{"title":"考虑斜坡要求的最佳储能辅助风力发电集成","authors":"Lin Xiang, D. W. K. Ng, Woongsup Lee, R. Schober","doi":"10.1109/SmartGridComm.2013.6688032","DOIUrl":null,"url":null,"abstract":"Large-scale integration of intermittent wind energy can put a large burden on the utility company in balancing system demand and supply. As more and more dispersed wind energy suppliers connect to the system for electricity supply, the power system suffers from increased operation cost and risk caused by the discrepant interests of energy suppliers and the utility company. Energy suppliers may only concern about maximizing their own profits by pushing as much energy into the grid as possible, while neglecting the risk of steep ramps in wind generation. In this paper, exploiting the two-way communication capability in smart grid, we propose interactive ramp control of wind energy integration by aligning the individual pursuits of the energy suppliers and the utility company for social welfare maximization. The optimal wind energy integration and generator ramp control are investigated in an offline social welfare optimization problem assuming full knowledge of future wind energy and load demand. Moreover, the benefits of storage are exploited in our proposed storage-aided generation range adaption scheme to reduce the potential risk caused by inaccurate wind energy forecasts and the ramping latency of slow generators. Furthermore, a suboptimal storage-aided generation range adaption scheme with low computational complexity is presented for online control of wind integration when wind energy forecasts are unavailable. Our simulation results show that interactive ramp control is necessary to achieve efficient and secure wind energy integration and with the aid of storage, the power system's ramping capability can be improved at lower operation cost.","PeriodicalId":136434,"journal":{"name":"2013 IEEE International Conference on Smart Grid Communications (SmartGridComm)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Optimal storage-aided wind generation integration considering ramping requirements\",\"authors\":\"Lin Xiang, D. W. K. Ng, Woongsup Lee, R. Schober\",\"doi\":\"10.1109/SmartGridComm.2013.6688032\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Large-scale integration of intermittent wind energy can put a large burden on the utility company in balancing system demand and supply. As more and more dispersed wind energy suppliers connect to the system for electricity supply, the power system suffers from increased operation cost and risk caused by the discrepant interests of energy suppliers and the utility company. Energy suppliers may only concern about maximizing their own profits by pushing as much energy into the grid as possible, while neglecting the risk of steep ramps in wind generation. In this paper, exploiting the two-way communication capability in smart grid, we propose interactive ramp control of wind energy integration by aligning the individual pursuits of the energy suppliers and the utility company for social welfare maximization. The optimal wind energy integration and generator ramp control are investigated in an offline social welfare optimization problem assuming full knowledge of future wind energy and load demand. Moreover, the benefits of storage are exploited in our proposed storage-aided generation range adaption scheme to reduce the potential risk caused by inaccurate wind energy forecasts and the ramping latency of slow generators. Furthermore, a suboptimal storage-aided generation range adaption scheme with low computational complexity is presented for online control of wind integration when wind energy forecasts are unavailable. Our simulation results show that interactive ramp control is necessary to achieve efficient and secure wind energy integration and with the aid of storage, the power system's ramping capability can be improved at lower operation cost.\",\"PeriodicalId\":136434,\"journal\":{\"name\":\"2013 IEEE International Conference on Smart Grid Communications (SmartGridComm)\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE International Conference on Smart Grid Communications (SmartGridComm)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SmartGridComm.2013.6688032\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Conference on Smart Grid Communications (SmartGridComm)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SmartGridComm.2013.6688032","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Large-scale integration of intermittent wind energy can put a large burden on the utility company in balancing system demand and supply. As more and more dispersed wind energy suppliers connect to the system for electricity supply, the power system suffers from increased operation cost and risk caused by the discrepant interests of energy suppliers and the utility company. Energy suppliers may only concern about maximizing their own profits by pushing as much energy into the grid as possible, while neglecting the risk of steep ramps in wind generation. In this paper, exploiting the two-way communication capability in smart grid, we propose interactive ramp control of wind energy integration by aligning the individual pursuits of the energy suppliers and the utility company for social welfare maximization. The optimal wind energy integration and generator ramp control are investigated in an offline social welfare optimization problem assuming full knowledge of future wind energy and load demand. Moreover, the benefits of storage are exploited in our proposed storage-aided generation range adaption scheme to reduce the potential risk caused by inaccurate wind energy forecasts and the ramping latency of slow generators. Furthermore, a suboptimal storage-aided generation range adaption scheme with low computational complexity is presented for online control of wind integration when wind energy forecasts are unavailable. Our simulation results show that interactive ramp control is necessary to achieve efficient and secure wind energy integration and with the aid of storage, the power system's ramping capability can be improved at lower operation cost.