Methods and systems architecture to virtualize energy functions and processes into a cloud based model

• US 9,343,903 B2
• Filed: 03/11/2014
• Issued: 05/17/2016
• Est. Priority Date: 03/14/2013
• Status: Active Grant

• Current Assignee: Mark Hauenstein
• Original Assignee: Mark Hauenstein
• Inventors: Hauenstein, Mark
• Primary Examiner(s): Shah, Kamini S
• Assistant Examiner(s): PIERRE LOUIS, ANDRE
• Application Number:
  US14/203,576
• Publication Number:
  US 20140278327A1
• Time in Patent Office: 798 Days
• Field of Search: 703/18, 703/1, 703/13
• US Class Current: 1/1
• CPC Class Codes: F24F 11/30 for purposes related to the operation of the system, e.g. for safety or monitoring
• CPC Class Codes: F24F 11/47 Responding to energy costs
• CPC Class Codes: F24F 11/58 using Internet communication
• CPC Class Codes: F24F 11/62 characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
• CPC Class Codes: F24F 11/63 Electronic processing
• CPC Class Codes: G06F 30/20 Design optimisation, verification or simulation optimisation, verification or simulation of circuit designs G06F30/30
• CPC Class Codes: H02J 2203/20 Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
• CPC Class Codes: H02J 3/00 Circuit arrangements for ac mains or ac distribution networks
• CPC Class Codes: Y02E 60/00 Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
• CPC Class Codes: Y04S 40/20 Information technology specific aspects, e.g. CAD, simulation, modelling, system security

Abstract

A system for creating an energy performance and predictive model includes a non-transitory computer-readable storage medium which performs the steps of obtaining parametric information objects that represent actual physical objects and modifying the parametric information by embedding data related to energy performance characteristics unique to the device represented. The system further performs the steps of grouping the modified parametric information objects that define actual real world interrelationships to create a complete virtualized project and parsing the virtualized model data set to create a first parsed data set and a second parsed data set. The first parsed data set creates the project system control application, which acts upon and coordinates the actions of the real device through the virtual field bus. The second parsed data set creates the project'"'"'s virtualized energy performance project and represents the subset of the virtualized performance environment where other virtualized devices can act upon it.

Claims

1. A non-transitory computer-readable storage medium storing instructions for creating a virtual cloud-based environment representing, controlling, and predicting the performance of a plurality of physical energy generating and consuming devices, the instructions, when executed by a computing device, cause the computing device to perform the following steps:

representing one or more physical energy generating or energy consuming devices that are configured in a physical environment each as a corresponding one or more parametric information objects;

embedding in each of the one or more parametric information objects data related to energy performance characteristics unique to its corresponding physical energy device;

grouping the parametric information objects that define physical interrelationships among the one or more physical devices to create a virtualized project design model; and

parsing embedded parametric information from the virtualized project design model to create a first parsed data set and a second parsed data set, wherein;

the first parsed data set comprises project system control application data that is read by a system control application, which acts upon and coordinates actions of the one or more physical energy devices through a virtual field bus, the virtual field bus configured in a cloud-based real time data exchange to interface virtualized project design model data with physical data associated with the one or more physical energy objects; and

the second parsed data set comprises extracted energy performance data used to;

create a virtualized energy performance project, the virtualized energy performance project including at least a subset of the one or more parametric information objects and an energy consumption predictive function; and

represent the subset of the parametric information objects from the virtualized performance project so as to permit other parametric information objects to exchange state and control data therewith in real time.

2. The non-transitory computer-readable storage medium of claim 1, wherein:

the virtualized energy performance project comprises;

a static model interacting with the parametric information data objects; and

a dynamic model interfaced with the static model, and

wherein the instructions further cause the computing device to;

provide to the dynamic model data regarding current performance of the one or more physical energy devices; and

affect changes to the one or more physical energy devices by inputting and outputting data to and from the dynamic model to the one or more physical energy devices via the virtualized field bus in a real time data exchange;

cause the dynamic model to communicate with the static model in order to;

register with the parametric information data objects user preferences and data that may have an effect on consumption, use, environmental, and costing variables; and

communicate in real time changes made by the dynamic model that may have an effect on consumption, use, environmental, and costing variable.

3. The non-transitory computer-readable storage medium of claim 2, further including instructions that, when executed by the computing device, cause the computing device to:

compare performance information associated with the physical energy devices communicated to the dynamic model to performance predicted by the static model;

predict energy performance in the future in real time;

and

analyze energy flow among the one or more physical energy devices, and associated energy generation and consumption transactional costs.

4. The non-transitory computer-readable storage medium of claim 3, further including instructions that, when executed by the computing device, causes the computing device to:

provide a real-time interface to the virtualized project design model using at least one of user input, or machine to machine interaction.

5. The non-transitory computer-readable storage medium of claim 1, further including instructions that, when executed by the computing device, causes the computing device to:

create a 3D real time management and control tool, using a uniform resource locator, polymorphism, or a combination thereof,

to communicate with and update in real time the parsed parametric information from the virtualized project design model to an original parametric model.

6. The non-transitory computer-readable storage medium of claim 1, wherein the storage medium comprises distributed storage memory remote from the one or more physical energy generating or energy consuming devices.

7. The non-transitory computer-readable storage medium of claim 6, further including instructions that, when executed by the computing device, cause the computing device to

aggregate parametric information data objects representing energy generational sources by type;

provide data regarding current generation in a physical system; and

provide data based on user preferences that may have an effect on generation moving forward;

create a virtualized model regarding the physical system inputting data;

create a predictive model regarding future generation;

track and summarizing each generational source performance variables; and

,

compare the predictive model to actual generation to evaluate and modify the performance of the predictive model.

8. The non-transitory computer-readable storage medium of claim 7, wherein the data related to energy performance characteristics of the one or more physical energy devices includes at least one of:

source data;

generation data;

environmental data;

or

sensor data.

9. The non-transitory computer-readable storage medium of claim 8, further including instructions that, when executed by a computing device, cause the computing device to:

create ancillary service within an electrical grid to offset transient electrical load conditions and distribution power factor by adjusting consumption demand in real time resolution between energy suppliers and energy consumers.

10. The non-transitory computer-readable storage medium of claim 9, further including instructions that, when executed by a computing device, cause the computing device to:

aggregate users by source generation type;

provide usage data regarding current usage in the physical system; and

provide preference data based on user preferences that may have an effect on consumption moving forward;

create a virtualized model regarding the physical system inputting data;

create a predictive model regarding future consumption;

track and summarizing each user'"'"'s consumption performance variables; and

,

compare the predictive model to actual consumption demands to evaluate and modify the performance of the predictive model.

11. The non-transitory computer-readable storage medium of claim 10, wherein the usage data or preference data includes at least one of:

source data;

generation data;

environmental data;

or

sensor data.

12. The non-transitory computer-readable storage medium of claim 11, further including instructions that, when executed by a computing device, cause the computing device to:

create a transactional model to allow for real time resolution between energy suppliers and energy consumers.

13. The non-transitory computer-readable storage medium of claim 12, wherein resolution between energy suppliers and energy consumers includes at least one of:

delaying electrical loads in order to participate in at least one of load demand response or power factor load balancing;

segregate virtualized loads and their associated energy use by user and based on users utility preferences, associate electrical consumption to electrical generation by generational type in real time;

place requests for particular electrical energy generational types with independent service operators (ISO'"'"'s) or other participants and track consumption model requests with generational model responses and establish tiered pricing levels in real time;

segregate virtualized electrical generational types and their associated environmental impact, along with specific costs, losses, and tariffs between any particular generational sources and any particular consumer;

or

allow users to select utility generational sources using a tiered billing structure for each virtualized device.