Abstract: Example embodiments relate to providing visual analytics of temporal-spatial relationships. In example embodiments, power meters may be located at regions within a building for collecting power consumption data at regular intervals. The power consumption data can be recursively processed to generate a pixel calendar tree by using a power meter hierarchy to subdivide the pixel calendar tree into tree portions according to a proportion of the power consumption data attributed to each of power meter nodes, where the tree portions are arranged in the pixel calendar tree according to an importance of the proportion; generating pixel cells in the pixel calendar tree that each represent a day in the power consumption data; and generating cell borders that each surround one of the pixel cells. At this stage, a pixel calendar display of a physical infrastructure of the building that includes the pixel cells and the cell borders can be generated.

Abstract: Examples of meter data management testing are disclosed. In one example implementation according to aspects of the present disclosure, a computing device may include one or more processors, a memory for storing machine readable instructions, and a data store. The computing device may further include a meter data management testing module stored in the memory and executing on at least one of the one or more processors to test a meter data management system using a data set of representative metering data and a user-generated test scenario specifying a plurality of metering parameters.

Abstract: Example embodiments relate to providing visual analytics of spatial time series data. In example embodiments, sensors may be located at regions within a building for collecting sensor data at regular time intervals. A sensor hierarchy can be generated including sensor nodes that are hierarchically arranged according to a physical infrastructure of the building, where each of the sensor nodes corresponds to a sensor. Sensor data can be obtained from the sensors, and a pixel calendar tree can be generated based on the sensor data and the sensor hierarchy, where the pixel calendar tree is recursively subdivided into tree portions according to a proportion of the sensor data attributable to each of the sensors. The pixel calendar tree can be displayed, where each of the tree portions includes time series sensor data of a corresponding region that is generated based on the sensor data.

Abstract: Example embodiments relate to device monitoring. In one example implementation according to aspects of the present disclosure, a computing device may include one or more processors, a memory for storing machine readable instructions, and a data store. Additionally, the computing device may include a utility device monitoring module stored in the memory and executing on at least one of the one or more processors to passively monitor network information and power information from a utility device communicatively coupled to a network and a power source.

Abstract: According to an example, synthetic time series data generation may include receiving time series data for a plurality of users, and applying dimensionality reduction to transform the time series data from a high dimensional space n of the time series data to a low dimensional space m, where m<n. The transformed time series data may be used to estimate a time series data density in the low dimensional space m by generating a density function. The density function may be sampled for data, and the sampled data may be transformed back to the high dimensional space n to generate the synthetic time series data.

Abstract: According to an example, synthetic time series data generation may include receiving empirical meter data for a plurality of users, and using the empirical meter data to estimate parameters of a Markov chain. The Markov chain may be used to generate the synthetic time series data having statistical properties similar to the statistical properties of the empirical meter data.

Abstract: In a method for managing a facility that is to receive resources from a first resource supply, a supply of resources available from the first resource supply is predicted for a predetermined period of time. In addition, a demand for resources in the facility during the predetermined period of time is predicted. A capacity schedule for the facility is planned to meet a predefined operational goal, in which the plan of the capacity schedule uses as inputs, the predicted supply of resources available from the first resource supply and the predicted demand for resources in the facility during the predetermined period of time. Moreover, a determination as to whether the planned capacity schedule meets the predefined operational goal is made.

Abstract: In an embodiment, a device characterization system includes a sensor to sense an attribute of a device, a processor, and an algorithm executable on the processor to collect time series data of the attribute from the sensor, detect edges in the data, identify clusters from the edges, label the clusters based on input from a supervisor, and estimate device characterization parameters from the clusters.

Abstract: Tree discovery systems and methods are disclosed. An example of a method is carried out by program code stored on non-transient computer-readable medium and executed by a processor. The method may include identifying in computer-readable medium a first node for a system under consideration, each node in the computer-readable medium representing a characteristic of a component. The method may include selecting at least a second node from the computer-readable medium for the first node. The method may include discovering in the computer-readable medium at least one system tree for the system under consideration based on the first node and the at least second node.

Abstract: Systems and methods of disaggregating power load are provided. An example of a method is carried out by program code stored on non-transient computer-readable medium and executed by a processor. The method includes receiving time series data representing total energy consumption. The method also includes identifying distinguishing features in the time series data. The method also includes identifying energy consumption constituents of the total energy consumption based on the features.

Abstract: In a method for supplying a resource to an entity from a resource actuator, a plurality of physics-based models pertaining to the resource actuator and the entity are developed, a condition detected at the entity is received, feedback control on a resource demand of the entity employed based upon the detected condition, feed forward control on the resource demand of the entity is employed based upon the detected condition and the plurality of physics-based models, a constraint optimization problem having an objective function and at least one constraint using the plurality of physics-based models is formulated, a solution to the constraint optimization problem is determined, in which the solution provides the actuator setting, and the resource actuator is set to the actuator setting to supply the entity with the resource from the resource actuator.

Abstract: Tree assessment systems and methods are disclosed. An example of a method includes building a system tree in computer-readable medium, the system tree having a plurality of nodes, each node in the system tree representing a characteristic of a component of a system under consideration. The method also includes comparing nodes of the system tree stored in computer-readable medium, with nodes in other trees to identify at least one similar node for identifying similar trees. The method also includes extracting extracting a most similar tree from the similar trees based on the at least one similar node. The method also includes assigning characteristics from the most similar tree to the system tree.

Abstract: In one implementation, an interactive service management system includes a performance profile module and a performance evaluation module. The performance profile modules defines a performance measure of an interactive service based on a quality assessment associated with the interactive service. The performance evaluation module compares the performance measure with performance target associated with the interactive service, and modifies the performance target associated with the interactive service based on the comparison of the performance measure and the performance target.

Abstract: Systems and automated methods for predicting photovoltaic (PV) generation are provided. Weather forecast data and present-day and historical PV generation data are provided to respective predictors. The predictors derive weighted predictions that are used to calculate a Bayesian model average. Near-future generation by the PV system is predicted using the Bayesian model average. Production rates, worker scheduling, hours of operation and other planning decisions can be made in accordance with the predicted near-future generation.

Abstract: Methods, apparatus and articles of manufacture to shift information technology workload demands are disclosed. An example method disclosed herein comprises obtaining demand profiles for workloads in an information technology infrastructure, each demand profile representing resource utilization over time to support a respective workload, and evaluating the demand profiles to shift, in time, assignment of at least one of the workloads to resources of the information technology infrastructure based on a target demand profile for an aggregation of the workloads.

Abstract: A method executed by a system having a processor includes arranging pixels representing attributes into a plurality of rings. Each ring contains pixels representing a time series of attribute values for a respective one of the attributes. The method further includes providing a peak detection ring. The peak detection ring includes visual indicators for indicating a location of at least one peak in an attribute in the plurality of rings.

Abstract: An identification of a constituent component is received. In response to receiving the identification, an estimated quantity of the constituent component in a product mix is determined, where the determining is based on bills of materials for corresponding product assemblies, and a data structure that stores information containing at least one metric for each of a plurality of components, the at least one metric indicating an impact of the corresponding component on an environment.

Abstract: Data points contain data values in respective time intervals. Pixels representing data points for time periods (each time period including multiple time intervals) are placed in corresponding discrete rings in a graphical visualization, wherein the pixels are user accessible to allow viewing of information of the corresponding data points. The pixels are temporally aligned in the corresponding discrete rings, and the pixels in the corresponding discrete rings are variably sized depending on a number of data points in the respective time periods.

Abstract: In a method for determining operational settings for a plurality of fluid moving devices, one or more motifs in utilization data of the plurality of fluid moving devices collected over a time series is identified as a multivariate time series of data, sustainability metric levels for each of the one or more identified motifs are calculated, and a determination as to which of the one or more identified motifs have favorable sustainability metric levels is made.

Abstract: Systems and methods of determining node similarity for component substitution. An example of a method may be carried out by program code stored on non-transient computer-readable medium and executed by a processor. The method includes estimating a normalized similarity metric between the plurality of nodes in the system tree and nodes in other trees. The method also includes assigning a similarity score to each compared node using at least one of: domain based rules, attribute based similarity metrics, and machine learning. The method also includes combining results for cluster analysis.