Automating LV Distribution networks using sensor technologies

Transcription

1 Automating LV Distribution networks using sensor technologies Jayant Sinha Lead Consultant (Smart Networks) Enzen Global Ltd, UK 1

2 Managing the last mile Growing pressure on DNOs to improve LV network visibility Stringent guidelines from regulators to meet performance standards CAIDI, CAIFI, CI & CML Demand of better services under new electricity regulations Distribution utilities exploring options to manage LV networks efficiently and effectively Sensor-based technologies are the key to managing low voltage networks down to the last mile 2

3 Sensor technologies for LV Distribution Key objectives Condition-based monitoring of distribution network Proactive network maintenance Improved operational efficiency & reduced downtime Expected benefits Optimum utilization of assets Workforce optimization Reduced cost of operations Readiness for future integration with SCADA/ DMS/ OMS 3 3

4 Introducing sensors to key applications Asset management system Transformer monitoring system Fault management and service restoration Real time network analysis Power quality monitoring Peak load management, and Automated demand response 4

5 Asset management Need to track network assets throughout the life cycle Sensors provide precise inventory control with the ability to manage, track and secure critical assets in real-time Wireless RFID tags placed on a network asset such as distribution transformer or smart meter Attached to assets, active RFID tags communicate with RF reader near the assets and linked via wireless or data communication bus to the computer RFID technology thus helps in asset planning, deployment, tracking and optimization. 5

6 Transformer health monitoring Distribution transformer is the heart of LV networks Sensors reduces risk of transformer failures, cut maintenance costs Makes predictive analysis possible, prevents faults & Detects voltage sags or swells, abnormal loading and state of the asset 6

7 Transformer health monitoring Sensor-based monitoring of state of the network: Current loading/ overcurrent Surface or Winding temperature Oil level/ Oil quality Event alarms Sensor data collected and transmitted to remote application Proactive action in fault prevention; increasing reliability of network. Telemetry systems GPRS, PLCC, RF or Zigbee Sensors RTUs Control Room 7

8 Fault management and service restoration Fault passage sensors on LV system measure current flow in real time; detect overloading, short circuit or earth fault Sensor signals displayed on remote Digital Fault Recorder (DFR); information used to validate location of fault Early fault detection provide better understanding of vulnerable section for taking suitable corrective action Regulatory pressure to reduce frequency (CI) & duration of outages (CML), and Penalties/ incentives linked to performance influencing decisions to use sensors 8

9 Fault management and service restoration Abnormal data from sensors are analyzed to detect and isolate faulty sections Optimize switching plans, considering network constraints, system interlocks and protective devices Alternate network plans to minimize the impact of power disruption Re-energize heathy sections upstream and downstream outside isolated section, & Facilitate early restoration of services to a large part of network without overloading. 9

10 Real time network analysis Substation SCADA receive regular data from sensors via remote terminal units (RTUs) in real time for analysis Sensors detect abnormal load variations, harmonics or physical parameters like transformer temperature and oil level Sensors have made predictive analysis possible for network fault prevention, optimization and planning Load flow analytics can help determine state of the network and identify causes which might lead to fault Intelligent Distribution Management System (DMS) rely on sensors for realtime analysis and modelling of network, & Provide intelligence to operate protective devices in a coordinated manner, isolate faulty sections and restore normalcy through alternate switching plan 10

11 Power Quality monitoring Power quality of LV distribution system is affected by overloading, capacitor switching transients, impulse transients or harmonic distortions Proliferation of UPS, invertors, power electronic devices and renewable energy sources induce harmonics in electrical supply Many loads are not purely resistive and presence of magnetizing current, effect of rectification and inherent impedance result in harmonics or transients which degrade power quality Smart meters, protection relays and fault recorders may not measure all power quality parameters Sensors and telemetry systems monitor power quality and analyse data to reduce their effects, making electrical network more efficient 11

12 Power Quality monitoring Sensor technology solves quality problems by timely identifying specific sources of harmonics Sensors measure and record harmonic and inter-harmonic frequencies, present on main supply Sensor data is transmitted via communications network to centralised database Low cost of sensor with the convenience of wireless communication, enables monitor power quality at multiple locations of the network, & Reduces cost by eliminating expensive diagnostic instrumentation, e.g. power quality analysers. 12

13 Peak load management Sensors are transforming operation of LV networks combining ICT to build intelligence Modern applications use sensors to make efficient use of energy, automation and enable peak load management. Interconnecting consumer devices on home area networks communicate with utility networks to facilitate residential energy management Residential energy management uses utilitydriven price signals (TOU pricing) to regulate energy consumption during peak hours, & Reducing peak load decreases generation expenses with corresponding decrease in greenhouse emissions 13

14 Automated demand response Refers to smart grid device or application interacting with customers to influence their consumption of electricity during select time periods Signals customers to decide to lower their consumption during peak periods, and shift their demand to off-peak periods Achieve a balance between electricity generation and demand, helping in load optimization and grid stability Sensors and advanced control systems on LV network interact with load control systems to manage peak loads, & Inherent benefits of automation bring reliable, faster and cheaper responses to load demand signals. 14

15 Automated demand response Auto DR requires both the grid and demand-side entities to install infrastructure to support the exchange of signals The grid entity puts in place sensors capable of communicating DR signals to customer s automation equipment and customer installs equipment capable of receiving these signals DR signals are relayed to the control systems where response strategies have been programmed for appropriate load control The smart network will receive feedback of the DR signal on the facility s consumption via smart meter, & Auto DR provides way for distribution operators to avail of more demand-side resources as cheaper option for grid balancing 15

16 Conclusion Assessment studies on the impact of sensor technology on LV networks reveal its potential in Improving operational efficiencies Proactive fault management Improving power quality and network reliability Controlling technical losses Other advantages of sensor technologies is the contribution to Reduction of greenhouse gas emissions Maintain health of LV networks in a sustainable manner Combined with DSM, contribute to energy efficiency, load management and optimized network operation Achieve carbon reduction goals 16

17 Thank you! Jayant Sinha Lead Consultant (Smart Networks) 17