A load estimating device measures a voltage and a current supplied to a plurality of loads connected with a power supply, and obtains feature amounts of the plurality of loads from measurement values of the voltage and the current. A storage device stores a feature amount of each combination of two or more loads in advance. The load estimating device estimates what the plurality of loads connected with the power supply device are, on the basis of the obtained feature amounts and the feature amounts stored in the storage device. The feature amount includes a combination of an apparent power and a power factor.

A load power monitoring system includes: an external power supply source; a renewable energy source configured to generate power or store a power applied from the external power supply source, and discharge the generated or stored power; a distribution board configured to distribute a power applied from the external power supply source or the renewable energy source to an electronic device; a power measurement device configured to detect power amount data of at least one of the external power supply source and the renewable energy source; a second power measurement device configured to detect power amount data distributed to the electronic device; and a monitoring server configured to collect power amount data detected by each of the power measurement devices and monitor a power of a load on the basis of the collected power amount data.

A system is provided for differentiating between water usage of multiple water consumers using a common distributed water infrastructure. The system receives from a water sensor that is upstream of a plurality of appliances, signals indicative of water usage, and constructs from the signals a plurality of water event profile signatures. The system associates, based on differences between similar water event profiles, at least one water event profile signature with a first water consumer and associates a second water event profile signature with a second water consumer, and stores the water event profile signatures for the first water consumer and the second water consumer. The system constructs current water event profiles reflecting subsequent water usage in the distributed water infrastructure, and attributes a first current water event profile to the first water consumer and attributes a second current water event profile to the second water consumer.

A system for monitoring electric energy amount according to one embodiment of the present disclosure includes an electric energy system including one or more loads receiving electric energy through an external electric energy source and a renewable energy generator, a home server for receiving information of a first electric energy amount that is an electric energy amount consumed by the one or more loads, a second electric energy amount that is supplied from the external electric energy source to the electric energy system, and a third electric energy amount that is supplied from the renewable energy generator to the electric energy system, and an electric energy amount monitoring server calculating the second electric energy amount or the third electric energy amount from electric energy consumption of the electric energy system, which is received from the home server, and supply electric energy amount information supplied to the electric energy system.

The invention relates to a disaggregation apparatus (4) for being used in a multi-group electrical network (5), which comprises multiple electrical groups (1, 2, 3), each comprising one or more appliances (1.sub.1, 1.sub.2, 1.sub.3, 2.sub.1, 2.sub.2, 2.sub.3, 3.sub.1, 3.sub.2, 3.sub.3). A determination unit (7) determines an electrical group (1, 2, 3) comprising an appliance, of which an operational state has been changed, based on first changes in mains voltages (V.sub.1, V.sub.2, V.sub.3) measured while the operational state change occurs, second and third changes in the mains voltages (V.sub.1, V.sub.2, V.sub.3) measured while switchable loads (1.sub.n, 2.sub.n, 3.sub.n) are switched, and the resistances (R.sub.1n, R.sub.2n, R.sub.3n) of the switchable loads (1.sub.n, 2.sub.n, 3.sub.n). Thus, a misdetection due to an operational state change of an appliance in another electrical group may be avoided and the accuracy of disaggregation may be improved in a multi-group electrical network (5).

A water supply monitoring system in connection with a supply line includes a fluid sensor configured to identify flow rate data identifying a flow rate of water through the supply line. A controller is configured to receive the flow rate data from the fluid sensor and compare the flow rate data over time to a plurality of flow rate models. The flow rate models define flow rate characteristics of a plurality of preconfigured water implements. The controller is further configured to classify a water consumption identified by the flow rate data as being consumed by a plurality of consumption implements in connection with the supply line in a plurality of consumption classifications.

Identification and tracking of major electric appliances by using aggregate power data obtained at the main breaker level of a residence or commercial establishment. Step power changes and power surges characterize appliances. These features are identified and the time of use and duration statistics are considered to match an observed sequence of power changes with the appliances being turned on and off. The time-dependent usage of appliances and their power consumption are then reconstructed.

Devices, methods, and programs for monitoring electrical devices. A method for monitoring an electrical device may include obtaining data representing a sum of electrical signals of electrical devices; processing the data with a Factorial Hidden Markov Model (FHMM) to produce an estimate of an electrical signal of a first of the electrical devices; and outputting the estimate of the electrical signal of the first electrical device. The FHMM may have a factor corresponding to the first electrical device. The factor may have three or more states.

Techniques determine if a gas service (e.g., piping and/or meter) is undersized for the customer's needs. In one example, flowrate information corresponding to gas usage at a service site over a first period of time is obtained. The flowrate information is disaggregated to determine an expected flowrate associated with each of two or more appliances having generally fixed-rates of gas consumption. Flowrate information is again obtained, corresponding to a second period of time. The second flowrate information is compared to one or more combinations (i.e., summations) of the expected flowrates associated with each of the two or more appliances. Based on the comparison, it may be determined that the service site is not appropriately sized. In an example, failure to detect two fixed-rate of gas-consumption appliances operating at their respective fixed-rates at the same time may indicate that the service cannot provide gas at a sufficient flowrate.

Techniques determine if an appliance having a fixed-rate of gas-consumption is degrading over time. In one example, a flowrate of gas at a service site is obtained. The flowrate of gas is disaggregated to obtain a flowrate of gas corresponding to an appliance having a generally fixed-rate of gas-consumption. The flowrate of gas of the appliance is compared to historical gas consumption by the appliance. Based at least in part on the comparing, it may be determined that performance of the appliance has changed over time. For example, the gas consumption of a hot water tank may increase due to mineral build-up in the bottom of the tank. Responsive to the determined degradation of the appliance, warnings may be sent, repairs may be made, and/or appliance(s) may be replaced.