Evaluation of hierarchical controls to manage power, energy and daily operation of remote off-grid power systems

Kaluthanthrige, Roshani; Rajapakse, Athula D.

doi:10.1016/j.apenergy.2021.117259

Cited by 11 publications

(5 citation statements)

References 32 publications

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“…With the rapid development of information technology, big data technology can be seen everywhere in production and life. In the power industry, the construction of the electric power Internet of things makes the power management and information technology fully integrated [1][2][3][4][5]. Power system prediction can provide the development status and level of the current power system, and the power dispatching department formulates the power supply plan according to the power system prediction.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…In past research, Li et al [6] proposed an improved hybrid optimization model based on the grey GM (1,1) model to develop a predictive model for the power system. To achieve more accurate predictions, the regression model is first integrated into GM (1,1) by compensating for the residual sequence. Almutairi et al [7] proposed a novel deep learning approach based on lower bound estimation (LUBE) and long short-term memory (LSTM) models to capture the effects of uncertainty in wind turbine power generation.…”

Section: Introductionmentioning

confidence: 99%

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Short-term electric power prediction in a certain area based on least squares support vector machine

Xie

Gao

2023

Eighth International Symposium on Advances in Electrical, Electronics, and Computer Engineering (ISAEECE 2023)

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Short-term power prediction is one of the important tasks in the daily operation of the energy system. With the popularity of smart grid, it brings more difficulties to the accuracy of electricity prediction. The purpose of this study is to explore the characteristics of short-term power data to achieve efficient and accurate power prediction and provide a reference for power grid operation management. Firstly, according to various characteristics of power prediction, this paper builds shortterm power prediction models by using SVM and LS-SVM, respectively. Then, this paper compares the prediction results of the two single models with the test values. It is found that the prediction curve of the LS-SVM model is better than that of the SVM model, and the LS-SVM prediction model has better potential for prediction short-term power consumption. This indicates that different machine learning models are suitable for different types of electrical power predictions.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Short-term electric power prediction in a certain area based on least squares support vector machine

Xie

Gao

2023

Eighth International Symposium on Advances in Electrical, Electronics, and Computer Engineering (ISAEECE 2023)

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“…[13] takes the microgrid group as the research object, focuses on the energy management and power coordination control strategy in the off-grid mode, and realizes the stable operation of the system. However, the current power dispatching optimization strategies mostly study and analyze the equivalence of source-grid-load-storage concentration in the power system, and fail to consider the power flow operation state on a spatial scale [14].…”

Section: Introductionmentioning

confidence: 99%

Optimal Dispatch of the Source-Grid-Load-Storage under a High Penetration of Photovoltaic Access to the Distribution Network

Zhang,

Zhou,

Gao

et al. 2023

Processes

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In the context of carbon peaking and carbon neutralization, distributed photovoltaics is a relatively mature new energy power generation technology that is being widely promoted. However, the randomness and volatility of distributed generation bring severe challenges to the distribution network’s operation. Based on this, taking the typical scenario of a high proportion of distributed photovoltaic grid connections against the background of a whole-county photovoltaic system as the research object, this paper constructs a source-grid-load-storage coordination optimal scheduling model in distribution networks, considering the spatial distribution of power flow, tie-line power fluctuation, grid loss, and voltage amplitude from the perspective of optimal day-to-day scheduling. Next, the Lehmer weighted and improved multi-mutation cooperation strategy differential evolution (LW-IMCSDE) algorithm is introduced to enhance the differential evolution algorithm based on the weighted Lehmer average, improved multi-mutation cooperation, and population update strategies. The feasibility and effectiveness of the algorithm are investigated by using a test function to verify its effectiveness. Finally, the feasibility and effectiveness of the proposed strategy are verified in two typical power scenarios: summer and winter.

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“…Furthermore, their system operation control is more complicated than traditional singleenergy systems, complex structures, regional dispersion, etc. [8][9][10]. However, the size and capacity of the current mainstream multi-energy system are relatively small, the proportion of intermittent energy is high, and the application range of the layered control concept is low [11,12].…”

Section: Scheduling 1 Introductionmentioning

confidence: 99%

Control method of multi-energy system based on layered control architecture

Zhang

et al. 2022

Energy and Buildings

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Evaluation of hierarchical controls to manage power, energy and daily operation of remote off-grid power systems

Cited by 11 publications

References 32 publications

Short-term electric power prediction in a certain area based on least squares support vector machine

Short-term electric power prediction in a certain area based on least squares support vector machine

Optimal Dispatch of the Source-Grid-Load-Storage under a High Penetration of Photovoltaic Access to the Distribution Network

Control method of multi-energy system based on layered control architecture

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