Optimal and stochastic performance of an energy hub-based microgrid consisting of a solar-powered compressed-air energy storage system and cooling storage system by modified grasshopper optimization algorithm

Wen, Peng; Xie, Yunfang; Hou, Limin; Tohidi, Akbar

doi:10.1016/j.ijhydene.2022.02.081

Cited by 29 publications

(14 citation statements)

References 31 publications

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“…The first assessed arrangement is the Wind/PV/DG/BESS structure, which benefits from the complementarity of the wind turbine and Photovoltaic resources. In comparison, five algorithms, including the Evolutionary Algorithm (EA) [ 38 ], Modified Grasshopper Optimization Algorithm (MGOA) [ 39 ], Improved Gray Wolf Optimization Algorithm (IGWOA) [ 40 ], Improved Arithmetic Optimization Algorithm (IAOA) [ 25 ], and the original MVOA were utilized. The suggested AMVOA yields the optimum project investment in Fig.…”

Section: Simulation Resultsmentioning

confidence: 99%

Maximizing energy storage in Microgrids with an amended multi-verse optimizer

Hu,

Zhao,

et al. 2023

Heliyon

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Section: Simulation Resultsmentioning

confidence: 99%

Maximizing energy storage in Microgrids with an amended multi-verse optimizer

Hu,

Zhao,

et al. 2023

Heliyon

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“…In this reference, the modelling of EVs, fuel cells, and hydrogen storage is considered in the problem. In [15], the modelling of PVs, CAES, and cooling storage in the EH have been discussed. In addition to this, the formulation of the operation of EHs in energy networks is non-linear.…”

Section: Literature Reviewmentioning

confidence: 99%

“…This issue can also be achieved by reducing the volume of the problem. However, it should be noted that scenario-based stochastic programming (SBSP) and probabilistic programming have been used in general studies such as [8][9][10][11][12][13][15][16][17] to model uncertainties. In these methods, to obtain the guaranteed optimal solution, it is necessary to extract a significant number of scenarios.…”

Section: Research Gapsmentioning

confidence: 99%

Participation of energy hubs in the market clearing price‐based energy market considering generation and consumption uncertainty modelling

Farsani

Joorabian

Mortazavi

2023

IET Renewable Power Gen

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The market clearing pricing (MCP) model is used to operate electricity, gas, and heating networks (EGHNs) with flexible energy hubs (EHs) in the day‐ahead energy market. It's two‐level optimization. Its higher level refers to EHs' participation in the market and their profit maximization bound by the operational model of power sources, storage devices, and responsive loads in the form of EHs and their flexibility limit. In the lower‐level problem, the MCP model calculates energy price and evaluates EH performance's effects on the networks' technical and economic indices. It optimizes power flow in the networks to reduce centralized generator operating costs. This approach is linear approximation. Unscented transformation (UT) model load and renewable power uncertainties. This technique contains the fewest situations, reducing issue volume and computing time. Benders decomposition (BD) technique calculates energy prices, EHs, and networks. Finally, the numerical results show that the proposed scheme can extract the optimal economic and flexibility states of EHs. EHs' optimal performance enhanced energy networks' economic and operating status compared to power flow studies and promoted societal welfare by lowering energy prices.

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“…Using the proposed system in a case study of San Francisco as an example, a total potable water production of 226,782 m 3 cubic meters, 27,551 MWh of electricity generation, and a payback period of 2.65 years were achieved. Wen et al [53] proposed an energy hub consisting of a CCHP system along with a wind turbine and photovoltaic cells. The energy hub system has an ice storage conditioner system and an energy storage system.…”

Section: Solar-assist Caes With Cchp or Producing Other Productsmentioning

confidence: 99%

Review of Coupling Methods of Compressed Air Energy Storage Systems and Renewable Energy Resources

Guo

Kang

et al. 2023

Energies

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With the strong advancement of the global carbon reduction strategy and the rapid development of renewable energy, compressed air energy storage (CAES) technology has received more and more attention for its key role in large-scale renewable energy access. This paper summarizes the coupling systems of CAES and wind, solar, and biomass energies from the perspective of system topology, and points out the advantages and limitations of each system. It is shown that the coupling of wind energy and CAES is mainly combined in series and in parallel, and sometimes part of the wind power can be converted into thermal energy when coupled to CAES. The coupling between solar heat and CAES is an important form of coupling between solar energy and CAES. Solar-heat-coupled CAES mainly uses solar energy to heat expander inlet air. The coupling forms of solar energy and CAES are based on various CAES forms, various heat heating sequences, reheating, bottom cycle, and other factors. The combination of biomass and CAES is generally based on biomass gasification power generation technology. In the future, a wind–solar–CAES multiple coupling system is expected to become a promising large-scale form for the utilization of renewable energy, and this integrated system has great potential as a system configuration, but has some technical challenges.

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Optimal and stochastic performance of an energy hub-based microgrid consisting of a solar-powered compressed-air energy storage system and cooling storage system by modified grasshopper optimization algorithm

Cited by 29 publications

References 31 publications

Maximizing energy storage in Microgrids with an amended multi-verse optimizer

Maximizing energy storage in Microgrids with an amended multi-verse optimizer

Participation of energy hubs in the market clearing price‐based energy market considering generation and consumption uncertainty modelling

Review of Coupling Methods of Compressed Air Energy Storage Systems and Renewable Energy Resources

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