A facility plan evaluation device includes a proposed plan receiving unit receiving input of a facility plan including capacities and locations of charging and discharging facilities to be newly arranged in a power system, a prediction unit predicting charge and discharge amounts of the charging and discharging facilities, and demands and power generation amounts of existing facilities, which are facilities already connected in the power system, a power flow calculating unit estimating voltage and current in the power system based on a prediction result of the prediction unit, a determination unit determining whether at least one of deviation of voltage from a proper range and overcurrent occurs based on an estimation result of the power flow calculating unit, and determining whether the facility plan needs to be modified based on a determination result, and a result presenting unit presenting a determination result of the determination unit.

A power estimation method is implemented in a three-phase electricity meter, and includes the steps of: detecting a fraud falsifying a first voltage measurement on a first phase; acquiring a second voltage measurement on a second phase, the second voltage measurement not being falsified by the fraud; estimating a first phase shift between the first phase voltage and a first phase current, by using a first phase shift estimation between the first phase voltage and the second phase voltage; estimating at least one first electrical power consumed on the first phase from a first current measurement on the first phase, of the second voltage measurement, and of the first phase shift.

A power estimation method is implemented in a three-phase electricity meter, and includes the steps of: detecting a fraud falsifying a first voltage measurement on a first phase; acquiring a second voltage measurement on a second phase, the second voltage measurement not being falsified by the fraud; estimating a first phase shift between the first phase voltage and a first phase current, by using a first phase shift estimation between the first phase voltage and the second phase voltage; estimating at least one first electrical power consumed on the first phase from a first current measurement on the first phase, of the second voltage measurement, and of the first phase shift.

Techniques for implementing a fault-tolerant power supply are described. In an example, a system converts an alternating-current (AC) voltage to an initial direct current (DC) voltage. The system further converts the initial DC voltage to a first DC voltage and a second DC voltage. The system applies the first DC voltage to a high-priority device such as a metrology device. The system applies the second DC voltage to a low-priority or peripheral device. When the initial DC voltage is outside a voltage range, the system deactivates the second DC voltage to the lower-priority device and maintains the first DC voltage to the metrology device.

A power distribution system comprises a first Smart Meter device for metering the power absorbed or yielded by a domestic utility, in which said first Smart Meter device is connected to a power distribution grid and dialogs in real time with other Smart Meters connected to other domestic utilities, in which said other Smart Meters are connected to the same power grid of said first Smart Meter device, in which said power distribution system is provided with multiple and comprehensive interconnections which connect said first Smart Meter device to the other Smart Meter nodes so as to form a network, in which the information on the energy production and consumption status of the network is available in each Smart Meter node of the network at all times, thus allowing the information on the energy status of the network to be instantaneously available to an operator of the power grid by querying a single Smart Meter among those present in the network.

A computer-implemented method for power grid anomaly detection using a convolutional neural network (CNN) trained to detect anomalies in electricity demand data and electricity supply data includes receiving (i) electricity demand data comprising time series measurements of consumption of electricity by a plurality of consumers, and (ii) electricity supply data comprising time series measurements of availability of electricity by one or more producers. An input matrix is generated that comprises the electricity demand data and the electricity supply data. The CNN is applied to the input matrix to yield a probability of anomaly in the electricity demand data and the electricity supply data. If the probability of anomaly is above a threshold value, an alert message is generated for one or more system operators.

Systems and methods herein automate detection of switched-capacitor bank operation on a power grid. At least one power line sensor (106) may be positioned on a power line to measure electric field strength and current. A processor may be in communication with the power line sensor and memory storing a capacitor bank analyzer as computer readable instructions that, when executed by the processor, control the processor to: receive electric field data and current data from the power line sensor. The processor may extract key characteristics from the electric field data and the current data, compare the key characteristics to a library of key characteristics of a predictive model, and output, based on the predictive model, a label indicating presence of, or lack of, a capacitor switching event. E-field and current data from multiple line sensors may be aggregated to provide additional insight to capacitor bank operation.

Systems and methods herein automate detection of switched-capacitor bank operation on a power grid. At least one power line sensor (106) may be positioned on a power line to measure electric field strength and current. A processor may be in communication with the power line sensor and memory storing a capacitor bank analyzer as computer readable instructions that, when executed by the processor, control the processor to: receive electric field data and current data from the power line sensor. The processor may extract key characteristics from the electric field data and the current data, compare the key characteristics to a library of key characteristics of a predictive model, and output, based on the predictive model, a label indicating presence of, or lack of, a capacitor switching event. E-field and current data from multiple line sensors may be aggregated to provide additional insight to capacitor bank operation.

In one example in accordance with the present disclosure, an electronic device is described. An example electronic device a power meter to capture real-time power draw of the electronic device from a power supply. The example electronic device also includes a controller. An example controller determines (1) an average power draw over a first interval, (2) an average power draw over a second interval, and (3) an overall throttle amount for the electronic device based on the average power draw over the first interval and the average power draw over the second interval. The example electronic device also includes a throttling device to reduce the power draw of the electronic device from the power supply based on the overall throttle amount for the electronic device.

In one example in accordance with the present disclosure, an electronic device is described. An example electronic device a power meter to capture real-time power draw of the electronic device from a power supply. The example electronic device also includes a controller. An example controller determines (1) an average power draw over a first interval, (2) an average power draw over a second interval, and (3) an overall throttle amount for the electronic device based on the average power draw over the first interval and the average power draw over the second interval. The example electronic device also includes a throttling device to reduce the power draw of the electronic device from the power supply based on the overall throttle amount for the electronic device.