Progress in the utility space brings new challenges and opportunities for innovation.

Historically distribution networks were designed to accommodate power flow from the grid supply points through to the electricity consumer via the medium voltage and low voltage networks, but the growth of distributed energy resources has changed this picture dramatically presenting utilities with a number of challenges in terms of grid management.

Traditional models of network distribution were predictable, and their design based on information from metering points, Maximum Demand Indicator (MDI) readings and high voltage load data to meet the needs of normal operation, fault conditions and abnormal operations. For decades, the daily load curves have underpinned investment and operation decisions and there has been a high degree of predictability of demand and generation with the traditional approach to network planning.

However, in the last few years there has been significant growth in large-scale renewable energy sources (RES), distributed energy resources (DER) and low carbon technologies (LCT) to address generation shortfalls and increase access to electricity. This has resulted in an increase in active networks, which are characterised by bi-directional power flow, variable voltage profiles and less predictable loads and fault current levels.

Active networks have different dynamics from traditional passive networks presenting management challenges to the operator that require different information, planning and management processes to ensure that the quality of supply is maintained.

With progress come new challenges

Active networks bring a whole raft of issues for utilities and network operators. Foremost amongst these is managing the ‘last mile’ of the distribution network. Previously low voltage networks have been virtually invisible in terms of system monitoring. As a result, utilities were reliant on customers reporting faults in order to understand where issues were occurring and with little or no visibility of ‘stress points’ at this level of the network.

Historically the focus for management of low voltage networks has been maintaining and improving quality of supply to customers and ensuring the operational efficiency of the networks. This was achieved through power flow monitoring and fault passage measurement on the MV network.

However, with much of the DER, such as embedded generation and electric vehicles (EV), being added to the network at low voltage level, utilities need more data to improve the visibility of this level of the network to help increase flexibility through access to daily energy profiles.

Additionally, the introduction of large amounts of small-scale embedded generation at LV level will also affect the fault levels, causing them to rise, but the biggest effect will be on voltage profiles. Given that the rising peak demand may need to be met without major reinforcement, it will be important to prevent overload of the network through integration of DER and other forms of LCT and utilities will need to consider temporarily or permanently increasing the ‘electrical headroom’ on the network.

Opportunity for innovation

As these challenges develop, so too does the market evolve. As a result, more low voltage monitoring systems are becoming available to utilities, such as Lucy Electric’s award-winning GridKey system. This world-leading system measures, communicates and stores real-time data and, through a suite of analysis tools, translates the data into actionable information.

The system can be safely retrofitted to low voltage feeders including LV power flow monitoring, measurement at the LV side of the transformer (i.e. current, voltage, active and reactive power, voltage, harmonics, flicker, sags, and swells, etc.), LV fault passage indication and LV fault location. The system offers class 1 accuracy over 4-720Amp range with minimal crossfeed, plus communications, alarms and reports functionality.

Taking voltage inputs from the busbar, the metrology and communications unit (MCU) has a reporting period, which is adjustable from one minute to 24 hours and can be altered remotely. The metrology units measure the current and voltage inputs and carry out a series of calculations that are then communicated to a central database for analysis. The unit has programmable alarms to alert the operator to maximum and minimum parameters reached. In addition, the data can be retrieved from the unit over GPS.

The current is measured using a Rogowski style current sensor, specifically designed for low voltage monitoring, while different types of sensors can be used and mixed, depending on the system’s monitoring requirements.

The data that the system collects is transmitted to its data centre, capable of storing up to 60 million data points, where it can be analysed and presented back in highly visible dashboards, which give operators an ‘at a glance’ situational analysis of the LV network. Analysis tools provide daily load profiles and voltage level data to help utilities plan for ‘stress points’ in the network and maintain statutory voltage levels.

Changing environment demands attention

Looking ahead, distribution networks will have to change in order to meet new demands as growth in small-scale and intermittent generation continues and to accommodate the resultant bi-directional power flows. This is especially true at low voltage level where new analytics will be required to provide decisionmakers with actionable information rather than pure data.

This information will need to be predictive and will require a clear definition and new tools to share the information to provide a wider situational awareness of the LV network – essential for utilities going forward to ensure they meet statutory voltage requirements.

Furthermore, the ability to be able to predict where faults are likely to happen, detecting when they do happen and providing information that will allow the fault to be fixed quicker will ultimately help utilities to plan for asset maximisation; improve quality of service to the electrical consumer; diagnose and solve problems more quickly; and reduce capital and operational costs.