Zonal and Nodal Models of Energy Market in European Union

Along with economic development and development of power systems, new, more effective models of the energy market are sought. Traditional zonal models used on the electricity market have proved to be poorly adapted to new circumstances and phenomena occurring in the macroeconomic environment. The main aim of the research was to show the direction (including the nodal model and prosumer behavior) in which the energy market should develop in order to meet the state-of-the-art technical, ecological and social challenges. Therefore, with the new challenges, a new chapter has opened up on very interesting research for the electrical industry. There are new solutions for the development and modernization of models from the point of view of management and econometrics of the energy market, adapted to new challenges related to ecology, technology, and competition. This article presents the zone model with its imperfections and suggestions for its improvement and proposes a nodal model that may in the near future become a new model for the functioning of the electricity market in Europe.

Research on Predicting Line Loss Rate in Low Voltage Distribution Network Based on Gradient Boosting Decision Tree

Line loss rate plays an essential role in evaluating the economic operation of power systems. However, in a low voltage (LV) distribution network, calculating line loss rate has become more cumbersome due to poor configuration of the measuring and detecting device, the difficulty in collecting operational data, and the excessive number of components and nodes. Most previous studies mainly focused on the approaches to calculate or predict line loss rate, but rarely involve the evaluation of the prediction results. In this paper, we propose an approach based on a gradient boosting decision tree (GBDT), to predict line loss rate. GBDT inherits the advantages of both statistical models and AI approaches, and can identify the complex and nonlinear relationship while computing the relative importance among variables. An empirical study on a data set in a city demonstrates that our proposed approach performs well in predicting line loss rate, given a large number of unlabeled examples. Experiments and analysis also confirmed the effectiveness of our proposed approach in anomaly detection and practical project management.

Voltage Support Experimental Analysis of a Low-Voltage Ride-Through Strategy Applied to Grid-Connected Distributed Inverters

In recent decades, different control strategies have been designed for the increasing integration of distributed generation systems. These systems, most of them based on renewable energies, use electronic converters to exchange power with the grid. Capabilities such as low-voltage ride-through and reactive current injection have been experimentally explored and reported in many research papers with a single inverter; however, these capabilities have not been examined in depth in a scenario with multiple inverters connected to the grid. Only few simulation works that include certain methods of reactive power control to solve overvoltage issues in low voltage grids can be found in the literature. Therefore, the overall objective of the work presented in this paper is to provide an experimental analysis of a low-voltage ride-through strategy applied to distributed power generation systems to help support the grid during voltage sags. The amount of reactive power will depend on the capability of each inverter and the amount of generated active power. The obtained experimental results demonstrate that, depending on the configuration of distributed generation, diverse inverters could have different control strategies. In the same way, the discussion of these results shows that the present object of study is of great interest for future research.