Kabushiki Kaisha Toshiba

Toshiba Infrastructure Systems & Solutions Corporation

Yoshiyuki Sakamoto

Shuuichiro Imahara

Takahiro Yamamoto

Kazuo Watabe

Takashi Usui

Isao Takahashi

Toru Yano

Takenori Kobayashi

Hideo Sakamoto

Shinichi Nagano

Hisaaki Hatano

Kenichi Fujiwara

Takashi Koiso

Masatake Sakuma

Hisashi Hayashi

Shuichiro Imahara

Ryosuke Takeuchi

Topon Kumar Paul

Ryusei Shingaki

Toshiki Takayasu

Gaku Ishii

Takuro Moriyama

Tomohiro Toyosaki

Shuichiro Kobayashi

Shinya Umeno

Tsutomu Shinozaki

According to one embodiment, an operation planning system includes a demand information database and a plurality of planning units. The demand information database stores demand data including an overall output required for a plurality of operation units for a planning period in an operation plan. The plurality of planning units adjusts output settings of the plurality of operation units. Any of the planning units selects a combination of operation units which provide the overall output required for the planning period, and based on operation costs depending on the outputs of the operation units, a process is repeated to generate the operation plan, the process including: selection of the operation unit belonging to the combination of operation units; and adjustment of the output setting for the selected operation unit by the planning unit paired with the selected operation unit.

Operation planning system, operation planning device and operation planning method

According to an embodiment, a nondestructive inspection method includes: detecting, by a plurality of sensors installed in a truck that supports a vehicle body, an elastic wave generated when a lifting member inserted between the vehicle body and the truck moves the vehicle body up and down; and estimating, by an evaluation device, a position of a defect in the truck, based on the elastic wave detected by the plurality of sensors.

Nondestructive inspection method and nondestructive inspection system

According to one embodiment, an evaluation device includes first processing circuitry and second processing circuitry. The first processing circuitry calculates a feature value of an energy storage device based on voltage values measured from the energy storage device being subjected to charge-discharge-control according to charge-discharge command values. The second processing circuitry derives an evaluation function of a degradation state of the energy storage device according to a difference between a distribution of the charge-discharge command values and a reference distribution. The second processing circuitry evaluates the degradation state of the energy storage device, based on the evaluation function and the calculated feature value.

Evaluation device, energy storage system, evaluation method and non-transitory computer readable medium

According to one embodiment, a behavior estimation apparatus includes a storage unit, a first calculation unit, a second calculation unit, and an estimation unit. The storage unit stores first data collecting power values consumed by a consumer in a period. The first calculation unit calculates second data representing a frequency of each power value by using the first data. The second calculation unit calculates a first threshold to divide a first power value from a second power value which is larger than and next to the first power value, among power values corresponding to maximal values of frequencies included in the second data. The estimation unit obtains a power value consumed by the consumer in an estimating period, and estimates the consumer's behavior status in the estimating period by using the power value and the first threshold.

Behavior estimation apparatus, threshold calculation apparatus, behavior estimation method and non-transitory computer readable medium thereof

A district heat supply plant controller for efficiently and flexibly obtaining operation plans of a district heat supply plant includes a plant operation planning device responsive to a predicted thermal load value for a current day predicted by a thermal load prediction device to determine an operation plan of the district heat supply plant. The plant operation planning device has a genetic algorithm executing device applying genetic algorithms onto an individual having rows of genes representing ON/OFF states in each time unit by 1/0 for each of the heat source devices. In the plant operation planning device, a mathematical programming executing device,uses an operation plan obtained by the genetic algorithm executing device,as its initial value to determine the operation plan of the district heat supply plant

District heat supply plant controller

Growing community of inventors

Tokyo, Japan

Yoshiyuki Sakamoto