@inproceedings{ fischer_recommending_2013,
  address = {New York, {NY}, {USA}},
  series = {{IUI} '13},
  title = {Recommending Energy Tariffs and Load Shifting Based on Smart Household Usage Profiling},
  isbn = {978-1-4503-1965-2},
  url = {http://doi.acm.org/10.1145/2449396.2449446},
  doi = {10.1145/2449396.2449446},
  abstract = {We present a system and study of personalized energy-related recommendation. {AgentSwitch} utilizes electricity usage data collected from users' households over a period of time to realize a range of smart energy-related recommendations on energy tariffs, load detection and usage shifting. The web service is driven by a third party real-time energy tariff {API} ({uSwitch}), an energy data store, a set of algorithms for usage prediction, and appliance-level load disaggregation. We present the system design and user evaluation consisting of interviews and interface walkthroughs. We recruited participants from a previous study during which three months of their household's energy use was recorded to evaluate personalized recommendations in {AgentSwitch}. Our contributions are a) a systems architecture for personalized energy services; and b) findings from the evaluation that reveal challenges in designing energy-related recommender systems. In response to the challenges we formulate design recommendations to mitigate barriers to switching tariffs, to incentivize load shifting, and to automate energy management.},
  urldate = {2014-10-06TZ},
  booktitle = {Proceedings of the 2013 International Conference on Intelligent User Interfaces},
  publisher = {{ACM}},
  author = {Fischer, Joel E. and Ramchurn, Sarvapali D. and Osborne, Michael and Parson, Oliver and Huynh, Trung Dong and Alam, Muddasser and Pantidi, Nadia and Moran, Stuart and Bachour, Khaled and Reece, Steve and Costanza, Enrico and Rodden, Tom and Jennings, Nicholas R.},
  year = {2013},
  keywords = {demand response, energy tariffs, load shifting, personalization, recommender systems, smart grid},
  pages = {383--394}
}

{"_id":"zsd28FXLk4MhHyfxd","authorIDs":[],"author_short":["Fischer, J.<nbsp>E.","Ramchurn, S.<nbsp>D.","Osborne, M.","Parson, O.","Huynh","Dong, T.","Alam, M.","Pantidi, N.","Moran, S.","Bachour, K.","Reece, S.","Costanza, E.","Rodden, T.","Jennings, N.<nbsp>R."],"bibbaseid":"fischer-ramchurn-osborne-parson-huynh-dong-alam-pantidi-moran-bachour-reece-costanza-rodden-jennings-recommendingenergytariffsandloadshiftingbasedonsmarthouseholdusageprofiling-2013","bibdata":{"abstract":"We present a system and study of personalized energy-related recommendation. AgentSwitch utilizes electricity usage data collected from users' households over a period of time to realize a range of smart energy-related recommendations on energy tariffs, load detection and usage shifting. The web service is driven by a third party real-time energy tariff API (uSwitch), an energy data store, a set of algorithms for usage prediction, and appliance-level load disaggregation. We present the system design and user evaluation consisting of interviews and interface walkthroughs. We recruited participants from a previous study during which three months of their household's energy use was recorded to evaluate personalized recommendations in AgentSwitch. Our contributions are a) a systems architecture for personalized energy services; and b) findings from the evaluation that reveal challenges in designing energy-related recommender systems. In response to the challenges we formulate design recommendations to mitigate barriers to switching tariffs, to incentivize load shifting, and to automate energy management.","address":"New York, NY, USA","author":["Fischer, Joel E.","Ramchurn, Sarvapali D.","Osborne, Michael","Parson, Oliver","Huynh","Dong, Trung","Alam, Muddasser","Pantidi, Nadia","Moran, Stuart","Bachour, Khaled","Reece, Steve","Costanza, Enrico","Rodden, Tom","Jennings, Nicholas R."],"author_short":["Fischer, J.<nbsp>E.","Ramchurn, S.<nbsp>D.","Osborne, M.","Parson, O.","Huynh","Dong, T.","Alam, M.","Pantidi, N.","Moran, S.","Bachour, K.","Reece, S.","Costanza, E.","Rodden, T.","Jennings, N.<nbsp>R."],"bibtex":"@inproceedings{ fischer_recommending_2013,\n address = {New York, {NY}, {USA}},\n series = {{IUI} '13},\n title = {Recommending Energy Tariffs and Load Shifting Based on Smart Household Usage Profiling},\n isbn = {978-1-4503-1965-2},\n url = {http://doi.acm.org/10.1145/2449396.2449446},\n doi = {10.1145/2449396.2449446},\n abstract = {We present a system and study of personalized energy-related recommendation. {AgentSwitch} utilizes electricity usage data collected from users' households over a period of time to realize a range of smart energy-related recommendations on energy tariffs, load detection and usage shifting. The web service is driven by a third party real-time energy tariff {API} ({uSwitch}), an energy data store, a set of algorithms for usage prediction, and appliance-level load disaggregation. We present the system design and user evaluation consisting of interviews and interface walkthroughs. We recruited participants from a previous study during which three months of their household's energy use was recorded to evaluate personalized recommendations in {AgentSwitch}. Our contributions are a) a systems architecture for personalized energy services; and b) findings from the evaluation that reveal challenges in designing energy-related recommender systems. In response to the challenges we formulate design recommendations to mitigate barriers to switching tariffs, to incentivize load shifting, and to automate energy management.},\n urldate = {2014-10-06TZ},\n booktitle = {Proceedings of the 2013 International Conference on Intelligent User Interfaces},\n publisher = {{ACM}},\n author = {Fischer, Joel E. and Ramchurn, Sarvapali D. and Osborne, Michael and Parson, Oliver and Huynh, Trung Dong and Alam, Muddasser and Pantidi, Nadia and Moran, Stuart and Bachour, Khaled and Reece, Steve and Costanza, Enrico and Rodden, Tom and Jennings, Nicholas R.},\n year = {2013},\n keywords = {demand response, energy tariffs, load shifting, personalization, recommender systems, smart grid},\n pages = {383--394}\n}","bibtype":"inproceedings","booktitle":"Proceedings of the 2013 International Conference on Intelligent User Interfaces","doi":"10.1145/2449396.2449446","id":"fischer_recommending_2013","isbn":"978-1-4503-1965-2","key":"fischer_recommending_2013","keywords":"demand response, energy tariffs, load shifting, personalization, recommender systems, smart grid","pages":"383--394","publisher":"ACM","series":"IUI '13","title":"Recommending Energy Tariffs and Load Shifting Based on Smart Household Usage Profiling","type":"inproceedings","url":"http://doi.acm.org/10.1145/2449396.2449446","urldate":"2014-10-06TZ","year":"2013","bibbaseid":"fischer-ramchurn-osborne-parson-huynh-dong-alam-pantidi-moran-bachour-reece-costanza-rodden-jennings-recommendingenergytariffsandloadshiftingbasedonsmarthouseholdusageprofiling-2013","role":"author","urls":{"Paper":"http://doi.acm.org/10.1145/2449396.2449446"},"keyword":["demand response","energy tariffs","load shifting","personalization","recommender systems","smart grid"],"downloads":0,"html":""},"bibtype":"inproceedings","biburl":"http://bibbase.org/zotero/alspereira","creationDate":"2014-12-11T16:27:23.699Z","downloads":0,"keywords":["demand response","energy tariffs","load shifting","personalization","recommender systems","smart grid"],"search_terms":["recommending","energy","tariffs","load","shifting","based","smart","household","usage","profiling","fischer","ramchurn","osborne","parson","huynh","dong","alam","pantidi","moran","bachour","reece","costanza","rodden","jennings"],"title":"Recommending Energy Tariffs and Load Shifting Based on Smart Household Usage Profiling","year":2013,"dataSources":["ndsqabutJ3xHr3adK"]}