Multi-objective optimal sizing of hybrid energy storage systems for grid-connected wind farms using fuzzy control

Du, Rui; Zou, Penghui; Ma, Chao

doi:10.1063/5.0031696

Cited by 9 publications

(2 citation statements)

References 38 publications

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“…A multi-objective mathematical model is established in [35] for optimizing the capacity of hybrid energy storage system for a grid-connected 99MW Caka wind farm in Qinghai Province, China, to maximize target satisfaction rate and minimize net present value. The only wind farm is considered with a storage system which is less efficient than multiple energy sources.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimal Sizing of Hybrid Microgrid in a Remote Island Considering Advanced Direct Load Control for Demand Response and Low Carbon Emission

Akter

Howlader

Saber³

et al. 2021

Energies

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Optimal sizing of the power system can drastically reduce the total cost, which is challenging due to the fluctuation in output power of RE (primarily wind and solar) and pollution from thermal generators. The main purpose of this study is to cope with this output power uncertainty of renewables by considering ADLC, residential PV, and BESS at the lowest cost and with the least amount of carbon emission, while putting less burden on consumers by minimizing the IL. This paper optimizes the cost and carbon emission function of a hybrid energy system comprising PV, WG, BESS, and DG at Aguni Island, Japan, using a multi-objective optimization model. To solve the proposed problem in the presence of ADLC, the ϵ-constraint method and MILP are utilized. After obtaining all possible solutions, the FSM selects the best possible solution among all solutions. The result shows that while case 1 has a lower energy cost than the other cases, the quantity of IL is quite significant, putting customers in a burden. In case 2 and case 3, the total energy cost is 11.23% and 10% higher than case 1, respectively, but the sum of the IL is 99% and 95.96% lower than case 1 as the ADLC is applied only for the consumers who have residential PV and BESS, which can reflect the importance of residential PV and BESS. The total cost of case 3 is 1.72% lower than case 2, but IL is higher because sometimes home PV power will be used to charge the home BESS.

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Section: Literature Reviewmentioning

confidence: 99%

Optimal Sizing of Hybrid Microgrid in a Remote Island Considering Advanced Direct Load Control for Demand Response and Low Carbon Emission

Akter

Howlader

Saber³

et al. 2021

Energies

View full text Add to dashboard Cite

show abstract

“…However, due to high cost and low efficiency, it will produce economic waste. References [6][7][8] used adaptive wavelet transform to distribute the output power once and obtained the power and energy storage power which satisfied the gridconnected condition. However, the empirical mode decomposition (EMD) proposed in this paper is prone to modal aliasing and poor decomposition effect and cannot accurately separate signals with similar frequencies.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Energy Storage System Strategy for Smoothing Photovoltaic Power Fluctuation Based on Improved HHO-VMD

Liu

2023

International Journal of Photoenergy

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To solve the problems of large fluctuation of photovoltaic output power affecting the safe operation of the power grid, a hybrid energy storage capacity configuration strategy based on the improved Harris hawks optimization algorithm optimizing variational mode decomposition (IHHO-VMD) is proposed. In this strategy, the improved Harris hawk optimization algorithm is used to adaptively select k and α in VMD parameters and decompose the photovoltaic output power and distinguish between correlated and uncorrelated modes. Similarly, the moving average method (MA) is used to extract the continuous component signal in the uncorrelated mode, and it is reconstructed with the related mode as the grid-connected power that meets the national standard. The hybrid energy storage system (HESS) is used to stabilize the fluctuation component signal. The minimum annual configuration cost of the energy storage system is established as the objective function. The simulation results show that the improved algorithm reduces the cost of the hybrid energy storage system by 6.15% compared with the original algorithm, suppresses the power fluctuation, and improves the economy and stability of the system.

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Artificial intelligence applications for microgrids integration and management of hybrid renewable energy sources

et al. 2023

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The integration of renewable energy sources (RESs) has become more attractive to provide electricity to rural and remote areas, which increases the reliability and sustainability of the electrical system, particularly for areas where electricity extension is difficult. Despite this, the integration of hybrid RESs is accompanied by many problems as a result of the intermittent and unstable nature of RESs. The extant literature has discussed the integration of RESs, but it is not comprehensive enough to clarify all the factors that affect the integration of RESs. In this paper, a comprehensive review is made of the integration of RESs. This review includes various combinations of integrated systems, integration schemes, integration requirements, microgrid communication challenges, as well as artificial intelligence used in the integration. In addition, the review comprehensively presents the potential challenges arising from integrating renewable resources with the grid and the control strategies used. The classifications developed in this review facilitate the integration improvement process. This paper also discusses the various optimization techniques used to reduce the total cost of integrated energy sources. In addition, it examines the use of up-to-date methods to improve the performance of the electrical grid. A case study is conducted to analyze the impact of using artificial intelligence when integrating RESs. The results of the case study prove that the use of artificial intelligence helps to improve the accuracy of operation to provide effective and accurate prediction control of the integrated system. Various optimization techniques are combined with ANN to select the best hybrid model. PSO has the fast convergence rate for reaching to the minimum errors as the Normalized Mean Square Error (NMSE) percentage reaches 1.10% in 3367.50 s.

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Multi-objective optimal sizing of hybrid energy storage systems for grid-connected wind farms using fuzzy control

Cited by 9 publications

References 38 publications

Optimal Sizing of Hybrid Microgrid in a Remote Island Considering Advanced Direct Load Control for Demand Response and Low Carbon Emission

Optimal Sizing of Hybrid Microgrid in a Remote Island Considering Advanced Direct Load Control for Demand Response and Low Carbon Emission

A Hybrid Energy Storage System Strategy for Smoothing Photovoltaic Power Fluctuation Based on Improved HHO-VMD

Artificial intelligence applications for microgrids integration and management of hybrid renewable energy sources

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