Economic value and government compensation calculative method of energy storage system

Ye, Jilei; Xue, Junmin; Sang, Bingyu; Lu, Dan; Liu, Haoming

doi:10.1109/ipemc.2016.7512343

Cited by 7 publications

(5 citation statements)

References 5 publications

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“…In addition, the time of use electricity price policy is applied as shown in Table 2. Referring to [25,26], the related economic parameters are shown in Table 3. Table 3.…”

Section: Simulation and Discussionmentioning

confidence: 99%

Optimal Configuration of Different Energy Storage Batteries for Providing Auxiliary Service and Economic Revenue

Chen

2018

Applied Sciences

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Energy storage providing auxiliary service at the user-side has broad prospects in support of national polices. Three auxiliary services are selected as the application scene for energy storage participating in demand management, peak shaving and demand response. Considering the time value of funds, the user-side energy storage economy model is built. The model comprehensively considers the delayed transformation income, the government subsidy income, the auxiliary service income and the whole-life-cycle cost factor. According to the cost and benefit analysis, an energy storage optimization configuration model is proposed. The model takes maximum revenue of industrial user in energy storage’s whole-life-cycle as the objective function. Then, the Cplex solver is employed to solve the model. In addition, four indexes are utilized to evaluate the financial effect brought by the user-side energy storage. Finally, the revenue and configuration results of the four types of battery energy storage are calculated to verify the validity of the proposed model. In comparison to the value of evaluation index, planning suggestions are provided for the user-side energy storage providing different auxiliary services. Moreover, the conditions of profit and worthwhile investment are obtained through sensitivity analysis of energy storage providing peak shaving service.

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“…In addition, the time of use electricity price policy is applied as shown in Table 2. Referring to [25,26], the related economic parameters are shown in Table 3. Table 3.…”

Section: Simulation and Discussionmentioning

confidence: 99%

Optimal Configuration of Different Energy Storage Batteries for Providing Auxiliary Service and Economic Revenue

Chen

2018

Applied Sciences

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“…Due to the intermittency and variability of solar energy, accurate PV power forecasting can effectively improve the safety and stability of power grid operation, thus improving the access rate of PV power generation [4][5][6] . According to different modeling methods, PV power forecasting can be divided into physical and statistical methods [7] . At present, statistical methods are commonly used, including artificial neural network(ANN), support vector machine(SVM), Markov chain, and autoregression [8][9] .…”

Section: Introductionmentioning

confidence: 99%

The Method of Photovoltaic Power Forecast based on Seasonal Classification and Limit Learning Machine

Li¹,

Ma²,

Hu³

et al. 2023

J. Phys.: Conf. Ser.

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The seasonal distribution characteristics of photovoltaic power plant output fluctuation are analyzed, and a short-term power forecasting method based on seasonal classification is proposed. Firstly, the seasonal distribution characteristics of photovoltaic output and its fluctuation are analyzed. Secondly, the forecasting model of photovoltaic output in different seasons is established by the Limit Learning Machine neural network. Finally, an empirical analysis is carried out by using photovoltaic output data. The results show that the seasonal classification method of short-term PV power forecast is better than the unclassified model.

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“…In order to eliminate the impact of a high percentage of photovoltaics connected to the distribution network, the distribution network will be scaled to connect to the Energy Storage System (ESS), which is a device with the ability to supply and store electrical energy, while the power regulation is flexible and rapid, so it is increasingly used in the grid [1]. In response to a series of problems caused by household PV, the Distributed Energy Storage System (DESS) can effectively respond to PV fluctuations and improve the power quality of the grid [2].…”

Section: Introductionmentioning

confidence: 99%

Multi-objective planning of electric vehicle charging pile considering photovoltaic power uncertainty

Fu,

Li,

Hua

et al. 2023

Eighth International Conference on Electromechanical Control Technology and Transportation (ICECTT 2023)

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Economic value and government compensation calculative method of energy storage system

Cited by 7 publications

References 5 publications

Optimal Configuration of Different Energy Storage Batteries for Providing Auxiliary Service and Economic Revenue

Optimal Configuration of Different Energy Storage Batteries for Providing Auxiliary Service and Economic Revenue

The Method of Photovoltaic Power Forecast based on Seasonal Classification and Limit Learning Machine

Multi-objective planning of electric vehicle charging pile considering photovoltaic power uncertainty

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