WO2021214533A1

WO2021214533A1 - Device and method for auditing electrical energy

Info

Publication number: WO2021214533A1
Application number: PCT/IB2020/055564
Authority: WO
Inventors: Gokul Shrinivas
Original assignee: Minionlabs India Private Limited
Priority date: 2020-04-21
Filing date: 2020-06-15
Publication date: 2021-10-28

Abstract

A device and a method for auditing electrical energy are disclosed. The device also includes an electricity monitoring subsystem configured to monitor data associated with an electricity consumption in a predefined location. The device also includes a disaggregation subsystem configured to disaggregate the electricity consumption monitored by the electricity monitoring subsystem of the predefined location into one or more electricity consuming assets. The device also includes a parameter capturing subsystem configured to capture one or more parameters associated with each of the one or more electricity consuming assets. The device also includes an identification subsystem configured to identify the one or more electricity consuming assets in the predefined location. The device also includes a pattern determining subsystem configured to determine a pattern of the electricity consumption from each of the one or more electricity consuming assets.

Description

DEVICE AND METHOD FOR AUDITING ELECTRICAL ENERGY

This International Application claims priority from a complete patent application filed in India having Patent Application No. 202041017083, filed on April 21, 2020 and titled “DEVICE AND METHOD FOR AUDITING ELECTRICAL ENERGY”.

FIELD OF INVENTION

Embodiments of a present disclosure relate to an auditing electrical energy, and more particularly, to a device and a method for auditing electrical energy in one or more electricity consuming assets.

BACKGROUND

Auditing electrical energy is crucial for manufactures to ensure about a normal condition of the one or more electricity consuming assets. Therefore, it is useful to monitor status of the one or more electricity consuming assets and detect one or more anomalies. Various devices are available for auditing electricity consumption. In a conventional approach, the device, which is available for auditing the electricity consumption, monitors the electricity consumption of a whole area or a building and display on the light emitting diode (LED) display. However, if the user needs one or more details associated with an appliance level electricity consumption, then the user needs to buy and install multiple energy meters in each of the electrical appliances. This increases the investment cost of the user.

In another approach, the device, which is available for auditing the electricity consumption, audits the electricity consumption of the whole area or building and provide details on a cloud dashboard or on a mobile application. Also, if the user needs the one or more details associated with an appliance level electricity consumption, the wires will be running all along with the building with sensor clamps for each and every appliance. However, such devices are limited to maximum 10 measurement and if the user has more than 10 appliances then there is a requirement of the multiple devices and a bundle of wires which again increases the investment cost of the user. Also, wires will depreciate over a period of time, hence decreases an accuracy and increases the maintenance cost. In yet another approach, the device audits the electricity consumption of the one or more appliances by connecting each of such device to the one or more appliances. However, user needs to procure many smart plugs for each and every power sockets, appliances, devices and tools inside the building which again increases the investment cost of the user.

Hence, there is a need for an improved device and a method for auditing electrical energy in order to address the aforementioned issues.

BRIEF DESCRIPTION

In accordance with an embodiment of the disclosure, a device for auditing electrical energy is disclosed. The device includes one or more processors. The device also includes an electricity monitoring subsystem operable by the one or more processors. The electricity monitoring subsystem is configured to monitor data associated with an electricity consumption in a predefined location. The device also includes a disaggregation subsystem operable by the one or more processors. The disaggregation subsystem is configured to disaggregate the electricity consumption monitored by the electricity monitoring subsystem of the predefined location into one or more electricity consuming assets using a disaggregation technique.

The device also includes a parameter capturing subsystem operable by the one or more processors. The parameter capturing subsystem is configured to capture one or more parameters associated with each of the one or more electricity consuming assets disaggregated by the disaggregation subsystem. The device also includes an identification subsystem operable by the one or more processors. The identification subsystem is configured to identify the one or more electricity consuming assets in the predefined location based on the one or more parameters of each of the one or more electricity consuming assets captured by the parameter capturing subsystem. The device also includes a pattern determining subsystem operable by the one or more processors. The pattern determining subsystem is configured to determine a pattern of the electricity consumption from each of the one or more electricity consuming assets identified in the identification subsystem.

In accordance with another embodiment, a method for auditing electrical energy is disclosed. The method includes monitoring data associated with an electricity consumption in a predefined location. The method also includes disaggregating the electricity consumption monitored by the electricity monitoring subsystem of the predefined location into one or more electricity consuming assets using a disaggregation technique. The method also includes capturing one or more parameters associated with each of the one or more electricity consuming assets disaggregated by the disaggregation subsystem. The method also includes identifying the one or more electricity consuming assets in the predefined location based on the one or more parameters of each of the one or more electricity consuming assets captured by the parameter capturing subsystem. The method also includes determining a pattern of the electricity consumption from each of the one or more electricity consuming assets based on the one or more parameters captured by the parameter capturing subsystem.

To further clarify the advantages and features of the present disclosure, a more particular description of the disclosure will follow by reference to specific embodiments thereof, which are illustrated in the appended figures. It is to be appreciated that these figures depict only typical embodiments of the disclosure and are therefore not to be considered limiting in scope. The disclosure will be described and explained with additional specificity and detail with the appended figures.

BRIEF DESCRIPTION OF THE DRAWINGS

The disclosure will be described and explained with additional specificity and detail with the accompanying figures in which:

FIG. 1 is a schematic representation of a device for auditing electrical energy in accordance with an embodiment of the present disclosure;

FIG. 2 is a block diagram representation of the device for auditing electrical energy of FIG. 1 in accordance of the present disclosure; FIG. 3 is the block diagram of an embodiment of the device for auditing electrical energy of FIG. 2 in accordance with an embodiment of the present disclosure;

FIG. 4 is a block diagram of an auditing electrical energy computer system or a server in accordance with an embodiment of the present disclosure; and FIG. 5 is a flow diagram representing steps involved in a method for auditing electrical energy in accordance with an embodiment of the present disclosure.

Further, those skilled in the art will appreciate that elements in the figures are illustrated for simplicity and may not have necessarily been drawn to scale. Furthermore, in terms of the construction of the device, one or more components of the device may have been represented in the figures by conventional symbols, and the figures may show only those specific details that are pertinent to understanding the embodiments of the present disclosure so as not to obscure the figures with details that will be readily apparent to those skilled in the art having the benefit of the description herein.

DETAILED DESCRIPTION

For the purpose of promoting an understanding of the principles of the disclosure, reference will now be made to the embodiment illustrated in the figures and specific language will be used to describe them. It will nevertheless be understood that no limitation of the scope of the disclosure is thereby intended. Such alterations and further modifications in the illustrated system, and such further applications of the principles of the disclosure as would normally occur to those skilled in the art are to be construed as being within the scope of the present disclosure.

The terms "comprises", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process or method that comprises a list of steps does not include only those steps but may include other steps not expressly listed or inherent to such a process or method. Similarly, one or more devices or sub-systems or elements or structures or components preceded by "comprises... a" does not, without more constraints, preclude the existence of other devices, sub-systems, elements, structures, components, additional devices, additional sub-systems, additional elements, additional structures or additional components. Appearances of the phrase "in an embodiment", "in another embodiment" and similar language throughout this specification may, but not necessarily do, all refer to the same embodiment.

Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this disclosure belongs. The system, methods, and examples provided herein are only illustrative and not intended to be limiting.

In the following specification and the claims, reference will be made to a number of terms, which shall be defined to have the following meanings. The singular forms “a”, “an”, and “the” include plural references unless the context clearly dictates otherwise.

Embodiments of the present disclosure relate to a system and a method for auditing electrical energy. The device includes one or more processors. The device also includes an electricity monitoring subsystem operable by the one or more processors. The electricity monitoring subsystem is configured to monitor data associated with an electricity consumption in a predefined location. The device also includes a disaggregation subsystem operable by the one or more processors. The disaggregation subsystem is configured to disaggregate the electricity consumption monitored by the electricity monitoring subsystem of the predefined location into one or more electricity consuming assets using a disaggregation technique.

FIG. 1 is a schematic representation of a device (10) for auditing electrical energy in accordance of the present disclosure. A device (20) for auditing electrical energy audits one or more electricity consuming assets (30) such as one or more appliances (32) and one or more devices (32) to predict an amount of electricity consumed by each of the one or more electricity consuming assets (30) in one or more predefined locations.

FIG. 2 is a block diagram representation of a device (20) for auditing electrical energy of FIG. 1 in accordance of the present disclosure. The device (20) includes one or more processors (40). In one embodiment, the device (20) may be installed within one or more distribution points at a predefined location. In such embodiment, the one or more distribution points may include, but not limited to, a utility meter, a breaker panel, a busbar panel and the like. In some embodiment, the predefined location may include hotels and restaurants, small and medium enterprises, hospitals, government buildings, banks, automobile and logistics, energy utilities, individual homes and the like.

Further, the device (20) also includes an electricity monitoring subsystem (50) operable by the one or more processors (40). The electricity monitoring subsystem (50) monitors data associated with an electricity consumption in the predefined location. In one embodiment, the electricity monitoring subsystem (50) monitors the data associated with the electricity consumption in a predefined interval of time. In such embodiment, the predefined interval of time may include macro- seconds. In one specific embodiment, the device (20) may include a data transmission subsystem (60) operable by the one or more processors (20). The data transmission subsystem (60) transmits a monitored data to a server via a communication module. In one embodiment, the communication module may include, but not limited to a wireless fidelity, a third generation (3G) network, a fourth generation (4G) network and the like.

Furthermore, the device (20) also includes a disaggregation subsystem (70) operable by the one or more processors (40). The disaggregation subsystem (70) disaggregates the electricity consumption monitored by the electricity monitoring subsystem (50) of the predefined location into one or more electricity consuming assets using a disaggregation technique. In one embodiment, the one or more electricity consuming assets may include one or more appliances, one or more devices and the like.

In one embodiment, the disaggregation technique may include a machine learning model. In one embodiment, the disaggregation subsystem (70) builds a machine learning model based on the self-learning from a historic data associated with the electricity consumed stored in a database. In some embodiment, the disaggregation subsystem (70) disaggregates even when at least two electricity consuming assets are simultaneously switched ON. Further, the device (20) also includes a parameter capturing subsystem (80) operable by the one or more processors (40).

The parameter capturing subsystem (80) captures one or more parameters associated with each of the one or more electricity consuming assets disaggregated by the disaggregation subsystem (70). In one embodiment, the one or more parameters may include, but not limited to energy, voltage, current and the like. In some embodiment, the parameter capturing subsystem (80) captures the one or more parameters at a predefined speed. In such embodiment, the predefined speed may include a macro- second speed. In some embodiment, the device (20) may include a data storage subsystem (90) operable by the one or more processors (40). In such embodiment, the data storage subsystem (90) stores the one or more parameters captured in a database.

Further, the device (20) includes an identification subsystem (100) operable by the one or more processors (40). The identification subsystem (100) identifies the one or more electricity consuming assets in the predefined location based on the one or more parameters of each of the one or more electricity consuming assets captured by the parameter capturing subsystem (80). In one embodiment, the identification subsystem (100) identifies the one or more electricity consuming assets in the predefined location by continuously monitoring the one or more parameters of each of the one or more electricity consuming assets stored in the database.

Furthermore, the device (20) also includes a pattern determining subsystem (110) operable by the one or more processors (40). The pattern determining subsystem (110) determines a pattern of the electricity consumption from each of the one or more electricity consuming assets identified in the identification subsystem (100). In one specific embodiment, the pattern may represent an amount of electricity consumed by each of the one or more electrical appliances, price correlations, temperature correlations, area wise ranking across device users and the like.

In one embodiment, the pattern of the electricity consumption of each of the one or more electricity consuming assets are graphically displayed on a user handheld device via a message or an electronic mail. In such embodiment, the server may be in a communication with the user handheld device to send the pattern of the electricity consumption of each of the one or more electricity consuming assets. In some embodiment, the pattern of the electricity consumption of each of the one or more electricity consuming assets are graphically displayed on a cloud dashboard. In one specific embodiment, the device (20) enables the user to track one or more insights to reduce the electricity consumption and a cost.

In some embodiment, the device (20) may include a power source identification subsystem (120) operable by the one or more processors (20). The power source identification subsystem (120) identifies a power source of each of the one or more electricity consuming assets prior to determining the pattern of the electricity consumption of the each of the one or more electricity consuming assets. In such embodiment, the power source may include, but not limited to, a power grid, a green energy source and the like.

In one embodiment, the device (20) may include a prediction subsystem (130) predicts a forthcoming electricity consumption of the one or more electricity consuming assets based on the pattern determined by the pattern determining subsystem (110). In one embodiment, the prediction subsystem (130) predicts the forthcoming electricity consumption by comparing the historic data associated with the electricity consumption in the database to a current data associated with the electricity consumption, wherein the current data is extracted from a determined pattern. Further, in some embodiment, the prediction subsystem (130) also performs one or more analysis such as asset efficiency analysis, root cause analysis, warranty analysis, carbon emission analysis and the like based on a predicted forthcoming electricity consumption.

Further, in one embodiment, the device (20) may include an alert generation subsystem (140) that generates an alert signal for one or more entities upon detection of a breakdown in the one or more electricity consuming assets based on the pattern determined by the pattern determining subsystem (110). In one embodiment, the one or more entities may include, but not limited to, one or more users one or more individuals, one or more organizations and the like. In such embodiment, the breakdown may be detected by correlating the pattern of the electricity consumption of each of the one or more electricity consuming assets with a predefined pattern of each of the one or more electricity consuming assets.

In such embodiment, a generated alert signal may be sent to the one or more entities via a mode of communication. In one embodiment, the mode of communication, may include, but not limited to, a mobile phone, an email account or a future form of a portable communication device. As used herein, the term “portable communication device” defined as a hand-held or a wearable device. In one specific embodiment, the device (20) enables the one or more entities to raise a service request via the mode of communication. In one embodiment, the device (20) also enables the one or more entities to control the electricity consumption of the one or more electricity consuming assets via the internet.

FIG. 3 is a block diagram of an embodiment of the device (20) for auditing electrical energy of FIG. 2 in accordance with an embodiment of the present disclosure. Assume, the device (20) is installed next to a utility meter in a residence building ‘X’ (150) in order to predict future possibilities of failures or inefficiencies of one or more house hold appliances such as a washing machine Ύ (160) and a refrigerator ‘Z’ (170) in the residence building ‘X’ (150). A continuous monitoring of the electricity consumption of the residence building ‘X’ (150) is performed by an electricity monitoring subsystem (50) in macro- seconds. Further, a monitored electricity consumption is sent to a server, by a data transmission subsystem (60), via a wireless fidelity.

Furthermore, the monitored electricity consumption of the residence building ‘X’ (150) is disaggregated, by the disaggregation subsystem (70), into the one or more household appliances (160,170) wise consumption by training a machine learning model. Furthermore, voltage and energy of the one or more household appliances (160,170) is captured, by the parameter capturing subsystem (80) and then the voltage and the energy of the one or more house hold appliances (160, 170) is matched with a pool of a predefined data to identify the one or more house hold appliances by the identification subsystem (100).

Further, a pattern of each of the one or more house hold appliances (160, 170) are determined by matching a current pattern of each of the one or more house hold appliances (160, 170) with a predefined labelled pattern which is stored in the database by the pattern determining subsystem (110), wherein a determined pattern indicates a user (180) “Your washing machine Ύ (160) is switched ON and the electricity consumption of the washing machine Ύ (160) is ‘A’ kWh.

FIG. 4 is a block diagram of an auditing electrical energy computer system (190) in accordance with an embodiment of the present disclosure. The computer system (190) includes processor(s) (40), and memory (200) coupled to the processor(s) (40) via a bus (210). The processor(s) (40), as used herein, means a type of computational circuit, such as, but not limited to, a microprocessor, a microcontroller, a complex instruction set computing microprocessor, a reduced instruction set computing microprocessor, a very long instruction word microprocessor, an explicitly parallel instruction computing microprocessor, a digital signal processor, or other type of processing circuit, or a combination thereof.

Also, the memory (200), as used herein, is stored locally on a user device. The memory (200) includes multiple subsystems stored in the form of executable program which instructs the processor (40) to perform the configuration of the device illustrated in FIG. 2. The memory (200) has following subsystems: an electricity monitoring subsystem (50), a disaggregation subsystem (70), a parameter capturing subsystem (80), an identification subsystem (100) and a pattern determining subsystem (110) of FIG. 2.

Computer memory elements may include a suitable memory device(s) for storing data and executable program, such as read-only memory, random access memory, erasable programmable read-only memory, electrically erasable programmable read-only memory, hard drive, removable media drive for handling memory cards and the like. Embodiments of the present subject matter may be implemented in conjunction with program subsystems, including functions, procedures, data structures, and application programs, for performing tasks, or defining abstract data types or low-level hardware contexts. The executable program stored on one of the above-mentioned storage media may be executable by the processor(s) (40).

The electricity monitoring subsystem (50) instructs the processor(s) (40) to monitor data associated with an electricity consumption in a predefined location. The disaggregation subsystem (70) instructs the processor(s) (40) to disaggregate the electricity consumption monitored by the electricity monitoring subsystem of the predefined location into one or more electricity consuming assets using a disaggregation technique. The parameter capturing subsystem (80) instructs the processor(s) (40) to capture one or more parameters associated with each of the one or more electricity consuming assets disaggregated by the disaggregation subsystem.

The identification subsystem (100) instructs the processor(s) (40) to identify the one or more electricity consuming assets in the predefined location based on the one or more parameters of each of the one or more electricity consuming assets captured by the parameter capturing subsystem. The pattern determining subsystem (110) instructs the processor(s) (40) to determine a pattern of the electricity consumption from each of the one or more electricity consuming assets identified in the identification subsystem.

FIG. 5 is a flow diagram representing steps involved in a method (220) for auditing electrical energy in accordance with an embodiment of the present disclosure. In one embodiment, the method (220) includes installing a device within one or more distribution points at a predefined location. In such embodiment, installing the device within the one or more distribution points may include installing the device within a utility meter, a breaker panel, a busbar panel and the like. In one embodiment, installing the device within the one or more distribution points at the predefined location may include installing the device within the one or more distribution points at hotels and restaurants, small and medium enterprises, hospitals, government buildings, banks, automobile and logistics, energy utilities, individual homes and the like.

Further, the method (220) includes monitoring, by an electricity monitoring subsystem, data associated with an electricity consumption in the predefined location in step 230. In one embodiment, the method (220) may include transmitting, by a data transmission subsystem, a monitored data to a server via one of a communication module. In such embodiment, transmitting the monitored data to the server via one of the communication module may include transmitting the monitored data to the server via one of a wireless fidelity, third generation (3G) network, a fourth generation (4G) network and the like. The method (220) also includes disaggregating, by a disaggregation subsystem, the electricity consumption monitored by the electricity monitoring subsystem of the predefined location into one or more electricity consuming assets using a disaggregation technique in step 240. In one embodiment, disaggregating the electricity consumption monitored by the electricity monitoring subsystem of the predefined location into the one or more electricity consuming assets may include disaggregating the electricity consumption monitored by the electricity monitoring subsystem of the predefined location into one or more appliances, one or more devices and the like.

In some embodiment, disaggregating the electricity consumption monitored by the electricity monitoring subsystem of the predefined location into the one or more electricity consuming assets using the disaggregation technique may include disaggregating the electricity consumption monitored by the electricity monitoring subsystem of the predefined location into the one or more electricity consuming assets using a machine learning model. In some embodiment, the method (220) may include building a machine learning model based on the self-learning from a historic data associated with the electricity consumed stored in a database.

The method (220) also includes capturing, by a parameter capturing subsystem, one or more parameters associated with each of the one or more electricity consuming assets disaggregated by the disaggregation subsystem in step 250. In one embodiment, capturing the one or more parameters may include capturing energy, voltage, current and the like. In one embodiment, the method may also include storing, by a data storage subsystem, the one or more parameters captured in a database.

The method (220) also includes identifying, by an identification subsystem, the one or more electricity consuming assets in the predefined location based on the one or more parameters of each of the one or more electricity consuming assets captured by the parameter capturing subsystem in step 260. In one embodiment, identifying the one or more electricity consuming assets in the predefined location may include identifying the one or more electricity consuming assets in the predefined location by continuously monitoring the one or more parameters of each of the one or more electricity consuming assets stored in the database. The method (220) also includes determining, by a pattern determining subsystem, a pattern of the electricity consumption from each of the one or more electricity consuming assets identified in the identification subsystem in step 270. In one embodiment, determining the pattern may include determining an amount of electricity consumed by each of the one or more electrical appliances, price correlations, temperature correlations, area wise ranking across device users and the like.

Further, in one embodiment, the method (220) may include graphically displaying the pattern of the electricity consumption of each of the one or more electricity consuming assets on a user handheld device via a message or an electronic mail. In some embodiment, the method (220) may include displaying the pattern of the electricity consumption on a cloud dashboard. In one embodiment, the method (220) may also include displaying the pattern of the electricity consumption to the user by generating a hard copy of the report.

In some embodiment, the method may include enabling the user to track one or more insights to reduce the electricity consumption and a cost.

In one embodiment, the method (220) may include identifying, by a power source identification subsystem, a power source of each of the one or more electricity consuming assets prior to determine the pattern of the electricity consumption of the each of the one or more electricity consuming assets. The method (220) may also include predicting, by a prediction subsystem, a forthcoming electricity consumption of the one or more electricity consuming assets based on the pattern determined by the pattern determining subsystem. In such embodiment, predicting the forthcoming electricity consumption of the one or more electricity consuming assets may include predicting the forthcoming electricity consumption of the one or more electricity consuming assets by comparing the historic data associated with the electricity consumption in the database to a current data associated with the electricity consumption, wherein the current data is extracted from a determined pattern.

In one specific embodiment, the method (220) may include generating, by an alert generation subsystem, an alert signal for one or more entities upon detection of a breakdown in the one or more electricity consuming assets based on the pattern determined by the pattern determining subsystem. In such embodiment, the method (220) may include detecting the breakdown by correlating the pattern of the electricity consumption of each of the one or more electricity consuming assets with a predefined pattern of each of the one or more electricity consuming assets.

In one embodiment, the method (220) may include sending a generated signal to the one or more entities via one of a mode of communication. In such embodiment, sending the generated signal to the one or more entities via one of the mode of communication may include sending the generated signal to the one or more entities via one of a mobile phone, an email account or a future form of a portable communication device.

In one embodiment, the method (220) may include enabling the one or more entities to raise a service request via one of the mode of communication. In such embodiment, enabling the one or more entities to raise the service request may include enabling the one or more entities to raise the service request with one or more service providers, one or more manufactures and the like. In some embodiment, the method (220) may include enabling the one or more entities to control the electricity consumption of the one or more electricity consuming assets via the internet.

Various embodiments of the present disclosure provide a technical solution to the problem of auditing electrical energy. The present disclosure provides an efficient system which audits the electrical energy of each of the one or more electricity consuming assets via a single device using a machine learning or an artificial intelligence technique. Furthermore, the solution eliminates a usage of device level sensors to obtain the device level electricity consumption.

Also, during normalcy of operations, the present device will provide real-time statistics and analytics of the one or more electricity consuming assets which helps in improving the performance or accuracy of the device. Moreover, the present disclosure reduces the down time of the one or more electricity consuming assets by predicting in advance, thereby saving time, efforts, money and lives. Also, the device includes an energy management solution which enables an energy transparency, energy efficiency up to 30% savings, predictive maintenance and asset health monitoring and ensures safety through recognition of anomalies such high and low voltages and power fluctuations.

While specific language has been used to describe the disclosure, limitations arising on account of the same are not intended. As would be apparent to a person skilled in the art, various working modifications may be made to the method in order to implement the inventive concept as taught herein.

The figures and the foregoing description give examples of embodiments. Those skilled in the art will appreciate that one or more of the described elements may well be combined into a single functional element. Alternatively, certain elements may be split into multiple functional elements. Elements from one embodiment may be added to another embodiment. For example, the order of processes described herein may be changed and are not limited to the manner described herein. Moreover, the actions of a flow diagram need not be implemented in the order shown; nor do all of the acts need to be necessarily performed. Also, those acts that are not dependant on other acts may be performed in parallel with the other acts. The scope of embodiments is by no means limited by these specific examples.

Claims

WE CLAIM:

1. A device (20) for auditing electrical energy, the device (20) comprising: one or more processors (40); an electricity monitoring subsystem (50) operable by the one or more processors (40), wherein the electricity monitoring subsystem (50) is configured to monitor data associated with an electricity consumption in a predefined location; a disaggregation subsystem (70) operable by the one or more processors (40), wherein the disaggregation subsystem (70) is configured to disaggregate the electricity consumption monitored by the electricity monitoring subsystem of the predefined location into one or more electricity consuming assets using a disaggregation technique; a parameter capturing subsystem (80) operable by the one or more processors (40), wherein the parameter capturing subsystem (80) is configured to capture one or more parameters associated with each of the one or more electricity consuming assets disaggregated by the disaggregation subsystem; an identification subsystem (100) operable by the one or more processors (40), wherein the identification subsystem (100) is configured to identify the one or more electricity consuming assets in the predefined location based on the one or more parameters of each of the one or more electricity consuming assets captured by the parameter capturing subsystem; and a pattern determining subsystem (110) operable by the one or more processors (40), wherein the pattern determining subsystem (110) is configured to determine a pattern of the electricity consumption from each of the one or more electricity consuming assets identified in the identification subsystem.

2. The device (20) as claimed in claim 1, wherein the one or more parameters comprise voltage and energy.

3. The device (20) as claimed in claim 1, wherein the pattern of the electricity consumption of each of the one or more electricity consuming assets is graphically displayed on a user handheld device.

4. The device (20) as claimed in claim 1, comprising an alert generation subsystem configured to generate an alert signal for one or more entities upon detection of a breakdown in the one or more electricity consuming assets based on the pattern determined by the pattern determining subsystem.

5. The device (20) as claimed in claim 1, comprising a prediction subsystem configured to predict a forthcoming electricity consumption of the one or more electricity consuming assets based on the pattern determined by the pattern determining subsystem.

6. A method (220) for auditing electrical energy, the method comprising: monitoring, by an electricity monitoring subsystem, data associated with an electricity consumption in a predefined location (230); disaggregating, by a disaggregation subsystem, the electricity consumption monitored by the electricity monitoring subsystem of the predefined location into one or more electricity consuming assets using a disaggregation technique (240); capturing, by a parameter capturing subsystem, one or more parameters associated with each of the one or more electricity consuming assets disaggregated by the disaggregation subsystem (250); identifying, by an identification subsystem, the one or more electricity consuming assets in the predefined location based on the one or more parameters of each of the one or more electricity consuming assets captured by the parameter capturing subsystem (260); and determining, by a pattern determining subsystem, a pattern of the electricity consumption from each of the one or more electricity consuming assets identified in the identification subsystem (270).

7. The method (220) as claimed in claim 6, wherein capturing the one or more parameters comprise capturing voltage and energy.

8. The method (220) as claimed in claim 6, comprising displaying, by the pattern determining subsystem, graphically the pattern of the electricity consumption of each of the one or more electricity consuming assets on a user handheld device.

9. The method (220) as claimed in claim 6, comprising generating, by an alert generation subsystem, an alert signal for one or more entities upon detection of a breakdown in the one or more electricity consuming assets based on the pattern determined by the pattern determining subsystem.

10. The method (220) as claimed in claim 6, comprising predicting, by a prediction subsystem, a forthcoming electricity consumption of the one or more electricity consuming assets based on the pattern determined by the pattern determining subsystem.