An Economic Optimization Method for Demand-side Energy-storage Accident Backup Assisted Deep Peaking of Thermal Power Units

Wen, Wei; Ye, Ze; Wang, Yali; Dai, Shuangfeng; Chen, Lei; Liu, Xiaolong

doi:10.23919/cjee.2022.000015

Cited by 5 publications

(2 citation statements)

References 20 publications

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“…Guo et al (2021) also constructed a model to optimize an integrated energy system by considering the DR with carbon emissions and the peak-to-valley ratio of load as the objectives of optimization. Wei et al (2022) proposed an economic optimization method for depth peak regulation and the depth of the emergency of the energy storage accident on the demand side. Meanwhile, carbon trading mechanism, as one of the effective ways to realize the goal of "double carbon", has been studied in depth in the integrated energy system.…”

Section: Related Work Of Demand Response and Carbon Trading Models Fo...mentioning

confidence: 99%

Master–slave game-based optimal scheduling of community-integrated energy system by considering incentives for peak-shaving and ladder-type carbon trading

Dai,

Jiang,

Chen

et al. 2023

Front. Energy Res.

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To alleviate the challenges posed by high energy consumption, significant carbon emissions, and conflicting interests among multiple parties in a community-level microgrid, the authors of this study propose a master–slave game-based optimal scheduling strategy for a community-integrated energy system (CIES). First, we analyze the decision variables and revenue-related objectives of each stakeholder in the CIES, and use the results to construct a framework of implementation. Second, we develop a model to incentivize peak regulation and a ladder-type carbon trading model that consider the correlation between the load owing to residential consumers, the load on the regional grid, and the sources of carbon emissions. Third, we propose a master–slave game-based mechanism of interaction and a decision-making model for each party to the game, and show that it has a Stackelberg equilibrium solution by combining genetic algorithms and quadratic programming. The results of evaluations showed that compared with an optimization strategy that considers only the master–slave game, the proposed strategy increased the consumption surplus of the user aggregator by 13.65%, the revenue of the community energy operator by 7.95%, increased the revenue of the energy storage operator, reduced CO2 emissions by 6.10%, and adequately responded to peak-cutting and valley-filling by the power grid company.

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Section: Related Work Of Demand Response and Carbon Trading Models Fo...mentioning

confidence: 99%

Master–slave game-based optimal scheduling of community-integrated energy system by considering incentives for peak-shaving and ladder-type carbon trading

Dai,

Jiang,

Chen

et al. 2023

Front. Energy Res.

Self Cite

View full text Add to dashboard Cite

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“…Li et al (2022) proposed a distributed battery energy storage station optimal scheduling model that considers the movement of peak loads, which can enhance the voltage distribution of the distribution network. Wei et al (2022) proposed an economic optimization method for depth peak regulation and the depth of the emergency of the energy storage (ES) accident on the demand side. Engels et al (2020) proposed a peak shaving strategy for coordinated control of multiple batteries with the goal of net profit.…”

Section: Related Workmentioning

confidence: 99%

Multi-timescale optimal control strategy for energy storage using LSTM prediction–correction in the active distribution network

Wu,

Chen,

Zhou

et al. 2023

Front. Energy Res.

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The daily output of wind power is inversely proportional to the load demand in most situations, which will lead to an increase in peak-to-valley difference and fluctuation. To solve this problem, this study proposes a long short-term memory prediction–correction-based multi-timescale optimal control strategy for energy storage. First, the proposed strategy performs a long short-term memory (LSTM) prediction on the power of wind power and load. Then, it establishes a predictive planning model to improve the effect of peak shaving and the operating income of energy storage. Finally, it uses the method of online correction of power lines for peak shaving to further optimize the energy storage power according to the error between the residual energy of energy storage and the planned residual energy in the actual peak shaving process. By comparing with traditional strategies, the proposed strategy is found to be significantly better than the constant power strategy and the power difference strategy in the peak shaving effect and operating income.

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A genuine V2V market mechanism aiming for maximum revenue of each EV owner based on non-cooperative game model

Lei

Shang

et al. 2023

Journal of Cleaner Production

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An Economic Optimization Method for Demand-side Energy-storage Accident Backup Assisted Deep Peaking of Thermal Power Units

Cited by 5 publications

References 20 publications

Master–slave game-based optimal scheduling of community-integrated energy system by considering incentives for peak-shaving and ladder-type carbon trading

Master–slave game-based optimal scheduling of community-integrated energy system by considering incentives for peak-shaving and ladder-type carbon trading

Multi-timescale optimal control strategy for energy storage using LSTM prediction–correction in the active distribution network

A genuine V2V market mechanism aiming for maximum revenue of each EV owner based on non-cooperative game model

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