Protection coordination for networked microgrids using single and dual setting overcurrent relays

Alam, Mahamad Nabab; Gokaraju, Ramakrishna; Chakrabarti, Saikat

doi:10.1049/iet-gtd.2019.0557

Cited by 35 publications

(12 citation statements)

References 38 publications

(48 reference statements)

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“…However, previous studies did not focus on the PV-based inverter. In [36,37], the same idea was implemented with different network reconfigurations for inverter-based MGs, but the reliability evaluation and stability improvement need to be carefully studied.…”

Section: Protection Challengesmentioning

confidence: 99%

Artificial Intelligence-Based Protection for Smart Grids

et al. 2022

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Lately, adequate protection strategies need to be developed when Microgrids (MGs) are connected to smart grids to prevent undesirable tripping. Conventional relay settings need to be adapted to changes in Distributed Generator (DG) penetrations or grid reconfigurations, which is a complicated task that can be solved efficiently using Artificial Intelligence (AI)-based protection. This paper compares and validates the difference between conventional protection (overcurrent and differential) strategies and a new strategy based on Artificial Neural Networks (ANNs), which have been shown as adequate protection, especially with reconfigurable smart grids. In addition, the limitations of the conventional protections are discussed. The AI protection is employed through the communication between all Protective Devices (PDs) in the grid, and a backup strategy that employs the communication among the PDs in the same line. This paper goes a step further to validate the protection strategies based on simulations using the MATLABTM platform and experimental results using a scaled grid. The AI-based protection method gave the best solution as it can be adapted for different grids with high accuracy and faster response than conventional protection, and without the need to change the protection settings. The scaled grid was designed for the smart grid to advocate the behavior of the protection strategies experimentally for both conventional and AI-based protections.

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Section: Protection Challengesmentioning

confidence: 99%

Artificial Intelligence-Based Protection for Smart Grids

et al. 2022

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“…Notably, not paying attention to this issue, which is not addressed in the most reviewed papers, can reduce the reliability of the system. Although papers such as [31][32][33][34] have suggested methods based on changes of OCRs settings or using separate setting groups, the specific point that exists is that system operators are usually reluctant to change the protection system settings.…”

Section: Introductionmentioning

confidence: 99%

A Resilience-Oriented Methodology for Transformation of the Distribution Networks into MicroGrid

Kia

Farzinfar

Amirahmadi

et al. 2022

International Transactions on Electrical Energy Systems

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Transformation of the distribution network, integrated with Distributed Energy Resources (DER), into a MicroGrid (MG) is an attractive approach in improving the reliability and resilience of the network. In this paper, by introducing the important and necessary aspects of the MG formation problem, an effective methodology for transformation of a distribution network into the MG is proposed. In the presented methodology, optimal allocation of DERs within MG is obtained by optimization of power losses and voltage stabilization along feeders. Moreover, the short-circuit constraints are also taken into account simultaneously while allocating DERs. The reason for the latter is that the integration of DERs alters the amplitude and direction of the short circuit current, which can cause the overall fault current to exceed the designed fault-level capability of the circuit breakers. This issue may put CBs at risk of failure and degrading MG resilience. In this regard, resilience-oriented evaluation of the MG formation, from the perspective of considering short circuit level and coordination of OCRs, is also performed. Another advantage of short circuit studies is devising complete and economic overcurrent-based protection plan for MG in both operating modes (grid-connected and islanded). It should be pointed out that adopting an appropriate control routine is a key element in the MG formation. Hence, a control strategy, based on Energy Storage System (ESS) utilization, is suggested in this paper. This feature, which is another contribution of the paper, will guarantee seamless transition to island mode and stable operation of the MG. The proposed formulation of the MG formation is solved using a modified multi-objective PSO and the Pareto-optimal set is obtained. However, since the optimal solutions are nondominated to each other, a Fuzzy Satisfaction Method (FSM) is utilized to find the optimal solution among the Pareto-set. Utilization of the proposed methodology leads to the successful transformation of the distribution network into a MG, which not only considers the load flow constraints but also preserves the optimal coordination of the protective relays and resilience of the MG. In addition, seamless transition and stable operation of the MG in island mode is achieved.

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“…In addition, the ability of a single microgrid to absorb renewable energy and its ability to cope with volatility still needs to be improved [14]. Multiple microgrids will be an effective means to solve this problem [15,16]. With the development of distributed energy, more and more microgrids are connected to the distribution system to form a Micro-Grid Community [17,18].…”

Section: Introductionmentioning

confidence: 99%

Bi-Level Energy Management Model of Grid-Connected Microgrid Community

Cao¹,

Dong²,

Ren³

et al. 2022

Energy Engineering

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As the proportion of renewable energy power generation continues to increase, the number of grid-connected microgrids is gradually increasing, and geographically adjacent microgrids can be interconnected to form a Micro-Grid Community (MGC). In order to reduce the operation and maintenance costs of a single micro grid and reduce the adverse effects caused by unnecessary energy interaction between the micro grid and the main grid while improving the overall economic benefits of the micro grid community, this paper proposes a bi-level energy management model with the optimization goal of maximizing the social welfare of the micro grid community and minimizing the total electricity cost of a single micro grid. The lower-level model optimizes the output of each equipment unit in the system and the exchange power between the system and the external grid with the goal of minimizing the operating cost of each microgrid. The upper-level model optimizes the goal of maximizing the social welfare of the microgrid. Taking a microgrid community with four microgrids as an example, the simulation analysis shows that the proposed optimization model is beneficial to reduce the operating cost of a single microgrid, improve the overall revenue of the microgrid community, and reduce the power interaction pressure on the main grid.

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Protection coordination for networked microgrids using single and dual setting overcurrent relays

Cited by 35 publications

References 38 publications

Artificial Intelligence-Based Protection for Smart Grids

Artificial Intelligence-Based Protection for Smart Grids

A Resilience-Oriented Methodology for Transformation of the Distribution Networks into MicroGrid

Bi-Level Energy Management Model of Grid-Connected Microgrid Community

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