{"title":"基于 AADMM 的共享储能规划,提高可再生能源站的复原力","authors":"Long Zhao, Jinping Zhang, Qingquan Lv, Zhenzhen Zhang, Pengfei Gao, Ruixiao Zhang","doi":"10.3389/fenrg.2024.1467627","DOIUrl":null,"url":null,"abstract":"The exponential proliferation of renewable energy has resulted in a significant mismatch between power supply and demand, especially during extreme events. This incongruity presents challenges in efficiently harnessing renewable energy and enhancing the resilience of the power grid. To address this issue, this paper proposes shared energy storage (SES) planning based on the adaptive alternating direction method of multipliers (AADMM). The objective is to fully leverage SES, enhance the local consumption level of renewable energy, ensure power grid resilience, and reduce operational costs. First, to ensure the effective utilization of SES while minimizing initial investment and construction costs, a planning model for SES is formulated. Secondly, to maximize the benefits for multiple prosumers within the renewable energy and SES station, a profit maximization model for multiple prosumers is established. Lastly, to guarantee the privacy security of SES and multi-prosumers while optimizing computational efficiency, a distributed computing model for SES based on AADMM is developed. The results of the example show that the proposed model can not only reduce the cost of 47.96 CNY, but also increase the power self-sufficiency rate by 21.86%. In addition, compared with the traditional distributed optimization, the number of iterations of AADMM is increased by 47.05%, and the computational efficiency is increased by 54.67%. In addition, market prices have a great impact on energy trading, and the impact of market pricing on the operation of the park is not considered in our current research. In this case, our future research aims to consider how to price reasonably between prosumers and between prosumers and SES, so as to realize the stable participation of each subject in the energy market.","PeriodicalId":12428,"journal":{"name":"Frontiers in Energy Research","volume":null,"pages":null},"PeriodicalIF":2.6000,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"AADMM based shared energy storage planning for resilience improvement of renewable energy stations\",\"authors\":\"Long Zhao, Jinping Zhang, Qingquan Lv, Zhenzhen Zhang, Pengfei Gao, Ruixiao Zhang\",\"doi\":\"10.3389/fenrg.2024.1467627\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The exponential proliferation of renewable energy has resulted in a significant mismatch between power supply and demand, especially during extreme events. This incongruity presents challenges in efficiently harnessing renewable energy and enhancing the resilience of the power grid. To address this issue, this paper proposes shared energy storage (SES) planning based on the adaptive alternating direction method of multipliers (AADMM). The objective is to fully leverage SES, enhance the local consumption level of renewable energy, ensure power grid resilience, and reduce operational costs. First, to ensure the effective utilization of SES while minimizing initial investment and construction costs, a planning model for SES is formulated. Secondly, to maximize the benefits for multiple prosumers within the renewable energy and SES station, a profit maximization model for multiple prosumers is established. Lastly, to guarantee the privacy security of SES and multi-prosumers while optimizing computational efficiency, a distributed computing model for SES based on AADMM is developed. The results of the example show that the proposed model can not only reduce the cost of 47.96 CNY, but also increase the power self-sufficiency rate by 21.86%. In addition, compared with the traditional distributed optimization, the number of iterations of AADMM is increased by 47.05%, and the computational efficiency is increased by 54.67%. In addition, market prices have a great impact on energy trading, and the impact of market pricing on the operation of the park is not considered in our current research. 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引用次数: 0
摘要
可再生能源的激增导致电力供需严重不匹配,尤其是在极端事件发生时。这种不协调给有效利用可再生能源和提高电网的恢复能力带来了挑战。为解决这一问题,本文提出了基于自适应交变方向乘法(AADMM)的共享储能(SES)规划。其目的是充分利用 SES,提高可再生能源的本地消纳水平,确保电网弹性,降低运营成本。首先,为确保 SES 的有效利用,同时最大限度地降低初始投资和建设成本,制定了 SES 的规划模型。其次,为实现可再生能源和 SES 站内多个消费者的利益最大化,建立了多个消费者的利润最大化模型。最后,为了在优化计算效率的同时保证 SES 和多用户的隐私安全,建立了基于 AADMM 的 SES 分布式计算模型。实例结果表明,所提出的模型不仅能降低 47.96 元人民币的成本,还能提高 21.86% 的电力自给率。此外,与传统的分布式优化相比,AADMM 的迭代次数增加了 47.05%,计算效率提高了 54.67%。此外,市场价格对能源交易有很大影响,我们目前的研究没有考虑市场价格对园区运行的影响。在这种情况下,我们未来的研究目标是考虑如何在用电方之间、用电方与 SES 之间合理定价,从而实现各主体稳定参与能源市场。
AADMM based shared energy storage planning for resilience improvement of renewable energy stations
The exponential proliferation of renewable energy has resulted in a significant mismatch between power supply and demand, especially during extreme events. This incongruity presents challenges in efficiently harnessing renewable energy and enhancing the resilience of the power grid. To address this issue, this paper proposes shared energy storage (SES) planning based on the adaptive alternating direction method of multipliers (AADMM). The objective is to fully leverage SES, enhance the local consumption level of renewable energy, ensure power grid resilience, and reduce operational costs. First, to ensure the effective utilization of SES while minimizing initial investment and construction costs, a planning model for SES is formulated. Secondly, to maximize the benefits for multiple prosumers within the renewable energy and SES station, a profit maximization model for multiple prosumers is established. Lastly, to guarantee the privacy security of SES and multi-prosumers while optimizing computational efficiency, a distributed computing model for SES based on AADMM is developed. The results of the example show that the proposed model can not only reduce the cost of 47.96 CNY, but also increase the power self-sufficiency rate by 21.86%. In addition, compared with the traditional distributed optimization, the number of iterations of AADMM is increased by 47.05%, and the computational efficiency is increased by 54.67%. In addition, market prices have a great impact on energy trading, and the impact of market pricing on the operation of the park is not considered in our current research. In this case, our future research aims to consider how to price reasonably between prosumers and between prosumers and SES, so as to realize the stable participation of each subject in the energy market.
期刊介绍:
Frontiers in Energy Research makes use of the unique Frontiers platform for open-access publishing and research networking for scientists, which provides an equal opportunity to seek, share and create knowledge. The mission of Frontiers is to place publishing back in the hands of working scientists and to promote an interactive, fair, and efficient review process. Articles are peer-reviewed according to the Frontiers review guidelines, which evaluate manuscripts on objective editorial criteria