bilevel optimization algorithm for the interaction between the distribution grid and PV microgrids. First, we construct price-based and incentive-based differentiated demand response models to deal with various supply and demand dynamics of the distribution grid and PV microgrids. Building upon this foundation, we construct a hybrid bilevel optimization model. In the lower level, distributed optimization is adopted, and an improved consensus algorithm is used to optimize power output of PV microgrids to maximize the revenue based on output power of upper-level generator sets. In the upper level, centralized optimization is adopted, and second-order cone programming is employed to minimize the grid loss in the distribution grid based on the power output of lower-level PV microgrids. Hybrid bilevel optimization is iterated until the convergence condition is satisfied. Simulation results verify the proposed algorithm for achieving a coordinated interaction between the distribution grid and PV microgrids.

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An overview of the operation architectures and energy management system for multiple microgrid clusters

Cited by 32 publications

References 50 publications

Increased Load Power With Centralized Control of Multiple Microgrid Resources

Increased Load Power With Centralized Control of Multiple Microgrid Resources

Hardware Implementation of a Resilient Energy Management System for Networked Microgrids

Hybrid bilevel optimization-based interaction between the distribution grid and PV microgrids with differentiated demand response

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