Two‐stage chance‐constrained unit commitment based on optimal wind power consumption point considering battery energy storage

Chen, Zhe; Li, Zhengshuo; Guo, Chuangxin; Ding, Yi; He, Yubin

doi:10.1049/iet-gtd.2019.1492

Cited by 17 publications

(4 citation statements)

References 39 publications

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“…Chen Z et al proposed an optimization method that balances robustness and overall cost based on the carbon flow situation in energy storage facilities. The feasibility and effectiveness of the method were ultimately verified through experiments [10].…”

Section: Introductionmentioning

confidence: 97%

Research on carbon flow tracking method for distributed energy stations based on power grid trends

Dou,

Zhang,

Zhang

et al. 2024

Eighth International Conference on Energy System, Electricity, and Power (ESEP 2023)

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In the context of "carbon neutrality" and "carbon peaking", the accuracy of carbon emission control for distributed energy stations is becoming increasingly high, and it is urgent to propose a carbon flow tracking method for distributed energy stations. On the basis of power system power flow theory, this article proposes a calculation method for carbon flow on load nodes and connecting branches based on the relationship between system power flow and carbon flow. The correctness of this method is verified by an IEEE 14 node example. The results indicate that this method can clearly identify branches with high carbon flow rates and areas with high carbon emissions, and provide reasonable emission reduction planning plans.

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Section: Introductionmentioning

confidence: 97%

Research on carbon flow tracking method for distributed energy stations based on power grid trends

Dou,

Zhang,

Zhang

et al. 2024

Eighth International Conference on Energy System, Electricity, and Power (ESEP 2023)

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“…The development of renewable energy is an effective measure to deal with the environmental pollution caused by traditional energy sources, and it is also one of the ways to promote the realization of double-carbon goal [1][2][3] . Among them, wind energy has developed rapidly in recent years because of its abundant resources, large space for development and utilization, and cleanliness [4][5] . Figure 1 shows the wind power installed capacity in the word, with an obvious upward trend, and China is one of the main players in the global installed capacity.…”

Section: Introductionmentioning

confidence: 99%

Research on causes of failure of direct-drive wind turbine

Zhang¹,

Donghao²,

Cao³

2023

Second International Conference on Electronic Information Engineering and Computer Communication (EIECC 2022)

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As one of the clean energy utilization forms, wind power plays a positive role in promoting energy transformation and realizing the double-carbon goal, and wind power generation has been vigorously developed. Wind turbine is an important equipment in the process of wind power generation and wind farm, and its reliable operation should be ensured. In this paper, taking an actual wind farm as an example, the annual failure time of its direct-drive wind turbines is analyzed, and its failure types are sorted out. The causes of failures are analyzed, and the measures to improve the reliability are put forward to provide reference for the safe and stable operation of wind farms.

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“…Energy storage, as a key means of stabilising fluctuations in clean energy power generation and improving the absorption capacity of a system, has been widely used in optimisation scheduling research. On the source side, a combination system of wind and photovoltaic (PV) storage is established, and a multilevel and multimode optimal scheduling strategy is proposed to solve the problem of renewable energy consumption [4][5][6]. However, the integration of wind-PV-storage systems was not considered because single energy storage was affected by capacity and the discharge time was limited.…”

Section: Introductionmentioning

confidence: 99%

Collaborative optimization strategy of source‐grid‐load‐storage considering dynamic time series complementarity of multiple storages

Huang

Liu³

2023

IET Generation Trans & Dist

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The multi‐scale flexibility coordination of multiple storages is a key technology to enhance the diversified regulation ability of the power system. This paper first considers the interaction mechanism of multi‐type storage peak regulation time sequences based on the Euclidian distance, dynamic time warping distance, and storage correlation distance. A matching index was proposed to consider the temporal correlation, overall distribution characteristics, and dynamic characteristics of the net load and energy storage. The multitype storage coordination mode, including battery storage, pumped storage, and electric vehicles, was formulated, and a collaborative optimal scheduling system architecture of source‐grid‐load‐storage (SGLS) was constructed. To attain a low‐carbon economy, a collaborative optimal scheduling model of SGLS considering the dynamic time‐series complementarity of multiple energy storage systems was constructed. The Nash equilibrium theory was used to achieve friendly interaction among the source, grid, load, and storage. Then, an improved transfer reinforcement learning algorithm for SGLS was proposed, which used reinforcement learning and transfer learning algorithms combined with K‐means clustering and dual‐structure experience pool technology. The test results of actual regional power grid data indicated that the proposed strategy can effectively reduce the economic and carbon treatment costs of the system and improve the absorption capacity of renewable energy.

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Two‐stage chance‐constrained unit commitment based on optimal wind power consumption point considering battery energy storage

Cited by 17 publications

References 39 publications

Research on carbon flow tracking method for distributed energy stations based on power grid trends

Research on carbon flow tracking method for distributed energy stations based on power grid trends

Research on causes of failure of direct-drive wind turbine

Collaborative optimization strategy of source‐grid‐load‐storage considering dynamic time series complementarity of multiple storages

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