Smart grid deployment simulator

• US 8,868,452 B2
• Filed: 01/04/2012
• Issued: 10/21/2014
• Est. Priority Date: 05/01/2008
• Status: Active Grant

• Current Assignee: Accenture Global Services Limited (Accenture PLC)
• Original Assignee: Accenture Global Services Limited (Accenture PLC)
• Inventors: Talavera, Gustavo, Parmar, Vaibhav
• Primary Examiner(s): Singh, Gurkanwaljit
• Application Number:
  US13/343,547
• Publication Number:
  US 20120109719A1
• Time in Patent Office: 1,021 Days
• Field of Search: None
• US Class Current: 705/28
• CPC Class Codes: G06Q 10/0637 Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
• CPC Class Codes: G06Q 10/06375 Prediction of business process outcome or impact based on a proposed change
• CPC Class Codes: G06Q 10/067 Enterprise or organisation modelling

Abstract

A decision management system simulates a smart grid communications network service deployment using business and technology changeable parameters, models describing traffic profiles for smart grid domain devices and smart grid applications, smart grid infrastructure and a cost model. Candidate solutions for deploying the smart grid service are determined for different sets of changeable parameters through the simulations. These solutions are analyzed to identify a solution for deploying the smart grid service.

Claims

1. A non-transitory computer readable storage medium including instructions executed by a computer system to perform simulating and analyzing of one or more scenarios for a smart grid communications network service to be deployed, the instructions comprising:

receiving business and technology changeable parameters for the smart grid communications network service to be deployed, wherein the business changeable parameters are financial data for the smart grid communications network service to be deployed;

determining a hierarchal model of a smart grid including domains and utility sections for the smart grid in different levels of the hierarchal model;

identifying, from the hierarchal model of the smart grid, at least one domain and at least one utility section for the smart grid communications network service;

selecting device models from a plurality of device models based on the identified at least one domain and at least one utility section, wherein the selected device models represent different smart grid domain devices in the identified at least one domain and at least one utility section and include traffic profiles for the different smart grid domain devices and smart grid applications executed by the devices;

simulating the smart grid communications network service using the changeable parameters, the device models, and a cost model to determine at least one candidate solution for deploying the service, wherein the at least one candidate solution includes smart grid domain devices and a smart grid application for deploying the smart grid communications network service, estimated bandwidth needed for the smart grid communications network service and estimated monetary costs for the smart grid communications network service,

wherein the simulating includes determining a relationship between the identified at least one domain and another domain in the hierarchal model of the smart grid; and

determining the estimated bandwidth needed for the smart grid communications network service based on the determined relationship; and

generating an analysis of the at least one candidate solution to evaluate an impact of the changeable parameters.

2. The non-transitory computer readable storage medium of claim 1, wherein the domains for the smart grid comprise at least some of utility sections, devices, local area network, backhaul, wide area network, head-end and operations.

3. The non-transitory computer readable storage medium of claim 1, wherein the utility sections for the smart grid comprise at least some of transmission substations, distribution substations, distribution lines, generators, customer, mobile information technology and data center.

4. The non-transitory computer readable storage medium of claim 1, wherein the at least one candidate solution includes a package size for devices for current and future deployment of the service, and the estimated bandwidth comprises raw bandwidth and protocol bandwidth for current and future deployment of the service, and for the estimated bandwidth needed for the service, an amount of the estimated bandwidth provided by a public network and an amount of the estimated provided by a private network.

5. The non-transitory computer readable storage medium of claim 1, wherein the cost model comprises a base case model and the simulating comprises determining the estimated costs based on the base case model, wherein the estimated costs comprise operational costs and capital expenditures for the smart grid communications network service.

6. The non-transitory computer readable storage medium of claim 1, wherein the cost model comprises a network cost model and the simulating comprises determining the estimated costs based on the network cost model, wherein the estimated costs comprise costs for the smart grid domain devices and the smart grid application.

7. The non-transitory computer readable storage medium of claim 1, wherein the cost model includes a dependent model parameter that is dependent on a corresponding dependent model parameter in the model.

8. The non-transitory computer readable storage medium of claim 7, wherein the dependent model parameter varies based on a predetermined relationship with its corresponding dependent model parameter.

9. The non-transitory computer readable storage medium of claim 8, wherein the method further comprises storing mappings that represent the predetermined relationships.

10. The non-transitory computer readable storage medium of claim 1, wherein the simulating comprises simulating the service to determine multiple candidate solutions;

and

generating the analysis includes generating the analysis for each of the multiple candidate solutions to identify a candidate solution that satisfies a business objective and a technology objective.

11. The non-transitory computer readable storage medium of claim 1, wherein the analysis includes cost and revenue projections over a predetermined period of time for deploying the service and technology requirements for deploying the service over the predetermined period of time.

12. A decision management system comprising:

data storage storing device models describing traffic profiles for smart grid domain devices and smart grid applications and a cost model; and

a processor executing a simulation engine to simulate deploying of a smart grid communications network service using business and technology changeable parameters, the device models and the cost model to determine at least one candidate solution, wherein the business changeable parameters are financial data for the smart grid communications network service to be deployed, and

to simulate deploying of the smart grid communications network service, the simulation engine is to

determine a hierarchal model of a smart grid including domains and utility sections for the smart grid;

identify, from the hierarchal model of the smart grid, at least one domain and at least one utility section for the smart grid communications network service;

select the device models from a plurality of device models based on the identified at least one domain and at least one utility section; and

use the traffic profiles from the selected device models for the simulation,

wherein the simulation engine generates an analysis of the at least one candidate solution.

13. The decision management system of claim 12, wherein the at least one candidate solution includes estimations of business and technology parameters describing deployment of the service over a period of time into the future.

14. The decision management system of claim 12, further comprising:

a user interface receiving the business and technology changeable parameters from a user and outputting the analysis.

15. The decision management system of claim 12, wherein the simulation engine simulates the smart grid communications network service deployment by:

determining a relationship between the identified at least one domain and another domain in the hierarchal model of the smart grid; and

determining the estimated bandwidth needed for the smart grid communications network service based on the determined relationship.

16. A method for simulating and analyzing one or more scenarios for a smart grid communications network service to be deployed, the method comprising:

receiving business and technology changeable parameters for the smart grid communications network service to be deployed, wherein the business changeable parameters are financial data for the smart grid communications network service to be deployed;

determining a hierarchal model of a smart grid including domains and utility sections for the smart grid in different levels of the hierarchal model;

identifying, from the hierarchal model of the smart grid, at least one domain and at least one utility section for the smart grid communications network service;

selecting device models from a plurality of device models based on the identified at least one domain and at least one utility section, wherein the selected device models represent different smart grid domain devices in the identified at least one domain and at least one utility section and include traffic profiles for the different smart grid domain devices and smart grid applications executed by the devices;

simulating, by a processor, the smart grid communications network service using the changeable parameters, the device models, and a cost model to determine at least one candidate solution for deploying the service, wherein the at least one candidate solution includes smart grid domain devices and a smart grid application for deploying the smart grid communications network service, estimated bandwidth needed for the smart grid communications network service and estimated costs for the smart grid communications network service,

wherein the simulating includes determining a relationship between the identified at least one domain and another domain in the hierarchal model of the smart grid; and

determining the estimated bandwidth needed for the smart grid communications network service based on the determined relationship; and

generating an analysis of the at least one candidate solution to evaluate an impact of the changeable parameters.