Sonali R. Nandanwar , Narayan Prasad Patidar , Siddharth Panda , Jalpa Thakkar , Mohan Lal Kolhe
{"title":"协同控制以增强具有分散式可再生能源资源、储能和电动汽车的电网集成网络的频率稳定性","authors":"Sonali R. Nandanwar , Narayan Prasad Patidar , Siddharth Panda , Jalpa Thakkar , Mohan Lal Kolhe","doi":"10.1016/j.clet.2024.100757","DOIUrl":null,"url":null,"abstract":"<div><p>The integration of Decentralized Energy Resources (DERs), Energy Storage Systems (ESS), and Electric Vehicles (EVs) into grid-connected networks presents a transformative paradigm in modern power systems. This article introduces a synergistic control framework tailored for optimizing frequency stability within grid-integrated distributed networks. The proposed approach leverages advanced control algorithms to orchestrate the dynamic interaction between DERs, ESS, and EVs, ensuring seamless operation and enhanced grid resilience. The effectiveness of the proposed control strategy is demonstrated in mitigating frequency deviations, thereby contributing to a more stable and reliable grid infrastructure. This article introduces a novel approach utilizing the Selfish Herd Optimization (SHO) algorithm to address this critical issue. Inspired by the self-preservation behavior observed in animal herding, the SHO algorithm is adapted to coordinate the operation of DERs with loads within a distributed network. By dynamically adjusting their output based on local frequency measurements, DERs collectively exhibit a self-organizing behavior, resulting in improved frequency stability. The SHO based PID controller is also proven to be far more effective at controlling frequency than the traditional PI controller. The findings underscore the potential of bio-inspired algorithms in enhancing the resilience of grid-integrated DER systems, offering a promising avenue for future grid control methodologies.</p></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":null,"pages":null},"PeriodicalIF":5.3000,"publicationDate":"2024-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666790824000375/pdfft?md5=8162d73b30906897c88b4f9389ec457e&pid=1-s2.0-S2666790824000375-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Synergistic control for enhancing frequency stability in grid-integrated network with decentralized renewable energy resources, energy storage, and electric vehicles\",\"authors\":\"Sonali R. 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This article introduces a novel approach utilizing the Selfish Herd Optimization (SHO) algorithm to address this critical issue. Inspired by the self-preservation behavior observed in animal herding, the SHO algorithm is adapted to coordinate the operation of DERs with loads within a distributed network. By dynamically adjusting their output based on local frequency measurements, DERs collectively exhibit a self-organizing behavior, resulting in improved frequency stability. The SHO based PID controller is also proven to be far more effective at controlling frequency than the traditional PI controller. 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引用次数: 0
摘要
将分散式能源资源 (DER)、储能系统 (ESS) 和电动汽车 (EV) 整合到并网网络中,是现代电力系统的一种变革模式。本文介绍了一种为优化并网分布式网络频率稳定性而量身定制的协同控制框架。所提出的方法利用先进的控制算法来协调 DER、ESS 和电动汽车之间的动态互动,从而确保无缝运行并增强电网弹性。建议的控制策略在缓解频率偏差方面的有效性得到了验证,从而有助于建立更加稳定可靠的电网基础设施。本文介绍了一种利用自私羊群优化(SHO)算法解决这一关键问题的新方法。受动物放牧中自我保护行为的启发,SHO 算法适用于协调分布式网络中 DER 与负载的运行。通过根据本地频率测量结果动态调整输出,DER 集体表现出自组织行为,从而提高频率稳定性。事实证明,基于 SHO 的 PID 控制器在频率控制方面远比传统的 PI 控制器更有效。研究结果强调了生物启发算法在增强电网集成 DER 系统的恢复能力方面的潜力,为未来的电网控制方法提供了一条前景广阔的途径。
Synergistic control for enhancing frequency stability in grid-integrated network with decentralized renewable energy resources, energy storage, and electric vehicles
The integration of Decentralized Energy Resources (DERs), Energy Storage Systems (ESS), and Electric Vehicles (EVs) into grid-connected networks presents a transformative paradigm in modern power systems. This article introduces a synergistic control framework tailored for optimizing frequency stability within grid-integrated distributed networks. The proposed approach leverages advanced control algorithms to orchestrate the dynamic interaction between DERs, ESS, and EVs, ensuring seamless operation and enhanced grid resilience. The effectiveness of the proposed control strategy is demonstrated in mitigating frequency deviations, thereby contributing to a more stable and reliable grid infrastructure. This article introduces a novel approach utilizing the Selfish Herd Optimization (SHO) algorithm to address this critical issue. Inspired by the self-preservation behavior observed in animal herding, the SHO algorithm is adapted to coordinate the operation of DERs with loads within a distributed network. By dynamically adjusting their output based on local frequency measurements, DERs collectively exhibit a self-organizing behavior, resulting in improved frequency stability. The SHO based PID controller is also proven to be far more effective at controlling frequency than the traditional PI controller. The findings underscore the potential of bio-inspired algorithms in enhancing the resilience of grid-integrated DER systems, offering a promising avenue for future grid control methodologies.