{"title":"针对有空调负荷的智能电网的弹性鲁棒模型预测负荷频率控制","authors":"Shiluo Jike, Guobao Liu, Feng Li, Changyu Zhang, Qi Wang, Mengxia Zhou, Haiya Qian","doi":"10.1049/rpg2.13075","DOIUrl":null,"url":null,"abstract":"<p>This paper investigates the robust model predictive load frequency control problem for smart grids with wind power under cyber attacks. To accommodate intermittent power generation, the demand response of the system is considered by involving the air conditioning loads in the frequency regulation. In addition, the system uncertainties produced by the air conditioning load users and wind turbines when replacing traditional generator sets are considered. By using the cone complementary linearization algorithm and the linear matrix inequality technique, a resilience robust model predictive control strategy with mixed <span></span><math>\n <semantics>\n <mrow>\n <msub>\n <mi>H</mi>\n <mn>2</mn>\n </msub>\n <mo>/</mo>\n <msub>\n <mi>H</mi>\n <mi>∞</mi>\n </msub>\n </mrow>\n <annotation>$H_2/H_\\infty$</annotation>\n </semantics></math> performance indexes is proposed. Furthermore, a rigorous derivation of the recursive feasibility of robust model predictive control is given. Finally, the simulation results of the two-area load frequency control scheme show that the proposed model predictive control strategy is capable of realizing the load frequency control of the multi-area smart grid and is robust to the parameter uncertainties and frequency regulation of the system. The results also show that the proposed model predictive control strategy has some resistance to cyber attacks and external disturbances.</p>","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"18 14","pages":"2326-2339"},"PeriodicalIF":2.6000,"publicationDate":"2024-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.13075","citationCount":"0","resultStr":"{\"title\":\"Resilient robust model predictive load frequency control for smart grids with air conditioning loads\",\"authors\":\"Shiluo Jike, Guobao Liu, Feng Li, Changyu Zhang, Qi Wang, Mengxia Zhou, Haiya Qian\",\"doi\":\"10.1049/rpg2.13075\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>This paper investigates the robust model predictive load frequency control problem for smart grids with wind power under cyber attacks. To accommodate intermittent power generation, the demand response of the system is considered by involving the air conditioning loads in the frequency regulation. In addition, the system uncertainties produced by the air conditioning load users and wind turbines when replacing traditional generator sets are considered. By using the cone complementary linearization algorithm and the linear matrix inequality technique, a resilience robust model predictive control strategy with mixed <span></span><math>\\n <semantics>\\n <mrow>\\n <msub>\\n <mi>H</mi>\\n <mn>2</mn>\\n </msub>\\n <mo>/</mo>\\n <msub>\\n <mi>H</mi>\\n <mi>∞</mi>\\n </msub>\\n </mrow>\\n <annotation>$H_2/H_\\\\infty$</annotation>\\n </semantics></math> performance indexes is proposed. Furthermore, a rigorous derivation of the recursive feasibility of robust model predictive control is given. Finally, the simulation results of the two-area load frequency control scheme show that the proposed model predictive control strategy is capable of realizing the load frequency control of the multi-area smart grid and is robust to the parameter uncertainties and frequency regulation of the system. The results also show that the proposed model predictive control strategy has some resistance to cyber attacks and external disturbances.</p>\",\"PeriodicalId\":55000,\"journal\":{\"name\":\"IET Renewable Power Generation\",\"volume\":\"18 14\",\"pages\":\"2326-2339\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2024-08-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.13075\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IET Renewable Power Generation\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1049/rpg2.13075\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Renewable Power Generation","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/rpg2.13075","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0
摘要
本文研究了网络攻击下风力发电智能电网的鲁棒模型预测负载频率控制问题。为了适应间歇性发电,考虑了系统的需求响应,让空调负荷参与频率调节。此外,还考虑了空调负荷用户和风力涡轮机取代传统发电机组时产生的系统不确定性。通过使用锥形互补线性化算法和线性矩阵不等式技术,提出了一种具有混合 H 2 / H ∞ $H_2/H_\infty$ 性能指标的弹性鲁棒模型预测控制策略。此外,还严格推导了鲁棒模型预测控制的递归可行性。最后,两区负荷频率控制方案的仿真结果表明,所提出的模型预测控制策略能够实现多区智能电网的负荷频率控制,并且对系统的参数不确定性和频率调节具有鲁棒性。结果还表明,所提出的模型预测控制策略具有一定的抵御网络攻击和外部干扰的能力。
Resilient robust model predictive load frequency control for smart grids with air conditioning loads
This paper investigates the robust model predictive load frequency control problem for smart grids with wind power under cyber attacks. To accommodate intermittent power generation, the demand response of the system is considered by involving the air conditioning loads in the frequency regulation. In addition, the system uncertainties produced by the air conditioning load users and wind turbines when replacing traditional generator sets are considered. By using the cone complementary linearization algorithm and the linear matrix inequality technique, a resilience robust model predictive control strategy with mixed performance indexes is proposed. Furthermore, a rigorous derivation of the recursive feasibility of robust model predictive control is given. Finally, the simulation results of the two-area load frequency control scheme show that the proposed model predictive control strategy is capable of realizing the load frequency control of the multi-area smart grid and is robust to the parameter uncertainties and frequency regulation of the system. The results also show that the proposed model predictive control strategy has some resistance to cyber attacks and external disturbances.
期刊介绍:
IET Renewable Power Generation (RPG) brings together the topics of renewable energy technology, power generation and systems integration, with techno-economic issues. All renewable energy generation technologies are within the scope of the journal.
Specific technology areas covered by the journal include:
Wind power technology and systems
Photovoltaics
Solar thermal power generation
Geothermal energy
Fuel cells
Wave power
Marine current energy
Biomass conversion and power generation
What differentiates RPG from technology specific journals is a concern with power generation and how the characteristics of the different renewable sources affect electrical power conversion, including power electronic design, integration in to power systems, and techno-economic issues. Other technologies that have a direct role in sustainable power generation such as fuel cells and energy storage are also covered, as are system control approaches such as demand side management, which facilitate the integration of renewable sources into power systems, both large and small.
The journal provides a forum for the presentation of new research, development and applications of renewable power generation. Demonstrations and experimentally based research are particularly valued, and modelling studies should as far as possible be validated so as to give confidence that the models are representative of real-world behavior. Research that explores issues where the characteristics of the renewable energy source and their control impact on the power conversion is welcome. Papers covering the wider areas of power system control and operation, including scheduling and protection that are central to the challenge of renewable power integration are particularly encouraged.
The journal is technology focused covering design, demonstration, modelling and analysis, but papers covering techno-economic issues are also of interest. Papers presenting new modelling and theory are welcome but this must be relevant to real power systems and power generation. Most papers are expected to include significant novelty of approach or application that has general applicability, and where appropriate include experimental results. Critical reviews of relevant topics are also invited and these would be expected to be comprehensive and fully referenced.
Current Special Issue. Call for papers:
Power Quality and Protection in Renewable Energy Systems and Microgrids - https://digital-library.theiet.org/files/IET_RPG_CFP_PQPRESM.pdf
Energy and Rail/Road Transportation Integrated Development - https://digital-library.theiet.org/files/IET_RPG_CFP_ERTID.pdf