No abstract

No abstract

The article presents the concept of voltage control in a medium-voltage network, using the classical control of a HV/MV (High Voltage/Medium Voltage) transformer and active participation of distributed generation sources. The proposed solution is based on the results of the optimization process. The objective function is considered as a single-criterion—the voltage quality indicator or value of power losses in the network, and optionally as two-criteria (voltage quality and losses combined, with appropriately selected weight factors). The analysis carried out for random selection of independent variables, using the original heuristic algorithm, indicated a very high efficiency of the proposed control process, compared to the traditional approach. A significant improvement in the voltage quality index and reduction of losses was found, which justifies the advisability of looking for new solutions in the field of voltage control in MV networks, taking into account active participation of distributed generation.

Modern power engineering is struggling with various problems that have not been observed before or have occurred very rarely. The main cause of these problems results from the increasing number of connected distributed electricity sources, mainly renewable energy sources (RESs). Therefore, energy generation is becoming more and more diverse, both in terms of technology and location. Grids that have so far worked as receiving networks change their original function and become generation networks. The directions of power flow have changed. In the case of distribution networks, this is manifested by power flows towards transformer stations and further to the network with a higher voltage level. As a result of a large number of RESs, their total share in the total generation increases. This has a significant impact on various aspects of the operation of the power system. Voltage profiles, branch loads, power flows and directions of power flows between areas change. As a result of the random nature of RES generation, there are problems with the quality of electricity, source stability issues, branch overloading, voltage exceedances and power balance. The occurrence of various types of problems requires the use of more and more advanced methods to solve them. This review paper, which is an introduction to the Special Issue Advanced Optimisation and Forecasting Methods in Power Engineering, describes and justifies the need to reach for effective and available mathematical and IT methods that are necessary to deal with the existing threats appearing in the operation of modern power systems. It indicates exemplary, current problems and advanced methods to solve them. This article is an introduction and justification for the use of advanced calculation methods and algorithms. Engineering intuition and experience are often not enough due to the size and complexity of power grid operation. Therefore, it becomes necessary to use methods based on artificial intelligence and other advanced solutions that will facilitate and support decision making in practice.

There are several threats that require the control of the conditions of switching operations in the transmission grid. They result mainly from the negative effects of the high-value current, which may appear after the breaker is closed. Problems considering closing the power circuit breakers on a large standing phase angle (SPA) are often formulated by grid operators. The literature most often discusses the problem of SPA reduction, which allows the system to be restored without the risk of damaging the turbogenerator shafts. This reduction can be achieved by various operational solutions; most often, it is the appropriate adjustment of active power generation, sometimes backed up by partial load shedding. The subject of the presented article is a slightly different approach to the SPA problem. The method of determining the maximum value of SPA for which the connection operation allows to avoid excessive transitional torques was presented. With this approach, finding the maximum value of SPA between the two considered system nodes is treated as an optimisation task. In order to solve it, the original heuristic optimisation method described in the article was applied.