Mitsubishi Electric Corporation

Toshihiro Mega

Fuyuki Sato

Genta Yoshimura

Hiroki Kawano

Kazuo Tomisawa

Yoshiaki Koizumi

Tomohiro Sato

Satoshi Endo

Kazuhiro Komatsu

Tomohiro Narui

Yoshinori Nakajima

Tomooki Ukiana

Kenjiro Miura

Nobuaki Tasaki

Shinichiro Otani

Jin Kawasaki

Sosuke Minamida

Kazuyuki Nagahiro

Kosuke Iwasaki

Kazumi Ueno

Tomoyuki Kamimura

Shuichi Murayama

Naoya Fukuoka

Hiroto Takahashi

A management device includes: an acquisition unit that acquires operating history data for an equipment device in a prescribed time period; and a classification processing unit that classifies, based on the operating history data acquired by the acquisition unit, an operating pattern of the equipment device in the prescribed time period. The classification processing unit includes: an operating pattern calculation unit that calculates a first operating pattern in a first time period and a second operating pattern in a remaining second time period when the prescribed time period is divided into unit time periods; a change calculation unit that calculates a degree of change in the operating pattern using the first operating pattern and the second operating pattern when the prescribed time period is divided into unit time periods; a split point calculation unit that calculates, as a split time point, a time point where the degree of change satisfies a prescribed condition for the prescribed time period; and a split processing unit that splits the prescribed time period at the calculated split time point.

Management device, management system, and management method for classifying an operation pattern

A power consumption estimation device () which estimates power consumption of each of one object facility () or more whose operation statuses can be monitored includes: a total power vector generation unit () to acquire time-series data of total power consumption; a status matrix generation unit () to acquire time-series data of an operation parameter of the one object facility () or more; a reference signal generation unit () to generate one reference signal or more; a contribution degree estimation unit () to perform multiple regression analysis by taking the total power consumption as an objective variable, and the operation parameter of the one object facility () or more and a component value of the one reference signal or more, as explanatory variables, to thereby calculate a contribution degree of each of the one object facility () or more; and a breakdown calculation unit () to multiply the contribution degree of the object facility () and the operation parameter of the object facility (), to thereby calculate power consumption of the object facility ().

Power consumption estimation device

A control method analysis unit acquires a correspondence relation between signs and model numbers from an apparatus table of an instrumentation diagram, and acquires signs and apparatus symbols, and connection relation among apparatuses, from a drawing of the instrumentation diagram. Subsequently, the control method analysis unit acquires an apparatus classification drawn on the diagram by searching an instrumentation apparatus classification database based on the model numbers, and decides a temperature control method employed by an instrumentation indicated in the instrumentation diagram, from the apparatus classification and the connection relation. The control method analysis unit then links the decided temperature control method to the instrumentation diagram accumulated in a case database. A search processing unit extracts a corresponding instrumentation diagram by searching the case database based on a temperature control method designated as a search condition.

Instrumentation diagram data generation device, instrumentation diagram search system, and computer readable medium

There is provided air-conditioning control in a low power operation so as not to exceed a target demand power amount in a predetermined measurement period while preventing deterioration of comfortableness of a living space. There include a reducible-power-amount estimation unit configured to calculate, for each group, a reducible power amount by making indoor units perform, for each group, a shut-off operation for a minimum shut-off time in the first half of a demand time limit, and a reduced-power-amount determination unit configured to distribute, when a power consumption amount predicted by a power consumption amount prediction unit exceeds a target demand power amount after the first half of the demand time limit passes, the exceeding power amount to each zone, evenly distribute, in each zone, the distributed power amount to each group, and calculate, based on the reducible power amount of each group, a shut-off time of each group when each group performs the shut-off operation to reduce the distributed power amount.

Demand control device and computer readable medium

An air conditioner control system comprises air conditioners configured to condition an environment in a target space, an integrated controller configured to control the air conditioners based on control parameter data, sensor devices configured to measure the temperature of the target space and transmit measurement data, and wireless master devices configured to create control parameter data based on the measurement data. The wireless master devices each determine sleep times so that at least two sensor devices run out of battery charge around the same time according to the remaining charge amount of each of the sensor devices. The sensor devices each will be in the sleep mode in which power consumption is lower than in the normal mode according to the sleep time decided by the wireless master devices.

Air conditioner control system, sensor device control method, and program

Growing community of inventors

Tokyo, Japan

Toshihiro Mega