Optimal facility combination set of integrated energy system based on consensus point between independent system operator and independent power producer

Son, Yeong Geon; Oh, Byeong Chan; Acquah, Moses Amoasi; Kim, Sung-Yul

doi:10.1016/j.energy.2022.126422

Cited by 10 publications

(6 citation statements)

References 32 publications

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“…In this paper, HESS is modeled as described in Equations ( 12) and ( 13) [14]. HESS applies Type 4 modules capable of storing hydrogen on a large scale at an atmospheric pressure of 700 bar.…”

Section: Modeling Of Hessmentioning

confidence: 99%

“…In this paper, BESS is modeled as described in Equations ( 14)-( 20) [14]. BESS is easy to charge and discharge, and it is assumed to use lithium-ion batteries, which are commonly utilized as power BESS.…”

Section: Modeling Of Bessmentioning

confidence: 99%

“…In a related study, Reference [13] explores the integration of PV systems with P2G, aiming to avert the output saturation in PV and enhance the overall generation efficiency. Additionally, Reference [14] demonstrates that utilizing a P2G-based Integrated Energy System can lead to a substantial reduction in curtailment for both WT and PV systems. Reference [15] is focused on identifying the ideal capacity of P2G facilities for the deployment of RESs, offering a model to adjust the capacity of P2G facilities accordingly.…”

Section: Introductionmentioning

confidence: 99%

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Optimal Coordination of Energy Coupling System Considering Uncertainty of Renewable Energy Sources

Son,

Kim,

Bae

2024

Energies

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To advance carbon neutrality policies, many countries are increasingly integrating Renewable Energy Sources (RESs) into their energy mix. However, for harnessing natural energy in power generation, RESs present challenges in output control, potentially leading to power imbalances. Such imbalances, when coupled with an excessive reliance on unpredictable RES, may necessitate the curtailment of grid-integrated renewable generation, halting production despite available capacity. This paper proposes strategies to mitigate the economic and operational efficiency impacts of increased RESs on the power grid. It focuses on the optimal operation of Battery Energy Storage Systems (BESSs) and Power to Gas (P2G) technology, which flexibly converts surplus electricity into hydrogen. By employing Mixed Integer Linear Programming (MILP) for optimization and Stochastic Programming (SP) for the management of the uncertainty of renewable energy output, this paper evaluates the anticipated benefits of BESS and P2G applications.

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Section: Modeling Of Hessmentioning

confidence: 99%

Section: Modeling Of Bessmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Optimal Coordination of Energy Coupling System Considering Uncertainty of Renewable Energy Sources

Son,

Kim,

Bae

2024

Energies

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“…To harvest the solar energy, it is necessary to optimally forecast its generation. For this purpose, the author in [53] has proposed a regression technique called least absolute shrinkage and selection operator (LASSO), which enhances forecast accuracy. ARIMA, wavelet neural network (WNN), and improved empirical mode decomposition (EMD) used to forecast load and FFI optimization is done.…”

Section: Hybrid Forecasting Modelmentioning

confidence: 99%

“…To compute the performance of the proposed hybrid model, two case studies are examined. Te frst study is for the Hellenic interconnected power system, where time series load data [53] covers the period from 1 January 2015 to 30 June 2019, and temperature prediction data is acquired from the SKIRON meteorological model [54]. Tis presented model was trained with recorded data for the frst four years and tested with recorded data during 2018.…”

Section: Case Studiesmentioning

confidence: 99%

Application of Fuzzy-RBF-CNN Ensemble Model for Short-Term Load Forecasting

Yadav

Jamil

Rizwan

et al. 2023

Journal of Electrical and Computer Engineering

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Accurate load forecasting (LF) plays an important role in the operation and decision-making process of the power grid. Although the stochastic and nonlinear behavior of loads is highly dependent on consumer energy requirements, that demands a high level of accuracy in LF. In spite of several research studies being performed in this field, accurate load forecasting remains an important consideration. In this article, the design of a hybrid short-term load forecasting model (STLF) is proposed. This work combines the features of an artificial neural network (ANN), ensemble forecasting, and a deep learning network. RBFNNs and CNNs are trained in two phases using the functional link artificial neural network (FLANN) optimization method with a deep learning structure. The predictions made from RBFNNs have been computed and produced as the forecast of each activated cluster. This framework is known as fuzzy-RBFNN. This proposed framework is outlined to anticipate one-week ahead load demand on an hourly basis, and its accuracy is determined using two case studies, i.e., Hellenic and Cretan power systems. Its results are validated while comparing with four benchmark models like multiple linear regression (MLR), support vector machine (SVM), ML-SVM, and fuzzy-RBFNN in terms of accuracy. To demonstrate the performance of RBF-CNN, SVMs replace the RBF-CNN regressor, and this model is identified as an ML-SVM having 3 layers.

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Systematic planning of power-to-gas for improving photovoltaic acceptance rate: Application of the potential RES penetration index

Son,

Choi,

Aquah

et al. 2023

Applied Energy

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Optimal facility combination set of integrated energy system based on consensus point between independent system operator and independent power producer

Cited by 10 publications

References 32 publications

Optimal Coordination of Energy Coupling System Considering Uncertainty of Renewable Energy Sources

Optimal Coordination of Energy Coupling System Considering Uncertainty of Renewable Energy Sources

Application of Fuzzy-RBF-CNN Ensemble Model for Short-Term Load Forecasting

Systematic planning of power-to-gas for improving photovoltaic acceptance rate: Application of the potential RES penetration index

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