## 1 Introduction  
The transformers of the electrical distribution networks, used in industrial, commercial and residential activities, have significant energy consumptions and give rise to high carbon dioxide emissions into the atmosphere. Consequently, these machines affect the energy and environmental sustainability of electrical systems [1; 2; 3; 4]. The energy consumption of transformers is due to their copper and core losses, as is well-known [5; 6; 7; 8; 9; 10]. A report carried out in 2008 for the project \"Strategies for development and diffusion of Energy Efficient Distribution Transformers (SEEDT)\" [11] estimated the percentage of energy losses caused by distribution transformers is a third of the total losses in the electrical networks. That same report counted more than 4.5 million transformers in the distribution networks of the EU-27, with energy consumption--caused by losses--of 33.4 TWh/year, of which 24.1 TWh/year corresponded to core losses, and 9.3 TWh/year was due to copper losses. The saving potential estimated by the report reached 12 TWh/year and a reduction in CO\({}_{2}\) emissions of up to 4 million tons/year of CO\({}_{2}\) in the year 2025 [12] and was the most favorable scenario for a rapid replacement of existing transformers for more efficient ones, which had only 49% losses in the core than current transformers. Following the proposals presented by the SEEDT project, organizations [13; 14] and companies in the electricity sector [15; 16; 17; 18] have promoted changes in regulations [19; 20; 21; 22; 23; 24; 25; 26; 27; 28; 29] to favor the manufacture and use of efficient transformers [30; 31]. Aware of the importance of reducing the transformers' own consumptions, as a necessary step to promote the circular economy and guarantee energy and environmental sustainability in the electricity sector, this paper describes a procedure to improve the sustainability of transformation houses in low-voltage distribution networks. This procedure is based on the reduction of transformer copper and core losses. Actions to reduce copper losses were analyzed in a previous article [32]. These consist of minimizing the values of reactive, unbalanced and distortion currents, using well-known techniques, such as reactive power compensation and the use of harmonic filters. As a novelty, the minimization of unbalanced current is achieved using the active and reactive components of the unbalanced power vector (\(\overset{\rightarrow}{S}_{\mathit{uip}}\), \(\overset{\rightarrow}{S}_{\mathit{uiq}}\)) [33]. These quantities provide sufficient information to network operators to obtain a more equitable distribution, in real-time, of the loads connected to the transformers. Copper loss reduction techniques are complementary to actions to reduce core losses and can be applied to both old, inefficient, transformers and efficient transformers. The reduction of losses in the core is achieved in the procedure by replacing the old transformers with more efficient ones, of equal or lesser power. The use of efficient, lower-power transformers considerably improves the energy sustainability of transformation centers, larger than the improvement derived from the reduction of copper losses. The procedure for sustainability improvement has been applied to a transformation house of the low-voltage distribution network of an industrial estate, which has a 1600 kVA transformer, 25 years old, from the manufacturer Ormazabal. The study has focused on energy, environmental and economic aspects. For the energy study, a measurement campaign has been carried out, using the FLUKE 435 Series II network analyzer, whose loss calculator allows for the copper losses due to each component of the secondary currents to be measured separately. The environmental effects caused by copper and core losses, that is, the amount of emissions of carbon dioxide and other gases, have been determined using the emission factor from Spain (0.241 kg CO\({}_{2}\)/kWh), corresponding to the year 2019 [34], prior to which the measurement campaign was made.