A method for characterizing power quality events in an electrical system includes deriving electrical measurement data for at least one first virtual meter in an electrical system from (a) electrical measurement data from or derived from energy-related signals captured by at least one first IED in the electrical system, and (b) electrical measurement data from or derived from energy-related signals captured by at least one second IED in the electrical system. In embodiments, the at least one first IED is installed at a first metering point in the electrical system, the at least one second IED is installed at a second metering point in the electrical system, and the at least one first virtual meter is derived or located at a third metering point in the electrical system. The derived electrical measurement data may be used to generate or update a dynamic tolerance curve associated with the third metering point.

A system for improving grid reliability in remote or isolated locations includes a battery tripping module, the battery tripping module determining whether a microgrid zone may be formed upon a fault. The system further includes a microgrid formation module, the microgrid formation module forming a microgrid zone, the microgrid zone connected to a BESS (battery electric storage system), the BESS providing power to the microgrid.

Methods and systems are provided for optimizing energy management of an energy resource site. For instance, a hierarchical energy management system can provide optimized management of energy resource sites with large numbers of energy resources. In particular, the hierarchical energy management system can effectively control energy resources by allocating functionality using different tiers. For instance, one or more energy resources devices can comprise the lowest tier of the hierarchical energy management system. The next tier of the hierarchical energy management system can comprise one or more controllers that can manage the energy resource devices. The next tier of the hierarchical energy management system, a resource manager, generally manages the set of controllers.

An electrical network includes a plurality of distribution transformers, a plurality of network protectors each electrically connected to one of the distribution transformers, a secondary bus electrically connected to each of the plurality of network protectors, and a control unit. The control unit is configured to receive data from each of the plurality of network protectors associated with electricity flowing therethrough, analyze the data to determine whether an electrical imbalance exists at any of the network protectors, and operate any imbalanced network protectors to disconnect the distribution transformers connected to the imbalanced network protector from the secondary bus. The control unit is further configured to permit beneficial backflow through the distribution transformers that may be created by generators coupled to the secondary bus.

A hazardous energy control system is presented. The system includes a back-end system and a personal electronic device communicatively connected to the back-end system. The personal electronic device provides a user interface for a user to select a set of equipment from the pieces equipment at the worksite for electrical isolation from hazardous energy sources via lockout/tagout (LOTO). The back-end system is configured to dynamically the back-end system is configured to dynamically determine a LOTO procedure for electrical isolation of the set of equipment from the hazardous energy sources based on the electrical node data set indicating pieces of equipment, energy isolation devices (EIDs), and electrical connections between the pieces of equipment and EIDs on a worksite.

The invention relates to a reliable system and method for energy management at an end user of electrical energy. The proposed energy management system comprises two substantially independent fault containment units (FCU), an energy steering system (110) and an energy optimization system (150), which exchange data via a well-defined message interface. The energy steering system performs the energy distribution according to the target data (142) periodically received from the energy optimization system. The energy optimization system calculates the optimum use of energy at any given time. Since the energy optimization system has no direct contact with the Internet during normal operation, there can be no intrusion into the energy optimization system. If the energy optimization system fails due to an intrusion, the energy steering system takes over the target data from an contingency/emergency plan stored locally a priori.

A grid-forming energy storage system includes a data interface and transfer module, a state analysis and prediction module, an event response and strategy adjustment module, and an energy scheduling and management module. In the present disclosure, the energy management efficiency in the smart grid is significantly improved through real-time data formatting and efficient information transfer, real-time transmission and accuracy of data are ensured by using a JSON formatted data interface and a TCP/IP protocol, the data processing flow is optimized in conjunction with Apache Kafka, and the throughput capacity is improved and the response time is shortened, such that the grid manages resources more efficiently. Through state analysis and demand prediction by Spark Streaming, the grid responds in real time and predicts energy demand changes to reduce the energy waste.

A method includes determining control setpoints for equipment based on a time-varying availability of green energy and revenue from an incentive program of an energy provider. The method also includes controlling the equipment using the control setpoints.

Systems and methods are disclosed for automated power plant unit trip prediction and control. Power plant controls may have limited time to manage the plant loads when one of the units trips unexpectedly. To mitigate any consequences on a power grid associated with a trip event, these systems and methods may allow for prediction of such trip events. The predictions may allow a signal to be provided to a controller in sufficient time for the controller to automatically take any necessary action to mitigate any impacts of the future trip event.

A method and device for detecting security of Internet of Things data of market transaction, and an electronic apparatus are provided. The method includes: calculating at least one first trapezoidal fuzzy set having a number of attacks of data; calculating at least one second trapezoidal fuzzy set of an error rate of the data; calculating at least one third trapezoidal fuzzy set of a repetition rate of the data; calculating at least one fourth trapezoidal fuzzy set of miss rate of the data; determining a security detection value according to the first trapezoidal fuzzy set; determining a false detection value according to the second trapezoidal fuzzy set, the third trapezoidal fuzzy set and the fourth trapezoidal fuzzy set; and determining security of the Internet of Things data of the market transaction according to the security detection value and the false detection value.