{"title":"Optimal planning and design of Distributed Generation based micro-grids","authors":"P. Mohanty, G. Bhuvaneswari, R. Balasubramanian","doi":"10.1109/ICIINFS.2012.6304823","DOIUrl":null,"url":null,"abstract":"Spiraling power demand, huge transmission and distribution (T&D) losses, providing quality and reliable power to the far-flunged, remote, dispersed populations have been a challenge and apparently has triggered research about alternative solutions. Against this backdrop, Distributed Generation (DG)/Renewable Energy (RE) based micro-grids are considered as one of the feasible options. Distributed Energy Resources (DER) can, not only deliver power to the local areas (where it is installed and distributed) more efficiently and reliably, but it can also feed excess power, if any, to the utility grid. In a micro-grid setup, the optimum planning and control of the micro-grid is a key to maximizing the potential benefits of the real world micro-grid installation. In this paper, the authors attempt to develop an optimal design and planning of a micro-grid considering various distributed energy technology options such as solar Photovoltaic (SPV), small wind electric generator, biomass gasifier system, diesel generator and battery storage for different applications and with realistic inputs on their physical, operating and economic characteristics. The objective of this paper is to come out with many such optimal micro-grids with various combinations of renewable energy resources with optimal dispatch strategies for different applications while minimizing the cost. The paper also presents the findings of the performance profiles of various micro-grid configurations under different operational scenarios and also determines break-even distance for connecting the micro-grid with the main grid, and compares that with the cost of the isolated micro-grid.","PeriodicalId":171993,"journal":{"name":"2012 IEEE 7th International Conference on Industrial and Information Systems (ICIIS)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE 7th International Conference on Industrial and Information Systems (ICIIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIINFS.2012.6304823","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17
Abstract
Spiraling power demand, huge transmission and distribution (T&D) losses, providing quality and reliable power to the far-flunged, remote, dispersed populations have been a challenge and apparently has triggered research about alternative solutions. Against this backdrop, Distributed Generation (DG)/Renewable Energy (RE) based micro-grids are considered as one of the feasible options. Distributed Energy Resources (DER) can, not only deliver power to the local areas (where it is installed and distributed) more efficiently and reliably, but it can also feed excess power, if any, to the utility grid. In a micro-grid setup, the optimum planning and control of the micro-grid is a key to maximizing the potential benefits of the real world micro-grid installation. In this paper, the authors attempt to develop an optimal design and planning of a micro-grid considering various distributed energy technology options such as solar Photovoltaic (SPV), small wind electric generator, biomass gasifier system, diesel generator and battery storage for different applications and with realistic inputs on their physical, operating and economic characteristics. The objective of this paper is to come out with many such optimal micro-grids with various combinations of renewable energy resources with optimal dispatch strategies for different applications while minimizing the cost. The paper also presents the findings of the performance profiles of various micro-grid configurations under different operational scenarios and also determines break-even distance for connecting the micro-grid with the main grid, and compares that with the cost of the isolated micro-grid.