ELECTRICAL DISTRIBUTION NETWORK IMPROVEMENT FOR PLUG-IN ELECTRIC VEHICLES

• US 20120271437A1
• Filed: 03/08/2012
• Published: 10/25/2012
• Est. Priority Date: 03/10/2011
• Status: Active Grant

• Current Assignee: Accenture Global Services Limited (Accenture PLC)
• Original Assignee: Accenture Global Services Limited (Accenture PLC)
• Inventors: Senart, Aline, Kurth, Scott W., Souche, Christian
• Granted Patent: US 9,106,101 B2
• Time in Patent Office: Days
• US Class Current: 700/29
• CPC Class Codes: B60L 2240/72 Charging station selection relying on external data
• CPC Class Codes: B60L 2260/44 by parameter estimation
• CPC Class Codes: B60L 3/0046 relating to electric energy storage systems, e.g. batteries or capacitors
• CPC Class Codes: B60L 3/0069 relating to the isolation, e.g. ground fault or leak current
• CPC Class Codes: B60L 3/04 Cutting off the power supply under fault conditions protective devices and circuit arrangements in general H01H; H02H
• CPC Class Codes: B60L 53/14 Conductive energy transfer
• CPC Class Codes: B60L 53/305 Communication interfaces
• CPC Class Codes: B60L 53/63 in response to network capacity
• CPC Class Codes: B60L 53/64 Optimising energy costs, e.g. responding to electricity rates
• CPC Class Codes: B60L 53/65 involving identification of vehicles or their battery types
• CPC Class Codes: B60L 53/665 Methods related to measuring, billing or payment
• CPC Class Codes: B60L 53/68 Off-site monitoring or control, e.g. remote control
• CPC Class Codes: B60L 55/00 Arrangements for supplying energy stored within a vehicle to a power network, i.e. vehicle-to-grid [V2G] arrangements
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 50/06 Energy or water supply
• CPC Class Codes: H02J 2203/20 Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
• CPC Class Codes: H02J 2310/48 for electric vehicles [EV] or hybrid vehicles [HEV]
• CPC Class Codes: H02J 2310/54 according to a pre-established time schedule
• CPC Class Codes: H02J 2310/60 Limiting power consumption in the network or in one section of the network, e.g. load shedding or peak shaving
• CPC Class Codes: H02J 2310/64 The condition being economic, e.g. tariff based load management
• CPC Class Codes: H02J 3/003 : Load forecast, e.g. methods or systems for forecasting future load demand
• CPC Class Codes: H02J 3/14 : by switching loads on to, or off from, network, e.g. progressively balanced loading
• CPC Class Codes: Y02B 70/3225 : Demand response systems, e.g. load shedding, peak shaving
• CPC Class Codes: Y02E 60/00 : Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
• CPC Class Codes: Y02T 10/70 : Energy storage systems for electromobility, e.g. batteries
• CPC Class Codes: Y02T 10/7072 : Electromobility specific charging systems or methods for batteries, ultracapacitors, supercapacitors or double-layer capacitors
• CPC Class Codes: Y02T 10/72 : Electric energy management in electromobility
• CPC Class Codes: Y02T 90/12 : Electric charging stations
• CPC Class Codes: Y02T 90/14 : Plug-in electric vehicles
• CPC Class Codes: Y02T 90/16 : Information or communication technologies improving the operation of electric vehicles
• CPC Class Codes: Y02T 90/167 : Systems integrating technologies related to power network operation and communication or information technologies for supporting the interoperability of electric or hybrid vehicles, i.e. smartgrids as interface for battery charging of electric vehicles [EV] or hybrid vehicles [HEV]
• CPC Class Codes: Y04S 10/126 : the energy generation units being or involving electric vehicles [EV] or hybrid vehicles [HEV], i.e. power aggregation of EV or HEV, vehicle to grid arrangements [V2G]
• CPC Class Codes: Y04S 10/50 : Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
• CPC Class Codes: Y04S 20/222 : Demand response systems, e.g. load shedding, peak shaving
• CPC Class Codes: Y04S 30/14 : Details associated with the interoperability, e.g. vehicle recognition, authentication, identification or billing
• CPC Class Codes: Y04S 40/20 : Information technology specific aspects, e.g. CAD, simulation, modelling, system security

Abstract

Electrical distribution network (EDN) improvement method for plug-in electric vehicles receives and stores in a database EDN configuration information, demography information and load information for simulating load of the EDN assets. The method dynamically updates the EDN configuration, demography information and/or load information to provide an efficient and customizable method of simulating a PEV load impact on an EDN configuration and apply improvements to the EDN in real time.

Claims

1. An electrical distribution network improvement method comprising:

receiving user input, wherein the user input comprises electrical distribution network (EDN) configuration information, demography information and load information;

storing the user input in a database;

performing a first simulation using a simulator based at least on the EDN configuration information, the demography information or the load information stored in the database to obtain a first simulation result;

analyzing the first simulation result using an analytics engine to obtain a first interpretation result;

determining at least one improvement program based on the first interpretation result;

updating the EDN configuration information based on the determined improvement program;

performing an improvement simulation based on the updated EDN configuration information; and

applying the improvement program to the EDN.

2. The method of claim 1, wherein applying the improvement program to the EDN comprises:

based on a request for usage allocation to be made in one or more nodes of the EDN, obtaining one or more real-time measurements of the EDN;

determine at least one change to at least one plug-in electric vehicle (“

PEV”

) node in order to meet the usage allocation; and

modifying the EDN based on the determined at least one change to be made to the EDN.

3. The method of claim 1, wherein updating the EDN configuration information based on the interpretation result comprises calculating a plug-in electric vehicle (“

PEV”

) load information and updating the load information with the PEV load information.

4. The method of claim 1, further comprising:

updating at least one of EDN configuration information, demography information and load information;

performing a second simulation using the simulator based on the updated at least one of the EDN configuration information, the demography information or the load information to obtain a second simulation result; and

analyzing the second simulation result using the analytics engine to obtain a second interpretation result.

5. The method of claim 1, wherein determining the at least one improvement program based comprises determining the at least one improvement program based on at least a first interpretation result or a second interpretation result.