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Energy Loss – What is, impacts, approach and methodology

Energy Loss

When energy is converted from one form to another, or transferred from one device to another, there is a loss of energy defined as Technical Loss. This implies that some of the incoming energy is transformed into a highly perturbed form of energy, such as typically heat. Converting all input energy into the same quantity of output energy is nearly impossible unless you intentionally want to convert energy into heat (such as in a heater). In practical terms, the electrical energy that is transmitted by power lines is greater than the energy that comes out at the other end. Energy losses are what prevent transmission and distribution processes from being 100% effective.

There’s another category of energy loss that is defined as Commercial Loss. Any illegal use of electricity, which is not properly measured, billed or revenued, is considered a commercial loss. Commercial losses are caused by non-technical or commercial factors, such as theft, or defective meters or errors in meter reading or incorrect energy supply estimation.

Energy losses have high impacts on utilities such as:

  • Lack of profits;
  • Financial implications on all users of the distribution network;
  • Shortage of funds for investment in the power system capacity and improvement;
  • Necessity to expand generating capacity in order to cope with power losses;
  • Corruption increases and becomes entrenched as favors can be ‘‘bought’’ from power sector employees in the form of inaccurate billing and allowing illegal connections.

Furthermore, losses are important as there is an environmental and economic cost associated with them. Whilst technical losses are directly related to carbon emissions and have an impact on generation capacity, all losses have to be paid for by users of the network.

Commercial Losses


To identify and reduce technical losses it is necessary for the utility to focus on some techniques that, with the advent and spread of smart grids, have become essential such as predictive maintenance, energy balancing and demand management. To do this, a gradual transformation program of business processes is required, including training of technical and non-technical personnel on modern technologies and methodologies.

Identifying the causes of network losses and identifying the best way to minimize losses can be difficult, but recent developments in smart meter technology and machine learning can bring an important contribution. Greater accuracy of the data generated by smart grid technologies can be used to better understand losses, the causes of the loss and the evolution of losses over time. Once a complete loss map is established, it is much easier to establish a cost-effective method to minimize them.

Some of the methods to deal with technical losses are:

Replace the old cables. In high-load network regions, installing alternative cables with higher power ratings will drastically reduce losses. When replacing power cables, careful load analysis is required to predict the likely load on the cable and determine the most effective ones.

Correct sizing of transformers. Transformers work most efficiently when they have 80-100 percent full capacity. Onload transformers are unreliable due to major losses. If some transformers are always under load, it may be possible to strategically shut down those transformers or add smaller transformers that are better for loading. If the transformers are always overloaded, it may be safer and more effective to add larger transformers or rebalance the load. Again, deep analysis is needed to decide when it will make financial sense to upgrade, downsize or shut down a transformer.

Demand management. Customer demand can be minimized by providing incentives to reduce energy consumption during peak hours and to install more powerful equipment. Since loss is a non-linear characteristic of current flow, even small reductions in peak power consumption can have a major impact on the total loss.


Detection of NTLs is difficult due to the wide variety of potential causes of NTL, such as multiple dishonest techniques used by customers.
The most efficient way to minimize NTL to date is to use advanced digital electronic meters (smart meters) that make it more difficult and easier to detect fraudulent activity. From an electrical engineering perspective, one approach to detecting losses is to measure the energy balance that needs topological information from the grid. This is a challenge for the following reasons:

  1. the grid topology is subjected to continuous adjustments to meet the growing demand for electricity
  2. the infrastructure can fail and lead to incorrect calculations of the energy balance
  3. requires connected transformers, power supplies and meters to be read simultaneously

In order to detect NTLs, customer inspections can be carried out based on predictions about the possibility of an NTL. The inspection results are then used in machine learning algorithms to improve predictions. However, it is expensive to carry out inspections, as it requires the physical presence of technicians. It is therefore necessary to make accurate predictions to minimize the number of false positives.
Finally, it is important to assess the business processes related to metering and billing (meter 2 cache chain) to identify the main causes of losses in invoicing and consequently in revenues.


In light of the above, it is clear that the identification of losses and their reduction cannot be managed without an articulated plan that includes an initial assessment, the definition of a methodology, the identification of the necessary policies and procedures, the involvement of the utility personnel at all level, the definition of roles and responsibilities inside the different business units of the utility, the implementation of procedures and periodic audit, maintenance and improvement.

Thanks to numerous experiences in the field of different territorial realities, our experts are able to manage the entire process. Contact us for further information and insights.

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