DETAILED ACTION
Claims 1-8 are pending.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-8 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Mieth, Robert, et al. "Learning-enabled residential demand response: Automation and security of cyberphysical demand response systems." IEEE Electrification Magazine 9.1 (2021): 36-44.
1. A response interaction system for intelligently interacting with a low-voltage user, comprising: a distribution network and system master station, an intelligent electric meter, a mobile APP (application), an intelligent interaction terminal, an intelligent gateway, and a low-voltage user load, (Figure 1, Pages 37-38 – sections labeled “The DR Process” and “Aggregation” - - see intelligent Utility SCADA, and intelligent virtual end node, intelligent virtual top node, intelligent customer interfaces and low-voltage user loads, such as HVAC loads and other IOT appliances) wherein the distribution network and system master station, the intelligent electric meter, the low-voltage user load, the intelligent gateway, the intelligent interaction terminal, and the mobile APP are wirelessly connected, and the distribution network and system master station is wirelessly connected to the mobile APP (Figure 1, Pages 37-38 – sections labeled “The DR Process” and “Aggregation” - - wireless communication). See Figure 1 below:
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2. The response interaction system for intelligently interacting with a low-voltage user according to claim 1, wherein following information flows are transmitted in the response interaction system: information flow 1 transmitted between the low-voltage user and the mobile APP, wherein the mobile APP is configured to perform a demand response invitation, a quotation and a verification, and remotely control and execute a demand response (Figure 1, Pages 37-38 – sections labeled “The DR Process” and “Aggregation” - - see communication scheme for Demand Response programs);
information flow 2 transmitted between the mobile APP and the intelligent interaction terminal, wherein the mobile APP is configured to transmit an execution instruction for a demand response task to the intelligent interaction terminal (Figure 1, Pages 37-38 – sections labeled “The DR Process” and “Aggregation” - - see communication scheme for Demand Response programs);
information flow 3 transmitted between the intelligent interaction terminal and the intelligent gateway, wherein the intelligent interaction terminal is configured to remotely control the low-voltage user load through the intelligent gateway (Figure 1, Pages 37-38 – sections labeled “The DR Process” and “Aggregation” - - see communication scheme for Demand Response programs);
information flow 4 transmitted between the intelligent gateway and the low-voltage user load, wherein the intelligent gateway is configured to transmit an instruction to control the low-voltage user load to operate or not operate (Figure 1, Pages 37-38 – sections labeled “The DR Process” and “Aggregation” - - see communication scheme for Demand Response programs);
information flow 5 transmitted between the low-voltage user load and the intelligent electric meter, wherein the intelligent electric meter is configured to acquire a state of the low-voltage user load that operates or does not operate, and then generate and transmit a message (Figure 1, Pages 37-38 – sections labeled “The DR Process” and “Aggregation” - - see communication scheme for Demand Response programs);
and information flow 6 transmitted between the intelligent electric meter and the mobile APP, wherein the intelligent electric meter is configured to transmit an execution result of the demand response task to the mobile APP (Figure 1, Pages 37-38 – sections labeled “The DR Process” and “Aggregation” - - see communication scheme for Demand Response programs).
3. The response interaction system for intelligently interacting with a low-voltage user according to claim 1, wherein the distribution network and system master station and the mobile APP perform communication through a 4G/5G communication network, a private wireless network or a fiber optic private network; and the mobile APP and the intelligent interaction terminal, the intelligent interaction terminal and the intelligent gateway, and the intelligent gateway and the low-voltage user load respectively perform communication based on a Wi-Fi technology, a Bluetooth technology or a Zigbee technology (Figure 1, Pages 37-38 – sections labeled “The DR Process” and “Aggregation” - - see communication scheme for Demand Response programs).
4. The response interaction system for intelligently interacting with a low-voltage user according to claim 3, wherein the distribution network and system master station and the mobile APP, the mobile APP and the intelligent interaction terminal, the intelligent interaction terminal and the intelligent gateway (Figure 1, Pages 37-38 – sections labeled “The DR Process” and “Aggregation” - - see communication scheme for Demand Response programs).
and the intelligent gateway and the low-voltage user load respectively perform communication with an encryption algorithm; and according to the encryption algorithm, a security protection mechanism is constructed by using an account password and a protocol encryption algorithm, an IP address, a MAC address, a spectrum, an orientation and an intensity feature of a communication link are analyzed, and a feature fingerprint of a legitimate intelligent home gateway is extracted by using a clustering analysis algorithm, to detect and identify an illegal communication link (Figure 1, Pages 37-38 – sections labeled “The DR Process” and “Aggregation” - - see communication scheme for Demand Response programs).
5. The response interaction system for intelligently interacting with a low-voltage user according to claim I, wherein the low-voltage user load is one or a combination of a computer, an illuminating device, a water heater, an air conditioner, a sweeping machine, a washing machine, a dishwasher, and an electric vehicle (Figure 1, Pages 37-38 – sections labeled “The DR Process” and “Aggregation” - - see communication scheme for Demand Response programs).
6. A response interaction method for intelligently interacting with a low-voltage user, comprising a process of the low-voltage user participating in a demand response, wherein the process of the low-voltage user participating in the demand response comprises: step S1, transmitting, by a distribution network and system master station, a demand response plan and a demand response notification through a mobile APP (application) (Figure 1, Pages 37-38 – sections labeled “The DR Process” and “Aggregation” - - see intelligent Utility SCADA, and intelligent virtual end node, intelligent virtual top node, intelligent customer interfaces and low-voltage user loads, such as HVAC loads and other IOT appliances);
step S2, receiving, by the low-voltage user, the demand response notification through the mobile APP, and acquiring, by the low-voltage user, an operation guide for performing a demand response task (Figure 1, Pages 37-38 – sections labeled “The DR Process” and “Aggregation” - - see communication scheme for Demand Response programs);
step S3, connecting the low-voltage user to an intelligent interaction terminal through the mobile APP, and transmitting, by the low-voltage user, an operation instruction related to the demand response task (Figure 1, Pages 37-38 – sections labeled “The DR Process” and “Aggregation” - - see communication scheme for Demand Response programs);
step S4, transmitting, by the intelligent interaction terminal through an intelligent gateway, an operation instruction to an intelligent circuit breaker corresponding to a load connected to the intelligent gateway to control the intelligent circuit breaker to be turned on or turned off (Figure 1, Pages 37-38 – sections labeled “The DR Process” and “Aggregation” - - see communication scheme for Demand Response programs);
and step S5, determining, by the low-voltage user through the mobile APP, an execution state of the demand response task, and performing, by the low-voltage user, the demand response task. (Figure 1, Pages 37-38 – sections labeled “The DR Process” and “Aggregation” - - wireless communication). See Figure 1 below:
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7. The response interaction method for intelligently interacting with a low-voltage user according to claim 6, wherein an intelligent electric meter generates a message and transmits the message to the distribution network and system master station, the distribution network and system master station analyzing the message to acquire the execution state of the demand response task of the low-voltage user, and transmits an execution result of the demand response task through the mobile APP (Figure 1, Pages 37-38 – sections labeled “The DR Process” and “Aggregation” - - see communication scheme for Demand Response programs)
8. The response interaction method for intelligently interacting with a low-voltage user according to claim 7, wherein the intelligent electric meter transmits the message, and communicates and interacts with the distribution network and system master station in a powerline communication manner (Figure 1, Pages 37-38 – sections labeled “The DR Process” and “Aggregation” - - see communication scheme for Demand Response programs).
Citation of Pertinent Prior Art
The following prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Hammerstrom, Donald J., and Chellury Sastry. Progress Toward Producing Demand-Response-Ready Appliances. No. PNNL--19075. Pacific Northwest National Lab.(PNNL), Richland, WA (United States), 2009.
Mataloto, Bruno, Joao C. Ferreira, and Nuno Cruz. "LoBEMS—IoT for building and energy management systems." Electronics 8.7 (2019): 763.
US-20080167931-A1, Gerstemeier; Richard Allen – relates to community resource management.
US-20080177678-A1, Di Martini; Paul – relates to communicating between a utility and its customer locations.
US-8359124-B2, Zhou; Zhi – relates to energy optimization system.
US-8621097-B2, Venkatakrishnan; Natarajan – relates to low cost and flexible energy management system.
US-8666560-B2, Lu; Jin – relates to power control system and method.
US-8780790-B2, Sarkar; Sandip – relates to TDD operation in wireless communication systems.
US-10541556-B2, Dutta et al., - relates to integrate and manage diverse demand response.
Conclusion
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/CARLOS R ORTIZ RODRIGUEZ/ Primary Examiner, Art Unit 2119