{"title":"基于智能代理的ABT状态下发电机组调度优化体系结构","authors":"B. Parekh, S. Sharma, P. Sharma","doi":"10.1109/POWERCON.2012.6401386","DOIUrl":null,"url":null,"abstract":"Information technology played an important role in information and knowledge dissemination in the last decade in the almost all the domains through the development of internet, wireless, satellites and mobile based intelligent knowledge based information system. These systems need timely expert advice to make them more productive and competitive. By implementing them as knowledge servers, it becomes economically feasible, profitable, and beneficial to users to share knowledge. The Indian tariff structure for power generation utilities has also undergone major revision under the ABT regime. As a result, the operation philosophy employed by power generation utilities also has undergone change under the ABT. The proposed solution aims to help the end user (as a large power generation utility) to manage their resources in the most optimal and economic fashion under the new regime. Scheduling implies drawing up a generation program to cater to forecast power demand at a minimum cost subject to transmission system constraints, capability of generating units & other factors (e.g. voltage profile, system security & system sustainability under grid disturbance). Architecture for Optimization of Generator Scheduling under ABT Regime Using Intelligent Agents is proposed involving Tariff modeling engine, Generation scheduling engine, Generation target achievement engine, etc.","PeriodicalId":176214,"journal":{"name":"2012 IEEE International Conference on Power System Technology (POWERCON)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Architecture for optimization of generator scheduling under ABT regime using intelligent agents\",\"authors\":\"B. Parekh, S. Sharma, P. Sharma\",\"doi\":\"10.1109/POWERCON.2012.6401386\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Information technology played an important role in information and knowledge dissemination in the last decade in the almost all the domains through the development of internet, wireless, satellites and mobile based intelligent knowledge based information system. These systems need timely expert advice to make them more productive and competitive. By implementing them as knowledge servers, it becomes economically feasible, profitable, and beneficial to users to share knowledge. The Indian tariff structure for power generation utilities has also undergone major revision under the ABT regime. As a result, the operation philosophy employed by power generation utilities also has undergone change under the ABT. The proposed solution aims to help the end user (as a large power generation utility) to manage their resources in the most optimal and economic fashion under the new regime. Scheduling implies drawing up a generation program to cater to forecast power demand at a minimum cost subject to transmission system constraints, capability of generating units & other factors (e.g. voltage profile, system security & system sustainability under grid disturbance). Architecture for Optimization of Generator Scheduling under ABT Regime Using Intelligent Agents is proposed involving Tariff modeling engine, Generation scheduling engine, Generation target achievement engine, etc.\",\"PeriodicalId\":176214,\"journal\":{\"name\":\"2012 IEEE International Conference on Power System Technology (POWERCON)\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE International Conference on Power System Technology (POWERCON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/POWERCON.2012.6401386\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE International Conference on Power System Technology (POWERCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/POWERCON.2012.6401386","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Architecture for optimization of generator scheduling under ABT regime using intelligent agents
Information technology played an important role in information and knowledge dissemination in the last decade in the almost all the domains through the development of internet, wireless, satellites and mobile based intelligent knowledge based information system. These systems need timely expert advice to make them more productive and competitive. By implementing them as knowledge servers, it becomes economically feasible, profitable, and beneficial to users to share knowledge. The Indian tariff structure for power generation utilities has also undergone major revision under the ABT regime. As a result, the operation philosophy employed by power generation utilities also has undergone change under the ABT. The proposed solution aims to help the end user (as a large power generation utility) to manage their resources in the most optimal and economic fashion under the new regime. Scheduling implies drawing up a generation program to cater to forecast power demand at a minimum cost subject to transmission system constraints, capability of generating units & other factors (e.g. voltage profile, system security & system sustainability under grid disturbance). Architecture for Optimization of Generator Scheduling under ABT Regime Using Intelligent Agents is proposed involving Tariff modeling engine, Generation scheduling engine, Generation target achievement engine, etc.