{"title":"一个实际集成的自动发电控制和需求响应","authors":"Dylan J. Shiltz, A. Annaswamy","doi":"10.1109/ACC.2016.7526740","DOIUrl":null,"url":null,"abstract":"For a power grid to operate properly, electrical frequency must be continuously maintained close to its nominal value. Increasing penetration of distributed generation, such as solar and wind generation, introduces fluctuations in active power while also reducing the natural inertial response of the electricity grid, creating reliability concerns. While frequency regulation has traditionally been achieved by controlling generators, the control of Demand Response (DR) resources has been recognized in recent smart grid literature as an efficient means for providing additional regulation capability. To this end, several control methodologies have been proposed recently, but various features of these proposals make their practical implementations difficult. In this paper, we propose a new control algorithm that facilitates optimal frequency regulation through direct control of both generators and DR, while addressing several issues that prevent practical implementation of other proposals. In particular, i) our algorithm is ideal for control over a large, low-bandwidth network as communication and measurement is only required every 2 seconds, ii) it enables DR resources to recover energy lost during system transients, and iii) it allows the market to immediately respond to disturbances through feedback of the system frequency. We demonstrate the viability of our approach through dynamic simulations on a 118-bus grid model.","PeriodicalId":137983,"journal":{"name":"2016 American Control Conference (ACC)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":"{\"title\":\"A practical integration of automatic generation control and Demand Response\",\"authors\":\"Dylan J. Shiltz, A. Annaswamy\",\"doi\":\"10.1109/ACC.2016.7526740\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"For a power grid to operate properly, electrical frequency must be continuously maintained close to its nominal value. Increasing penetration of distributed generation, such as solar and wind generation, introduces fluctuations in active power while also reducing the natural inertial response of the electricity grid, creating reliability concerns. While frequency regulation has traditionally been achieved by controlling generators, the control of Demand Response (DR) resources has been recognized in recent smart grid literature as an efficient means for providing additional regulation capability. To this end, several control methodologies have been proposed recently, but various features of these proposals make their practical implementations difficult. In this paper, we propose a new control algorithm that facilitates optimal frequency regulation through direct control of both generators and DR, while addressing several issues that prevent practical implementation of other proposals. In particular, i) our algorithm is ideal for control over a large, low-bandwidth network as communication and measurement is only required every 2 seconds, ii) it enables DR resources to recover energy lost during system transients, and iii) it allows the market to immediately respond to disturbances through feedback of the system frequency. We demonstrate the viability of our approach through dynamic simulations on a 118-bus grid model.\",\"PeriodicalId\":137983,\"journal\":{\"name\":\"2016 American Control Conference (ACC)\",\"volume\":\"55 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-07-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"18\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 American Control Conference (ACC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ACC.2016.7526740\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 American Control Conference (ACC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACC.2016.7526740","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A practical integration of automatic generation control and Demand Response
For a power grid to operate properly, electrical frequency must be continuously maintained close to its nominal value. Increasing penetration of distributed generation, such as solar and wind generation, introduces fluctuations in active power while also reducing the natural inertial response of the electricity grid, creating reliability concerns. While frequency regulation has traditionally been achieved by controlling generators, the control of Demand Response (DR) resources has been recognized in recent smart grid literature as an efficient means for providing additional regulation capability. To this end, several control methodologies have been proposed recently, but various features of these proposals make their practical implementations difficult. In this paper, we propose a new control algorithm that facilitates optimal frequency regulation through direct control of both generators and DR, while addressing several issues that prevent practical implementation of other proposals. In particular, i) our algorithm is ideal for control over a large, low-bandwidth network as communication and measurement is only required every 2 seconds, ii) it enables DR resources to recover energy lost during system transients, and iii) it allows the market to immediately respond to disturbances through feedback of the system frequency. We demonstrate the viability of our approach through dynamic simulations on a 118-bus grid model.