By the year 2040, annual global electricity consumption will be 70% higher than in 2015, according to International Energy Agency (IEA) estimates . This increase has left electric utilities around the globe seeking answers to some very difficult power questions. Revenue collection and the reduction of non-technical losses are two of the most important issues that utilities and local municipalities are currently facing in this ever-changing landscape.
Non-technical losses are commercial losses which consist of delivered and consumed energy which cannot be invoiced to an end user. This category of losses can be split into fraudulent losses (theft, illegal connections, meter tampering, faulty meters) and non-compliant material, such as material used in transformers, or non-metered public lightning and hidden losses such as the in-house consumption of equipment in the distribution network, for example where the power is needed to cool transformers and run control systems.
Local municipalities must have the intention to keep the losses of electricity below a certain percentage of the total electricity purchased from the utility providing power. Reducing the technical and non-technical losses will ensure that the cost of electricity to the supplier will be reduced, as less electricity will be used from the utility. The cost of the electricity to the customer will therefore also be less, as they will not have to pay for the losses in the electricity supply network. Both these reductions will have a positive influence on the cost of electricity.
The efficiency of electrical distribution is rarely planned or managed by utilities or municipalities. The unfortunate result is that substantial amounts of electricity are wasted. Annual electricity transmission and distribution losses average 5% in the European Union[2, 3]. That breaks into 24% for transmission and 76% for distribution losses, which represents about R80-billion in energy wasted every year in distribution in today’s terms. This number includes losses in the medium and low voltage lines and in primary and secondary substations.
Technical losses on MV networks represent about 3% of the distributed energy. Joules losses represent 70% of these losses, but this is dependent upon the load rating of the network. More losses occur in the LV network . The LV ends of distribution networks are often heavily unbalanced between transformers (transformer to transformer), between LV feeders within a transformer, and between the three phases of one given transformer. These imbalances can lead to incorrect billing of sections of the users connected to that section of the network.
Incorrect and inaccurate municipal billing system poses a challenge in the local municipality’s systems throughout the area where it supplies power to customers. Various communities are dissatisfied with the incorrect and inaccurate local municipality bills that are being issued. Consequently, public confidence in terms of the billing system dwindles, communities are unwilling to pay for the bills issued, the debt accumulates and the local municipality cannot recover that debt.
Locating the sources of losses within the network is one of the first challenges. One solution for monitoring LV networks is to use smart energy meters as additional sensors to supply data regarding the energy performance of the network. In addition to loss detection, the above smart metering approach also provides faster detection and location of outages on LV networks, which leads to an improved reliability of supply.
The monitoring of MV equipment in older substations is costly, as it requires complex, intrusive methods. Thus, the ability to acquire accurate, ‘real time’ voltage measurements requires the deployment of new solutions and sensors to minimise long-term global costs.
Local municipalities are using the following measures internally to minimise the impact of non-technical losses on their revenue collection :
Smart grids are electricity networks that can intelligently integrate the actions of all users connected to it (generators, consumers, and those that do both) to deliver sustainable, economic and secure electricity supplies efficiently.
Smarter electricity grids are vital to success of reducing non-technical losses and increasing revenue collection, because they support tomorrow’s electricity-dependent world. While centralised power generation will remain critical to grid stability for decades to come, distributed energy resources (DERs), such as residential rooftop and community-scale solar arrays and storage, will become important for energy suppliers and supporters of system stability. The digitisation of distribution systems will enable the greater connectivity required for a more flexible and efficient control and transfer of electricity between:
Several new solutions can be deployed to address the challenges of monitoring MV and LV systems within a smart grid solution by automating the conventional methods, in conjunction with newer available technologies and methods:
Systems built to estimate losses, such as advanced distribution management systems (ADMS), need a real-time network topology, network measurements, load profiles at MV/LV substations, and customer consumption information to determine the optimal location of normal open points. In this environment, when the system operator plans to open or close a switch-disconnector, the ADMS simulates the impact on reliability of supply, losses and voltage management.
Algorithms calculate optimum configurations on an hourly, monthly, seasonal or yearly basis according to provided load curves, weather forecasts, real-time data coming from sensors, smart meters and a number of switch operations. Fig. 1 shows an example of an ADMS system which could be used.
Deployment of such systems can help minimise losses, minimise load unbalance in HV/MV substation transformers and feeders, unload overloaded segments of a network, improve voltage quality and achieve an optimal voltage profile. However, the system can also be constrained by an infrastructure that limits the feasibility of switching operations and with infrastructure voltage and loading limits.
Utilities operating electrical distribution networks are now able to reduce losses in their networks, thanks to smart strategies, enhancing active and passive energy efficiency. Local distribution networks are becoming more difficult to manage. This is because many distribution networks are poorly or partially instrumented, especially downstream in the areas of secondary substations. Furthermore, old transformers in many of those networks are inefficient.
Therefore, more accurate and highly networked (connected) sensors, actuators, and advanced distribution management systems, as well as more efficient distribution transformers, will be required.
The daily load, voltage, power factor and temperature profiles of the substation and feeders are examples of data that can be gathered by the monitoring system. A chronological overview of events can be determined, such as the voltage duration curve, load duration curve per feeder, vector diagram for the diagnosis of unbalances per feeder and other values. These data points can then be formatted into customisable dashboards.
Using analytic software, together with connected equipment installed in connected equipment, can help achieve real-time and historic data required to improve the accuracy of revenue collection, thus improving confidence with the billing system. Non-technical losses can be minimised by using the self-healing technology available within certain smart grid technologies.
The self-healing grid (SHG) technology helps automate power restoration, reducing outage duration to a minimum. Unlike a conventional solution, using a centralised control approach, the SHG is fully decentralised. In the event of a power fault, substations communicate with each other to execute the best possible instruction for rapid fault isolation and restoration of power supply. The average restoration time with SHG is reduced to under one minute, while the conventional approach may take hours. By reducing time on affected sections within the network, it decreases the losses on the network, increasing availability and thus the revenue collection by local municipalities.
Calculations show that losses can be further reduced by reconfiguring the network on a weekly or hourly basis using the self-healing technology. However, in the case of the hourly reconfiguration, this is not realistic in terms of number of operations. Switch-disconnectors equipment is designed to respond to current needs, such as 1000 operations per lifetime of the device. Hourly reconfiguration would require 200 000 operations during the lifetime of the device.
Distributed energy resources management systems (DERMS) offer utilities and municipalities the data, insights and control capabilities needed to operate diverse distribution grids efficiently. DERMS combine sensors, controls, hardware and software to drive the intelligence needed to harmonise distribution and transmission systems and to optimise DER input and centralised generation. DERMS extends beyond managing grid operations through the support of billing systems, especially where net-metering tariffs are in place and, by facilitating the implementation of retail-level demand response programs connected to customers’ smart thermostats and other Internet of Things (IoT)-connected devices, DERMS can also support blockchain-based community energy markets, enabling customers who participate in transactive energy models.
IDC forecasts 30% of utilities will have invested in such management systems such as DERMS by 2019, with many more considering or investigating the feasibility thereof. Thus, the transitioning to Smart MV/LV Substations, smart/connected equipment and networks, is the cornerstone of a Smart Grid Solution, and major contributor in overcoming the risk that is created from revenue collection. due to the non-technical losses.
 International Energy Agency: “World Energy Outlook,” November 2015.
 Ognjen Radovic and Michael Westermann: Workshop on Power Losses European experiences in the treatment of losses/Summary of a survey among NRAs, CEER October 2016.
 Eurelectric: Power statistics 2013.
 Dr Georgios Papaefthymiou, Christina Beestermöller, and Ann Gardiner: “Ecofys Incentives to improve energy efficiency in EU Grids”, 15 April 2013.
 Drakenstein Municipality Electrical Losses Policy, 2017.
 IDC: “FutureScape: Worldwide Utilities 2017 Predictions”, November 2016.
Contact Prisca Mashanda, Schneider Electric, Tel 011 046-1900, email@example.com
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