Systems and methods for making real-time predictions about an arc flash event on an electrical system are disclosed. An analytics server is communicatively connected to a data acquisition component. The analytics server comprises a virtual system modeling engine configured to create a virtual system model reflecting current network topology of the electrical system; an analytics engine configured to monitor predicted output data from the virtual system model and real-time output data from the electrical system acquired by the data acquisition component and update the virtual system model when a difference between the real-time output data and the predicted output data exceeds a threshold; and an arc flash simulation engine configured to forecast at least one aspect of and arc flash event based on the virtual system model.

The invention provides a computer simulation system for simulating a data centre. The simulation system uses a logical representation of the data centre to perform the simulation. This logical representation includes a plurality of nodes representing devices in the data center. Each node has an input for applied load and outputs for electrical power drawn and losses in the form of heat output. Each node also has a function for calculating the outputs from the inputs. A first set of connections between the nodes represent electrical power drawn by one device in the data center from another device in the data center. A second set of connections between the nodes represent a thermal load applied by one device in the data center to another device in the data center. The simulator can be run for a series of different operating conditions to map data center efficiency, for example, or to assess the impact of different IT devices on the data center.

A computer program product includes program instructions to: Receive a unit including register transfer level content for a component of an integrated circuit and one or more IP blocks; Select one or more input pins for each IP block; Assign a numerical value of either zero or one to each of the one or more input pins to yield at least one numerical sequence; For each numerical sequence, perform a check to yield a number of fails, wherein the check is formal verification of each of the one or more IP blocks; Determine a simulation condition for power modeling of the unit based on optimizing a numerical sequence with respect to the number of fails; Set the one or more input pins to the simulation condition for power modeling of the unit; and Determine a number of design errors of the unit based on the simulation condition.

The present invention relates to methods and systems for identifying PV system and solar irradiance sensor orientation and tilt based on energy production, energy received, simulated energy production, estimated energy received, production skew, and energy received skew. The present invention relates to systems and methods for detecting orientation and tilt of a PV system based on energy production and simulated energy production; for detecting the orientation and tilt of a solar irradiance sensor based on solar irradiance observation and simulated solar irradiance observation; for detecting orientation of a PV system based on energy production and energy production skew; and for detecting orientation of a solar irradiance sensor based on solar irradiance observation and solar irradiance observation skew.

A method of forecasting a resource load for consumption at a site, e.g., an electrical load of a site. The method includes receiving historical load data and historical ambient condition data that are time series data pertaining to a site and generating additional data from the received data. The method includes building a best sub-model for each of multiple forecast intervals. The building includes clustering in parallel training portions of the historical load data and the additional data, training possible sub-models using the clustered training portions, verifying forecasted loads output from the possible sub-models against verification portions of the historical load data and the additional data, and determining a first subset of parameters for the best sub-model based upon accuracy of the forecasted loads. The method includes forecasting a resource load at the site for each of the forecast intervals using an ensemble of the best sub-models.

Embodiments of a system and method are disclosed for providing a renewable energy network optimization tool. A method for optimizing a renewable energy network determines an initial configuration state, populates a pool of candidate sites for placement of renewable-energy generating units a hybrid simulated annealing-genetic algorithm, constructs a plurality of candidate renewable energy generation networks from the pool of candidate sites using random selection, evaluates the candidate renewable energy generation networks using scoring metrics, ranks the evaluated candidate renewable energy generation networks with respect to each other and prior iteration candidate renewable energy generation networks, adds candidate sites from a top ranked candidate renewable energy generation network to a list of candidate sites to be kept repeats the above until a final best candidate renewable energy generation network of kept sites is determined.

A system, method, or apparatus for generating a blast plan that can receive blast data comprising geological properties of a blast site, blasthole parameters, and available explosive product. A pattern footage can be determined based on a relationship between the face height, the specific energy of the available explosive product, and the geological properties of the bench. The burden and spacing can be determined from the pattern footage.

A system, method, or apparatus for generating a blast plan that can receive blast data comprising geological properties of a blast site, blasthole parameters, and available explosive product. A pattern footage can be determined based on a relationship between the face height, the specific energy of the available explosive product, and the geological properties of the bench. The burden and spacing can be determined from the pattern footage.