Power transformers’ reliability is of the highest importance for distribution networks. A possible failure of them can interrupt the supply to consumers, which will cause inconvenience to them and loss of revenue for electricity companies. Additionally, depending on the type of damage, the recovery time can vary and intensify the problems of consumers. This paper estimates the maintenance required for distribution transformers using Artificial Intelligence (AI). This way the condition of the equipment that is currently in use is evaluated and the time that maintenance should be performed is known. Because actions are only carried out when necessary, this strategy promises cost reductions over routine or time-based preventative maintenance. The suggested methodology uses a classification predictive model to identify with high accuracy the number of transformers that are vulnerable to failure. This was confirmed by training, testing, and validating it with actual data in Colombia’s Cauca Department. It is clear from this experimental method that Machine Learning (ML) methods for early detection of technical issues can help distribution system operators increase the number of selected transformers for predictive maintenance. Additionally, these methods can also be beneficial for customers’ satisfaction with the performance of distribution transformers, which would enhance the highly reliable performance of such transformers. According to the prediction for 2021, 852 transformers will malfunction, 820 of which will be in rural Cauca, which is consistent with previous failure statistics. The 10 kVA transformers will be the most vulnerable, followed by the 5 kVA and 15 kVA transformers.

A power system can be defined as flexible if it can within economic and technological boundaries respond quickly and adequately to variations in supply and demand. The ongoing penetration of variable and intermittent renewable energy sources (RES) like wind and solar imposes additional and more critical requirement on power system flexibility. In this paper we propose a method to quantify these requirements based on the comparison of seven demand side parameters describing the statistical properties of the net load and the residual load of the referred power system. Each one of these parameters reflects a separate requirement on the available conventional generation in hourly and daily time scales—ramp up and ramp-down capabilities, technological minimum of generation, daily variation of generation. The proposed approach can be used to predict the requirements for generation flexibility according to the expected scenario of RES penetration in the future development of energy power system. It has been applied and integrated from the Bulgarian Transmission System Operator (TSO) which name is the Bulgarian Electricity System Operator (ESO).

The paper’s main objective is to demonstrate the trading and flexibility of services amongst TSOs, DSOs, and Prosumers in a transparent, secure, and cost-effective manner using Blockchain-based TSO-DSO flexibility marketplace (EFLEX). The aim is to look for ways to help DSOs/TSOs be more flexible and more directly engaged in managing energy flows on the network. EFLEX will streamline the needs of both TSO and DSO on the same platform. Based on the paper’s proposed services, the pilot service demonstration will be carried out in Bulgaria and Romania, and the main focus will be on congestion management, TSO-DSO Coordination, and Marketplace. The proposed objective is achieved by using Blockchain-based smart contracts and distributed ledger technology.

The legislation at the EU level is decisive in developing the local flexibility market. At the current stage, there are far-from-sufficient regulations on the local flexibility market, which can be perceived as a major barrier. The scope of this article is to explore the operational principles of the European local flexibility market and to assess the regulation of emerging flexible markets in order to help a new policy framework that facilitates the integration of flexible assets in the distribution grid. Although the evaluation primarily focuses on current regulations, numerous modifications are still being made to them, such as those brought about by the implementation of the Clean Energy Package. The possibility of the research material quickly becoming outdated makes this difficult. To reduce this risk, we also examine current debates over potential restrictions; nonetheless, the core of the report mainly applies to laws and policies that were in force prior to the second half of 2022. An examination and analysis of potential flexibility providers’ motives to offer flexibility on a local flexibility market were conducted concurrently with the regulatory assessment. The inquiry was initiated by identifying resources that may be used to improve the flexibility of the electrical system but are underutilized. Underutilized resources refer to assets that are already part of society, such as efficient energy use, support for behavioral changes, heating systems (such as district heating, heat pumps, and thermal inertia), as well as underutilized energy storage capacities that are underutilized in terms of supplying flexibility to the electric grid. Resources were found via conducting interviews and studying scientific literature. The rules and guidelines for the emerging local flexibility markets are examined in this study. The regulations need to be continually improved because they are far from complete.

The transition in the energy sector is essential for reducing carbon emissions and building a sustainable future. In this process, wind and solar energy play a leading role, offering environmentally friendly solutions. Their effective integration into the power system requires addressing various technical, operational, and regulatory challenges. This study examines long-term strategies for power system planning, which are crucial for maintaining the security of electricity supply. The analysis presents energy transition scenarios applied in Europe, clarifying their significance and timeline for implementation. This review provides an overview of existing studies on the technical, regulatory, and climatic aspects of renewable energy integration, highlighting key findings to support stakeholders in risk assessment and decision-making within the current decarbonization framework.

The journal retracts the article “Policy Framework Enabling Flexibility Markets—Bulgarian Case” by Mladenov et al