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A Novel Design of User Responsive Smart Meter

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Arjun .M.M.
Arjun .M.M.

This document proposes a novel design for a user-responsive smart meter integrated with an automated energy management system (EMS) within a supervisory control and data acquisition (SCADA)-interfaced smart grid. The system introduces distributed smart meters that intelligently notify consumers of power consumption rates and behaviors to encourage energy savings. It also isolates faulty or illegal supply connections. The design includes current and potential transformers connected to a programmable logic controller and monitoring unit, with communication enabled by Zigbee and a consumer notification system using LED, buzzer and SMS. The aim is optimized energy management within households and industries to better manage loads and prevent demand peaks in the smart grid.

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A Novel Design of User Responsive Smart Meter Integrated Automated EMS in SCADA Interfaced Smart Grid Presented by Group V
Abstract Electricity supply is rapidly becoming more complex and variable where energy efficiency rules are still evolving only to limited end. A near future with millions of electric vehicles and industrial loads will dramatically increase the necessity of a demand modulation system. The best way of practicing demand management is user responsive load management at the consumer ends. It will be difficult to alter consumer behaviour in the direction of energy savings unless consumers are more exposed to market prices than at present. The proposed system introduces a distributed smart meter that intelligently notifies the power consumption rate at various time intervals based on demand factors and power loss factors. It also notifies the characteristic behaviour of consumption to the consumer via GSM communication system, and isolates the supply for various faults and power theft. A new intelligent TLPF algorithm has been implemented that confronts all these features and executed using a SCADA controller.
Existing System The present electricity networks have a technical hierarchy where energy flows from large, centralized, fully controllable power plants to more or less passive customers at the receiving end of the network. The system does not have periodic updates of power consumptions with the user. The consumed data will arrive to the customers in the manner of written format. It makes the possibilities for human error.
Proposed system The proposed system offers a better modelling for the development of an intelligent smart grid system with the help of user acknowledged distributed remote smart meters interfaced in a distributed control structure aided Supervisory Control and Data Acquisition (SCADA) system with PLC, thus to avoid many strategies related to power systems, improving the efficiency and eliminating the fractional losses and power theft absolutely. The system may have many applications for optimizing overall energy management within the house hold consumers and industries, manages the load in the grid and prevent power demand peaks with an interface between the utility- controlled smart grid and consumers.
Block Diagram: Consumers Area: Input Programmable Logical Controller Output Current transformer Potential transformer Zigbee Relay 2 Load Rectifications (ADC) Rectifications (ADC) LED Relay 1 Buzzer
Monitoring or Distributer Unit:
Process Needs: Hardware requirements: Current transformers Potential transformers Zigbee PLC PC LED Buzzer Rectifier Software Requirements: PLC Programming: WPL Soft V2.36 I/O Interfacing: Kepserver SCADA: Wonderware Intouch LabVIEW Type: Prototype model
References: 1. A Smart energy Meter Architecture, Prudhvi, Potuganti , Pages 1 - 6 Iranian Conference on Smart Grids (ICSG), 2nd Jan2012. 2. Evaluation of residential smart meter policies, WEC-ADEME Case studies on Energy Efficiency Measures and Policies , Jessica Strom back and Christophe Dromacque, VaasaETT Global Energy Think Tank 3. Implementing the Energy Efficiency Directive provision for easy access to 24 months of daily/weekly/monthly/annual consumption data for consumers with smart meters. Department of Energy and Climate Change, Orchard 3, Lower Ground, London. 4. D. Li, Z. Aung, J. Williams and A. Sanchez, "Efficient Authentication Scheme for Data Aggregation in Smart Grid Fault tolerance and Fault diagnosis", IEEE Power and Energy Society Conference on Innovative Smart Grid Technologies (lSGT'12), 1-8 (2012). 5. Hart, D.G.; "Using AMI to Realize the Smart Grid," IEEE PES General Meeting, July 2008, pp. l - 2.
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A Novel Design of User Responsive Smart Meter

  • 1. A Novel Design of User Responsive Smart Meter Integrated Automated EMS in SCADA Interfaced Smart Grid Presented by Group V
  • 2. Abstract Electricity supply is rapidly becoming more complex and variable where energy efficiency rules are still evolving only to limited end. A near future with millions of electric vehicles and industrial loads will dramatically increase the necessity of a demand modulation system. The best way of practicing demand management is user responsive load management at the consumer ends. It will be difficult to alter consumer behaviour in the direction of energy savings unless consumers are more exposed to market prices than at present. The proposed system introduces a distributed smart meter that intelligently notifies the power consumption rate at various time intervals based on demand factors and power loss factors. It also notifies the characteristic behaviour of consumption to the consumer via GSM communication system, and isolates the supply for various faults and power theft. A new intelligent TLPF algorithm has been implemented that confronts all these features and executed using a SCADA controller.
  • 3. Existing System The present electricity networks have a technical hierarchy where energy flows from large, centralized, fully controllable power plants to more or less passive customers at the receiving end of the network. The system does not have periodic updates of power consumptions with the user. The consumed data will arrive to the customers in the manner of written format. It makes the possibilities for human error.
  • 4. Proposed system The proposed system offers a better modelling for the development of an intelligent smart grid system with the help of user acknowledged distributed remote smart meters interfaced in a distributed control structure aided Supervisory Control and Data Acquisition (SCADA) system with PLC, thus to avoid many strategies related to power systems, improving the efficiency and eliminating the fractional losses and power theft absolutely. The system may have many applications for optimizing overall energy management within the house hold consumers and industries, manages the load in the grid and prevent power demand peaks with an interface between the utility- controlled smart grid and consumers.
  • 5. Block Diagram: Consumers Area: Input Programmable Logical Controller Output Current transformer Potential transformer Zigbee Relay 2 Load Rectifications (ADC) Rectifications (ADC) LED Relay 1 Buzzer
  • 7. Process Needs: Hardware requirements: Current transformers Potential transformers Zigbee PLC PC LED Buzzer Rectifier Software Requirements: PLC Programming: WPL Soft V2.36 I/O Interfacing: Kepserver SCADA: Wonderware Intouch LabVIEW Type: Prototype model
  • 8. References: 1. A Smart energy Meter Architecture, Prudhvi, Potuganti , Pages 1 - 6 Iranian Conference on Smart Grids (ICSG), 2nd Jan2012. 2. Evaluation of residential smart meter policies, WEC-ADEME Case studies on Energy Efficiency Measures and Policies , Jessica Strom back and Christophe Dromacque, VaasaETT Global Energy Think Tank 3. Implementing the Energy Efficiency Directive provision for easy access to 24 months of daily/weekly/monthly/annual consumption data for consumers with smart meters. Department of Energy and Climate Change, Orchard 3, Lower Ground, London. 4. D. Li, Z. Aung, J. Williams and A. Sanchez, "Efficient Authentication Scheme for Data Aggregation in Smart Grid Fault tolerance and Fault diagnosis", IEEE Power and Energy Society Conference on Innovative Smart Grid Technologies (lSGT'12), 1-8 (2012). 5. Hart, D.G.; "Using AMI to Realize the Smart Grid," IEEE PES General Meeting, July 2008, pp. l - 2.