A low voltage (LV) distribution network is the last link that connects consumers in the power supply chain. Electricity regulators are demanding better services from distribution network operators (DNOs) and have put in place stringent guidelines for meeting performance standards as well as network reliability indices such as the Customer Average Interruption Duration Index, Customer Average Interruption Frequency Index, Customer Interrupted [CI] Index and Current Mode Logic (CML).
There is increasing pressure on DNOs to improve the visibility of LV networks. As a result, distri-bution utilities are exploring options for man-aging LV networks in a more efficient and effective manner down to the last mile, for which they are turning to sensor-based technologies.
Key objectives and benefits
Sensor technologies enable condition-based monitoring of a distribution network. In addition, they offer proactive network maintenance, improved operational efficiency and reduced downtime.
The key benefits of such technologies include optimum utilisation of assets as well as of the workforce, and reduced cost of operations. They also facilitate network readiness for future integration with supervisory control and data acquisition (SCADA) systems, distribution management systems (DMSs) and order management systems.
Sensor use in key applications
Sensor-based technologies can be introduced in the following key applications in a network:
Asset management system: Network assets need to be tracked throughout their life cycle. In this context, sensors provide precise inventory control to manage, track and secure critical assets in real time. Wireless radio frequency identification (RFID) tags are placed on network assets like distribution transformers or smart meters. These tags communicate with a radio frequency reader near the asset, which is linked via wireless or data communication bus to a computer. RFID technology thus helps in asset planning, deployment, tracking and optimisation.
Transformer monitoring system: The distribution transformer is the heart of an LV network. Sensors reduce the risk of transformer failure; cut main-tenance costs; enable predictive analyses; prevent faults; and detect voltage sags or swells, abnormal loading and the state of the asset. Sensor-based monitoring of the network is done through parameters like current loading or overcurrent; surface or winding temperatures; oil level or oil quality; and event alarms. This ensures proactive action and fault prevention, thereby increasing the reliability of a network. Telemetry systems such as GPRS, power line communication, radio frequency and ZigBee are deployed for transmitting sensor data to remote applications.
Fault management and service restoration: Fault passage sensors on an LV system measure
current flow in real time and also detect overloading, short circuits and earth faults. Sensor signals are displayed on the remote digital fault recorder and this information is used to validate fault location. Early fault detection provides a better understanding of a vulnerable section so that suitable corrective action can be taken. This is all the more important considering the regulatory pressures to reduce the frequency (CI) and duration of outages (CML). Penalties and incentives are linked to performance, thereby influencing the decision to use sensors.
Abnormal data from sensors is analysed to detect and isolate faulty sections. Doing this also helps optimise switching plans, considering network constraints, system interlocks and protective devices. Sensor technologies re-
energise healthy sections upstream and downstream outside the isolated section, and facilitate the early restoration of services to a large part of the network without overloading it.
Real-time network analysis: The substation SCADA system receives regular data in real time from sensors via remote terminal units. Sensors detect abnormal load variations, harmonics and physical parameters like transformer temperatures and oil levels.
Sensors make it possible to carry out predictive analyses for network fault prevention, optimisation and planning. Intelligent DMSs rely on sensors for real-time analysis and the modelling of networks. Sensors provide the intelligence required to operate protective devices in a coordinated manner, isolate faulty sections and restore normalcy through alternative switching plans.
Power quality monitoring: The power quality of an LV distribution system is affected by overloading, capacitor switching transients, impulse transients and harmonic distortions. The proliferation of UPS, inverters, power electronic devices and renewable energy sources induce harmonics in electrical supply. Many loads are not purely resistive and the presence of a magnetising current, the effect of rectification and inherent impedance result in harmonics or transients, which degrade power quality.
The smart meters, protection relays and fault recorders currently being deployed do not measure all the power quality parameters. On the other hand, sensors and telemetry systems monitor power quality and analyse data to make electrical networks more efficient. Sensor technology solves quality problems through the timely identification of specific sources of harmonics. Sensors measure and record the harmonic and inter-
harmonic frequencies present in the main supply. The data is then transmitted through the communications network to a centralised database.
The low cost of sensors and the convenience of wireless communication facilitate the monitoring of power quality at multiple network locations. Sensors also reduce costs by eliminating expensive diagnostic instrumentation like power quality analysers.
Peak load management: Sensors are transforming the operations of LV networks, combining information and communication technology to build intelligence. Modern applications use sensors to effectively utilise energy, and enable automation and peak load management. Sensors help interconnecting consumer devices on home area networks to communicate with utility networks to facilitate residential energy management (REM). This enables REM systems to use utility-driven price signals (time-of-use pricing) to regulate energy consumption during peak hours, thereby reducing peak load, generation expenses and greenhouse gas (GHG) emissions.
Automated demand response (ADR): ADR refers to a smart grid device or application that interacts with customers to influence their electricity consumption during select time periods. It notifies customers to lower their consumption during peak periods and shift demand to off-peak periods. It also creates a balance between electricity generation and demand, and helps to achieve load optimisation and grid stability. Sensors and advanced control systems on the LV network interact with load control systems to manage peak loads. The inherent benefits of automation enable reliable, faster and cheaper responses to load demand signals.
ADR requires both the grid and demand-side entities to install infrastructure to support the exchange of signals. The grid entity has to install sensors that are capable of communicating demand response (DR) signals to the customer’s automation equipment while the customer must install equipment that is capable of receiving these signals. The DR signals are relayed to control systems where response strategies have been programmed for appropriate load control. The smart network receives the feedback of the DR signal on the facility’s consumption through a smart meter. ADR provides a way for distribution operators to avail of more demand-side resources as a cheaper option for grid balancing.
Deploying sensor technologies in LV distribution networks has proved to be beneficial. Assessment studies measuring their impact on LV networks reveal their potential to improve operational efficiencies; manage faults in a proactive manner; improve power quality and network reliability; and control technical losses. The other advantages of such technologies include the reduction of GHG emissions, the achievement of carbon reduction goals, and the maintenance of the health of LV networks in a sustainable manner. Sensor technologies thus contribute to energy efficiency, load management and optimised network operations.
Based on a presentation by Jayant Sinha, Lead Consultant (Smart Networks), Enzen Global Limited, UK, at the India Smart Grid Week 2015