Danish Mahmood, N. Javaid, Umar Nouman, Afaq Urrahman, Z. Khan, U. Qasim
{"title":"Comparative Analysis of Energy Management Solutions Focusing Practical Implementation","authors":"Danish Mahmood, N. Javaid, Umar Nouman, Afaq Urrahman, Z. Khan, U. Qasim","doi":"10.1109/CISIS.2016.126","DOIUrl":null,"url":null,"abstract":"This work analyzes major energy management solutions in terms of their practical implementation. Every EMS proposed has its own merits and demerits. Energy management solutions are based upon 4 major categories i.e., EMS by a sensor network, EMS by using optimization technique, EMS by merging sensory information with optimization algorithm to yield better energy efficiency and integrating small scale micro grids at demand side to optimize energy preservation. Load shifting to low peak or low priced hours in such a way that user comfort is not much compromised is an NP-hard problem. Nature inspired evolutionary algorithms proves their worth in solving such problems. In this work, we focus mainly on energy and cost optimization with respect to above mentioned all categories that provide energy management solutions. Extensive simulations are conducted regarding each catagory to investigate impact of each regarding cost and energy savings.","PeriodicalId":249236,"journal":{"name":"2016 10th International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS)","volume":"265 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 10th International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISIS.2016.126","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
This work analyzes major energy management solutions in terms of their practical implementation. Every EMS proposed has its own merits and demerits. Energy management solutions are based upon 4 major categories i.e., EMS by a sensor network, EMS by using optimization technique, EMS by merging sensory information with optimization algorithm to yield better energy efficiency and integrating small scale micro grids at demand side to optimize energy preservation. Load shifting to low peak or low priced hours in such a way that user comfort is not much compromised is an NP-hard problem. Nature inspired evolutionary algorithms proves their worth in solving such problems. In this work, we focus mainly on energy and cost optimization with respect to above mentioned all categories that provide energy management solutions. Extensive simulations are conducted regarding each catagory to investigate impact of each regarding cost and energy savings.