Performance Recovery of Voltage Source Converters With Application to Grid-Connected Fuel Cell DGs

Raoufat, M. Ehsan; Khayatian, Alireza; Mojallal, Aslan

doi:10.1109/tsg.2016.2580945

Cited by 35 publications

(16 citation statements)

References 23 publications

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“…Based on the proposed formulation, optimal allocation and sizing of BES units for load variance minimization can be determined. Different types of DER like fuel cell [22] can be integrated and analyzed. Since the formulation provides capability of reshaping power at PCC, a resiliency-oriented or a market-oriented scheduling problem can be considered.…”

Section: Discussionmentioning

confidence: 99%

Battery energy storage scheduling for optimal load variance minimization

Zhang

Melin

Olama

et al. 2018

2018 IEEE Power &Amp; Energy Society Innovative Smart Grid Technologies Conference (ISGT)

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Generation portfolio can be significantly altered due to the deployment of distributed energy resources (DER) in distribution networks and the concept of microgrid. Generally, distribution networks can operate in a more resilient and economic fashion through proper coordination of DER. However, due to the partially uncontrollable and stochastic nature of some DER, the variance of net load of distribution systems increases, which raises the operational cost and complicates operation for transmission companies. This motivates peak shaving and valley filling using energy storage units deployed in distribution systems. This paper aims at theoretical formulation of optimal load variance minimization, where the infinity norm of net load is minimized. Then, the problem is reformulated equivalently as a linear program. A case study is performed with capacitylimited battery energy storage model and the simplified power flow model of a radial distribution network. The influence of capacity limit and deployment location are studied.

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Section: Discussionmentioning

confidence: 99%

Battery energy storage scheduling for optimal load variance minimization

Zhang

Melin

Olama

et al. 2018

2018 IEEE Power &Amp; Energy Society Innovative Smart Grid Technologies Conference (ISGT)

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show abstract

“…However, many authors have depicted the adoption of AC grid connection by the FCs. [52][53][54][55][56][57][58][59][60][61][62][63] The architecture of DC based grid tied FC is illustrated in Figure 5B and its related literature survey are cited by numerous researchers. [64][65][66][67][68] AC based grid connected FCs can be further classified into single phase 47,69,70 and three phase systems.…”

Section: Microgrid Technology and Connectionmentioning

confidence: 99%

Retracted

Choudhury

Khandelwal

2020

Int Trans Electr Energ Syst

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“Retraction: [Subhashree Choudhury, Nikhil Khandelwal. A critical survey of fuel cells applications to microgrid integration: Configurations, issues, potential solutions and opportunities. International Transactions on Electrical Energy System. 2020;e12512. (https://doi.org/10.1002/2050-7038.12512)] The above article from International Transactions on Electrical Energy Systems, published online on June 23, 2020 in Wiley Online Library (http://onlinelibrary.wiley.com), has been retracted by agreement between the authors, the journal Editor in Chief, Dr. Chongqing Kang and John Wiley & Sons Ltd. The retraction has been agreed due to unattributed reuse of figures and tables from the following article published in Journal of Cleaner Production, “Review of fuel cells to grid interface: Configurations, technical challenges and trends” by Mustafa İnci and Ömer Türksoy, Volume 213, 2019, pages 1353–1370.”

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“…= + (14) = × 1 × ( − ) + × 2 × ( − ) (15) where is the leaping step, is a random number such that 0 ≤ ≤ 1, and 1 , 2 ∈ [1,2]. The scaling constants 1 , 2 help to "accelerate" past and to effectively search around the optimum, rather than linearly approach them.…”

Section: B Modified Shuffled Frog Leaping Algorithmmentioning

confidence: 99%

Sequential optimal placement of distributed photovoltaics using downstream power index

Athari

Yang

Wang

2017

2017 North American Power Symposium (NAPS)

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The optimization of the size and location of Photovoltaic (PV) Distributed Generation (DG) is a method for reducing distribution networks loss, cutting costs for utilities, and integrating renewable energy into the power grid. However, this optimization problem is a difficult mixed continuous discrete problem that is difficult to solve efficiently. Herein, we propose a novel Sequential PVDG Placement algorithm which utilizes a Downstream Power Index (DPI) for PV allocation. We compare Sequential PVDG Placement results with those of Shuffled Frog Leaping Algorithm (SFLA), a memetic heuristic algorithm. Our algorithm demonstrates similar accuracy and drastically less computation time compared to SFLA. Given its high accuracy and low computation time, sequential PVDG allocation algorithm may be useful for rapid online power dispatch, long-term planning, and microgrid operations under high penetration of renewable sources.

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Performance Recovery of Voltage Source Converters With Application to Grid-Connected Fuel Cell DGs

Cited by 35 publications

References 23 publications

Battery energy storage scheduling for optimal load variance minimization

Battery energy storage scheduling for optimal load variance minimization

Retracted

Sequential optimal placement of distributed photovoltaics using downstream power index

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