{"action":"created","issue":{"url":"https://api.github.com/repos/CalTRACK-2/caltrack/issues/85","repository_url":"https://api.github.com/repos/CalTRACK-2/caltrack","labels_url":"https://api.github.com/repos/CalTRACK-2/caltrack/issues/85/labels{/name}","comments_url":"https://api.github.com/repos/CalTRACK-2/caltrack/issues/85/comments","events_url":"https://api.github.com/repos/CalTRACK-2/caltrack/issues/85/events","html_url":"https://github.com/CalTRACK-2/caltrack/issues/85","id":312145590,"number":85,"title":"Hourly methods","user":{"login":"hshaban","id":13769526,"avatar_url":"https://avatars2.githubusercontent.com/u/13769526?v=4","gravatar_id":"","url":"https://api.github.com/users/hshaban","html_url":"https://github.com/hshaban","followers_url":"https://api.github.com/users/hshaban/followers","following_url":"https://api.github.com/users/hshaban/following{/other_user}","gists_url":"https://api.github.com/users/hshaban/gists{/gist_id}","starred_url":"https://api.github.com/users/hshaban/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/hshaban/subscriptions","organizations_url":"https://api.github.com/users/hshaban/orgs","repos_url":"https://api.github.com/users/hshaban/repos","events_url":"https://api.github.com/users/hshaban/events{/privacy}","received_events_url":"https://api.github.com/users/hshaban/received_events","type":"User","site_admin":false},"labels":[{"id":893272212,"url":"https://api.github.com/repos/CalTRACK-2/caltrack/labels/hourly-methods","name":"hourly-methods","color":"a4f9bd","default":false}],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":6,"created_at":"2018-04-06T23:11:14Z","updated_at":"2018-04-30T18:16:38Z","closed_at":null,"author_association":"COLLABORATOR","body":"Purpose of this task is to test and recommend methods that can handle hourly data and yield hourly results."},"comment":{"url":"https://api.github.com/repos/CalTRACK-2/caltrack/issues/comments/385483736","html_url":"https://github.com/CalTRACK-2/caltrack/issues/85#issuecomment-385483736","issue_url":"https://api.github.com/repos/CalTRACK-2/caltrack/issues/85","id":385483736,"user":{"login":"eliotcrowe","id":36049152,"avatar_url":"https://avatars3.githubusercontent.com/u/36049152?v=4","gravatar_id":"","url":"https://api.github.com/users/eliotcrowe","html_url":"https://github.com/eliotcrowe","followers_url":"https://api.github.com/users/eliotcrowe/followers","following_url":"https://api.github.com/users/eliotcrowe/following{/other_user}","gists_url":"https://api.github.com/users/eliotcrowe/gists{/gist_id}","starred_url":"https://api.github.com/users/eliotcrowe/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/eliotcrowe/subscriptions","organizations_url":"https://api.github.com/users/eliotcrowe/orgs","repos_url":"https://api.github.com/users/eliotcrowe/repos","events_url":"https://api.github.com/users/eliotcrowe/events{/privacy}","received_events_url":"https://api.github.com/users/eliotcrowe/received_events","type":"User","site_admin":false},"created_at":"2018-04-30T18:16:38Z","updated_at":"2018-04-30T18:16:38Z","author_association":"NONE","body":"@mcgeeyoung Funny, I was thinking exactly that over the weekend! I like this approach a lot, especially if aggregating data for many sites. A few thoughts:\r\n1. Curious what magnitude of true-up resulted when you tried this out? If it's significant then maybe we need to put more thought into the process/variables, but if it's minimal then maybe it's good to go\r\n2. I like how your chart splits up the loadshapes by month (a lot more meaningful than an annualized average), but some utilities/stakeholders might want to split up differently based on their rate structures, peak period definitions etc. Maybe Caltrack can define a standardized 8760-hour reporting format (and perhaps the true up process) which allows any stakeholder to manipulate the data into whatever chart or reporting format meets their needs - I'm sure it would be very simple as an Excel template. \r\n3. If converting the mass of data to hourly loadshapes I'd also recommend something like a box plot for each hour, so that you get a sense of predictive accuracy (lower for a single building, higher for a large portfolio). Doesn't have to be a boxplot but there should be some way to capture the variation"}}
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