US 2017/0373500 A1Published application

Method for Adaptive Demand Charge Reduction

AssigneeRobert Bosch GmbH

InventorsSayed Yusef Shafi, Maksim V. Subbotin, Ashish S. Krupadanam, Binayak Roy, Jasim Ahmed

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Abstract

A method for peak load shaving uses an energy storage device. A controller predicts the threshold above which the energy consumed by a load is equal to the capacity of the storage device. Load forecasting methods include artificial neural networks and support vector machines to compute a real-time threshold estimate that is used to decide when to dispatch power from the energy storage device. The threshold estimates are adapted iteratively, using the most recent observed load and previous threshold estimates. The adaptive algorithm reduces the peak demand charge assessed to the customer compared to existing static approaches that compute dispatch policies in advance.

Claims15

Dependent claims

A method of peak load shaving in an energy management system (EMS) comprising:

identifying with a controller an available energy capacity of an energy storage device in the EMS;
estimating with the controller a level and duration of peak power consumption for a load connected to the EMS over a predetermined time period based on a feed-forward neural network trained with a history of peak power consumption measurements by the EMS;
identifying with the controller a power consumption threshold for the load connected to the EMS with reference to the level and duration of peak power consumption estimated by the controller and the available energy capacity of the energy storage device;
measuring with the controller a power consumption level of the load during the predetermined time period;
and
activating with the controller the energy storage device to provide energy to the load from the energy storage device in response to the measured power consumption level of the load exceeding the threshold.

3 more elements

An energy management system (EMS) configured to perform peak load shaving, the EMS comprising:

an energy storage device connected to a load and to an external electrical power source;
and
a controller operatively connected to the energy storage device, the controller being configured to:
identify an available energy capacity of an energy storage device in the EMS;
estimate a level and duration of peak power consumption for a load connected to the EMS over a predetermined time period based on a feed-forward neural network trained with a history of peak power consumption measurements by the EMS;
identify a power consumption threshold for the load connected to the EMS with reference to the level and duration of peak power consumption estimated by the controller and the available energy capacity of the energy storage device;
measure a power consumption level of the load during the predetermined time period;
and
activate the energy storage device to provide energy to the load from the energy storage device in response to the measured power consumption level of the load exceeding the threshold.

6 more elements

Dependencies are inferred from the claim text.

Facts

Application: 15/538,699Filed 22 Dec 2015
Priority: 22 Dec 2014
Published: 28 Dec 2017
Term ends: Not estimatedThe source records don’t support an estimate.

Classification18 codes

H02J 3/28
Circuit arrangements for AC mains or AC distribution networks: arrangements for balancing of the load in networks by storage of energy
G05B 13/027
The criterion being a learning criterion: using neural networks only
G06N 3/084
Learning methods: backpropagation, e.g. using gradient descent
H02J 3/14
Arrangements for adjusting voltage in AC networks by changing a characteristic of the network load: by switching loads on to, or off from, the…

Family

Application62/095,455Us provisional application · filed 22 Dec 2014
Application62/095,810Us provisional application · filed 23 Dec 2014
US 2017/0373500 A1This patent

From the US filing history. Foreign family members aren’t listed.

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