Abstract: A system and method for energy optimization is disclosed. The system may collect information from an information collector data including energy usage and storage data of at least one renewable energy generation system and battery energy storage system (BESS). The system may identify historical events that result in curtailment of renewable energy production, determine whether there is a curtailment of renewable energy production based at least on one historical event supervise the charge and discharge cycles of the at least one BESS; and ensuring that the diesel generators minimum up/down time is satisfied based on controlling at least one parameter of the BESS.

Abstract: A system for controlling air flow in an air handling unit having an air mover is provided. The system includes a first and a second sensing device, each receiving a first input indicative of electric power and a second input indicative of properties of air, respectively. The system further includes a processing unit to determine heat generated from a motor of the air mover based on the first input, determine density of air based on the heat generated from the motor based on the second input, and determine an actual air flow rate based on the density of the air, a speed of the motor, and dimensional characteristics of the air handling unit. Further, the speed of the motor is controlled when the actual air flow rate is different from a target air flow rate.

Abstract: A feedback gain and a speed feed-forward gain are adjusted. A method for adjusting control parameters for a control device that performs servo control on a control target includes calculating an upper limit of a feedback gain of a feedback signal within a range in which a predetermined index for the feedback gain satisfies a predetermined target value with a speed feed-forward gain for speed feed-forward control set at a predetermined reference value, setting the feedback gain at an adjustment initial value lower than the upper limit, setting the speed feed-forward gain at the highest value within a settable range, and increasing the feedback gain from the adjustment initial value within a range in which the feedback gain does not exceed the upper limit with at least the speed feed-forward gain set at a predetermined increased value.

Abstract: Methods and apparatus for controlling a characteristic of a cement slurry at a cementing unit, including regulating a characteristic of the cement slurry employing a closed loop feedback arrangement in the cementing unit, and adjusting a gain of the closed loop feedback arrangement in response to sampling an error of the characteristic.

Abstract: A heating, ventilation, and air conditioning (HVAC) control device configured to receive a user input for controlling an HVAC system, to determine whether the user input indicates an energy saving occupancy setting, and to identify a first plurality of time entries that are associated with a confidence level for a predicted occupancy status that is less than a predetermined threshold value in the predicted occupancy schedule. The device is further configured to modify the predicted occupancy schedule by setting the first plurality of time entries to an away status when the user input indicates an aggressive energy saving occupancy setting. The device is further configured to modify the predicted occupancy schedule by setting the second plurality of time entries to a present status when the user input indicates a conservative energy saving occupancy setting. The device is further configured to output the modified predicted occupancy schedule.

Abstract: A graph display device according to one aspect of the present invention generates a first directed graph, which contains a plurality of first nodes respectively representing device variables, edges representing the existence of a dependency relation, and a block representing a function, and a second directed graph, which contains a plurality of first nodes, edges, a block, and a plurality of second nodes arranged in the block and respectively representing function parameters. In response to an instruction from a user the display device switches between displaying the generated first directed graph and displaying the generated second directed graph.

Abstract: Controlling heating and cooling in a conditioned space utilizes a fluid circulating in a thermally conductive structure in fluid connection with a hydronic-to-air heat exchanger and a ground heat exchanger. Air is moved past the hydronic-to-air heat exchanger, the air having fresh air supply and stale air exhaust. Sensors located throughout the conditioned space send data to a controller. User input to the controller sets the desired set point temperature and humidity. Based upon the set point temperature and humidity and sensor data, the controller sends signals to various devices to manipulate the flow of the fluid and the air in order to achieve the desired set point temperature and humidity in the conditioned space. The temperature of the fluid is kept less than the dew point at the hydronic-to-air heat exchanger and the temperature of the fluid is kept greater than the dew point at the thermally conductive structure.

Abstract: A heating, ventilation, and air conditioning (HVAC) control device configured to receive a user input for controlling an HVAC system, to determine whether the user input indicates an energy saving occupancy setting, and to identify a first plurality of time entries that are associated with a confidence level for a predicted occupancy status that is less than a predetermined threshold value in the predicted occupancy schedule. The device is further configured to modify the predicted occupancy schedule by setting the first plurality of time entries to an away status when the user input indicates an aggressive energy saving occupancy setting. The device is further configured to modify the predicted occupancy schedule by setting the second plurality of time entries to a present status when the user input indicates a conservative energy saving occupancy setting. The device is further configured to output the modified predicted occupancy schedule.

Abstract: A building management system includes building equipment operable to affect a physical state of a building. The building management system includes a system manager coupled to the building equipment via a system bus, the system manager comprising a schedule manager configured to control an operation schedule of the building equipment. A client device is configured to communicate with the schedule manager to modify operation schedules of the building equipment or add new operation schedules for the building equipment. The schedule manager comprises a list of available schedules for the building equipment and is configured to, in response to modification of the operation schedules or addition of new operation schedules, update the list of available schedules to include the modification or the new operation schedule.

Abstract: Certain aspects of the present disclosure relate to a system including a first active control device, comprising: a flow control element; one or more sensors; a network interface configured to connect to a mesh network; a memory comprising computer-executable instructions; and a processor configured to: execute the computer-executable instructions; receive local sensor data from the one or more sensors; receive remote sensor data from a remote sensing device; control a position of the flow control element based on one or more of the local sensor data or the remote sensor data; store the local sensor data and remote sensor data in the memory; and transmit the local sensor data and the remote sensor data to a second active control device via the mesh network.

Abstract: The present invention reduces the probability of malfunction occurrence when performing predictive control of a device being controlled. In this control device of one aspect of the present invention, a prediction model for a control variable is used to calculate a prediction value from a measured value of the control variable, and a desired command value of the control variable is determined by correcting a desired basic value in accordance with the calculated prediction value. The degree of correction is determined on the basis of weight. The control device controls the operation of the device being controlled according to the determined desired command value. The control device assesses whether the device being controlled is operated appropriately on the basis of monitoring data relating to the operation result of the device being controlled, and optimizes the weight of the correction to make appropriate control possible based on the assessment result.

Abstract: A computer-implemented method for creating a control process for a technical system using a Bayesian optimization method, the control process being created and executable based on model parameters of a control model, the following steps being performed in order to optimize the control process: furnishing a quality function that corresponds to a trainable regression function, and that assesses a quality of a control process of the technical system based on model parameters; executing a Bayesian optimization method based on the quality function in order to iteratively ascertain an optimized model parameter set having model parameters, such that during execution of the Bayesian optimization method, a model parameter domain that indicates the permissible value ranges for the model parameters is expanded, by an amount equal to an expansion distance, with respect to those dimensions for which the model parameter ascertained in the current iteration lies at a range boundary.

Abstract: An HVAC system includes a controller configured to receive weather forecast information including anticipated future outdoor temperatures. Based at least in part on the weather forecast information, the controller determines that test-initiation criteria are satisfied for testing operation of the HVAC system in a test mode. In response to determining that the test-initiation criteria are satisfied, the controller determines that current weather conditions are suitable for operating the HVAC system in the test mode for a test time period. The HVAC system is operated in the test mode for the test time period.

Abstract: A parameter compression unit compresses first input parameter values so that a parameter restoration unit can restore the first input parameter values, and generates first compressed input parameter values in which the number of control parameters is reduced, a model learning unit learns a prediction model from learning data that is a set of the first compressed input parameter values and first output parameter values that are processing results obtained by giving the first input parameter values, as a plurality of control parameters, to a processing device, and a processing condition search unit estimates a second compressed input parameter values corresponding to target output parameter values by using the prediction model.

Abstract: Deep learning models and other complex models provide accurate representations of complex industrial processes. However, these models often fail to satisfy properties needed for their use in closed loop systems such as Advanced Process Control. In particular, models need to satisfy gain-constraints. Methods and systems embodying the present invention create complex closed-loop compatible models. In one embodiment, a method creates a controller for an industrial process. The method includes accessing a model of an industrial process and receiving indication of at least one constraint. The method further includes constructing and solving an objective function based on at least one constraint and the model of the industrial process. The solution of the objective function defines a modified model of the industrial process that satisfies the received constraint and can be used to create a closed-loop controller to control the industrial process.

Abstract: An autonomous real-time remedial action scheme (RAS) control system may receive electrical measurements of a power system. The RAS control system may determine active power and reactive power of each bus in the power system based on the received electrical measurements. The RAS control system may dynamically determine whether to shed one or more loads, generators, or both in the power system by optimizing an objective function to maintain maximum critical load and maximum critical generation in the electrical system based on the active and reactive power of each bus in the power system and the generation of each generator in the power system. The RAS control system may send a command to trip at least one breaker to cause the at least one breaker to shed the one or more loads, generators, or both. The RAS control system may send a command to runback one or more generators.

Abstract: A system and method are provided for operating a power generating asset. Accordingly, at least one external data set indicative of a plurality of variables affecting the performance of the power generating asset is received by the controller. The controller also receives at least one operational data set indicative of the performance of the power generating asset. A plurality of production-assessment models for the power generating asset are generated and trained based on the data sets. A performance prediction is then generated for each of a plurality of model-variable combinations and a control action is implemented based on one of the performance predictions.

Abstract: Provided is a method for the computer-assisted control of a technical system, in particular in a plant for generating energy, to achieve a predetermined technical behavior of the technical system, wherein an operating data set for controlling the system is provided. A system model for describing the mode of operation of the technical system is provided, wherein on the basis of the operating data set and on the basis of the system model, an optimization data set is determined by an optimization method. Based on the optimization data set, relevant parameters of the technical system that allow a more advantageous control of the technical system than other parameters of the technical system are selected using a selection method, wherein with the selected relevant parameters, a control method for the technical system is determined, wherein the technical system is controlled with the aid of the control method.

Abstract: An HVAC system includes a blower configured to provide a flow of air into a conditioned space. A temperature sensor measures a discharge air temperature of the flow of air provided to the conditioned space. The blower provides the flow of air at a predefined flow rate. The controller determines that the measured discharge air temperature satisfies predefined stability criteria associated with a change in the discharge air temperature during a first period of time being less than a threshold value. If the stability criteria are satisfied, a temperature offset is determined between the discharge air temperature and an indoor temperature. The temperature offset is stored in a memory and is associated with the flow rate of air provided by the blower and the outdoor temperature.

Abstract: Systems and methods are directed controlling components of a utility grid. The system can receive signals. The system can determine one or more statistical metrics based on the signals. The system can generate an input matrix. The system can input the input matrix into a machine learning model. The system can predict, based on the input matrix and via the machine learning model, the value for the signal of the utility grid at a time period for which the value is not provided in the input matrix. The system can provide a command to control a component of the utility grid responsive to the value for the signal of the utility grid predicted by the machine learning model.