Abstract: Disclosed herein is a belt tension measuring device utilizing a first end roller, the first end roller supporting the belt; a second end roller having an axis of rotation parallel to the first end roller; a support arm pivotably mounted to pivot about an axis parallel to the axis of rotation of the first end roller; a deflection roller rotatably mounted to the support arm at a distance from the pivot of the support arm; the deflection roller having a rotational axis parallel to the axis of rotation of the first end roller, the roller resting upon the belt, configured to bias the belt against the first roller and second roller; and a position indicator measuring the distance between the axis of the deflection roller and a line drawn between the axis of rotation of the first end roller and the axis of rotation of the second end roller.

Abstract: An apparatus includes a processor to: assign each value of each set of values of an initial supply meter data and of an initial load meter data to one of multiple buckets based on weather conditions and/or time and date; for each bucket, generate upper and lower bounds of power provision and power consumption values, and use the upper and lower bounds to identify outlier values assigned to the bucket; for each set of values within the initial supply meter data and within the initial load meter data, generate a naive model from the non-outlier values, and use interpolation and the naive model to fill in gaps, thereby generating cleansed supply meter data and cleansed load meter data; and store the cleansed supply meter data and cleansed load meter data together as merged meter data for use in making predictions.

Abstract: An apparatus includes a processor to: assign each value of each set of values of an initial supply meter data and of an initial load meter data to one of multiple buckets based on weather conditions and/or time and date; for each bucket, generate upper and lower bounds of power provision and power consumption values, and use the upper and lower bounds to identify outlier values assigned to the bucket; for each set of values within the initial supply meter data and within the initial load meter data, generate a naive model from the non-outlier values, and use interpolation and the naive model to fill in gaps, thereby generating cleansed supply meter data and cleansed load meter data; and store the cleansed supply meter data and cleansed load meter data together as merged meter data for use in making predictions.