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dc.contributor.advisorTony Hu.en_US
dc.contributor.authorAmarasinghe, Saluka.en_US
dc.contributor.otherMassachusetts Institute of Technology. Engineering and Management Program.en_US
dc.contributor.otherSystem Design and Management Program.en_US
dc.date.accessioned2019-09-26T19:53:27Z
dc.date.available2019-09-26T19:53:27Z
dc.date.copyright2019en_US
dc.date.issued2019en_US
dc.identifier.urihttps://hdl.handle.net/1721.1/122315
dc.descriptionThesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, System Design and Management Program, 2019en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 84-85).en_US
dc.description.abstractMost household consumers in the US are unaware of their electrical usage or the price of electricity until they receive their monthly bill. However, they are concerned about being "wasteful" when it comes to electricity use. But most consumers have no idea what being wasteful means. What if there was a way to show residential consumers their real-time electrical usage in terms of price or in terms of environmental emissions from non-renewable power plants? Would this appeal to their concerns about wastefulness and cause them to change their behavior with household appliance use? To test this question an experiment was designed, and multiple prototypes were built. The experiment consisted of a prototype showing a traffic light color pattern of two lights. The first light indicated the price/emissions metric chosen based on user allegiance. The second light indicated the usage of electricity in their home.en_US
dc.description.abstractAfter running this experiment, the key takeaway was that that consumers will change their electrical usage behavior based on a metric that matters to them but will not compromise comfort or convenience over price or emissions. Electric energy trading in the US is a complicated system and fundamentally a business. Electrical energy is predicted and traded the day before, generally using clean energy sources in the US. However, if there is a surge in demand on the predicted day, dirty power is turned on. A dirty power plant is classified as being harmful to the environment by burning coal or oil. Dirty power plants are also expensive to the consumer and inefficient in the electric grid but can be turned on instantly in times of need. Because of this, the trading system is designed to minimize the use of dirty power. The electricity trading models follow a principle called the "duck curve".en_US
dc.description.abstractThe duck curve is a graph of power production over the course of a day that shows the timing imbalance between peak demand and renewable energy production. Generally, grid usage follows the duck curve.en_US
dc.description.statementofresponsibilityby Saluka Amarasinghe.en_US
dc.format.extent104 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectEngineering and Management Program.en_US
dc.subjectSystem Design and Management Program.en_US
dc.titleChanging user behavior with home electricity use to reduce and shift the demand on the electric griden_US
dc.typeThesisen_US
dc.description.degreeS.M. in Engineering and Managementen_US
dc.contributor.departmentMassachusetts Institute of Technology. Engineering and Management Programen_US
dc.contributor.departmentSystem Design and Management Programen_US
dc.identifier.oclc1119390486en_US
dc.description.collectionS.M.inEngineeringandManagement Massachusetts Institute of Technology, System Design and Management Programen_US
dspace.imported2019-09-26T19:53:24Zen_US
mit.thesis.degreeMasteren_US
mit.thesis.departmentSysDesen_US


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