DIGITAL SOLUTION FOR FAST EVALUATION OF THE POWER FACTOR IN POWER NETWORKS

Power quality evaluation involves measurements and determinations of some power quality indicators. One of these indicators is represented by the power factor. The importance of the power factor as an indicator of power quality, both theoretical and practical, implies its determination or direct measurement as a necessity, especially in industrial environments where the optimization of energy costs is a primary target. Considering these, the determination of this power quality indicator implies multiple or sophisticated measurement tools. As a result, the present paper aims to present a solution for an easier evaluation of the power factor. The proposed solution can be integrated in numerical control systems for reactive power monitoring or in supervision and control systems in order to extend the applicability for the automatic power factor improvement. The proposed solution is characterized by simplicity and a low cost of implementation, representing an effective learning tool in the professional training in the electricity field. The configuration of the measurement circuit was designed to allow the measurement of a wide range of the power factor, starting from the case of inductive consumers to the case of capacitive consumers, noting that in the case of strongly deformed regimes the results shows significant deviations from the expected ones fact that is extensively exposed and motivated in the paper

Challenges for the Large-Scale Integration of Distributed Renewable Energy Resources in the Next Generation Virtual Power Plants

The proper power distribution systems operation is conditioned by its response to the consumers’ energy demand. This is achieved by using predictable power sources supplemented by ancillary services. With the penetration of different alternative power sources especially the renewable ones, the grid increasingly becomes an active distribution network. In this context, the stability provided by ancillary services becomes increasingly important. However, providers of ancillary services are interested to benefit from the shift towards renewable energy. This leads to a complex scenario regarding the management of such service providers, specifically virtual power plants. In this regard, the aim of the paper was to investigate the strategies for improving the performance of virtual power plants by increasing the number of distributed renewable energy resources

Energy Contour Forecasting Optimization with Smart Metering in Distribution Power Networks

Smart metering systems development and implementation in power distribution networks can be seen as an important factor that led to a major technological upgrade and one of the first steps in the transition to smart grids. Besides their main function of power consumption metering, as is demonstrated in this work, the extended implementation of smart metering can be used to support many other important functions in the electricity distribution grid. The present paper proposes a new solution that uses a frequency feature-based method of data time-series provided by the smart metering system to estimate the energy contour at distribution level with the aim of improving the quality of the electricity supply service, of reducing the operational costs and improving the quality of electricity measurement and billing services. The main benefit of this approach is determining future energy demand for optimal energy flow in the utility grid, with the main aims of the best long term energy production and acquisition planning, which lead to lowering energy acquisition costs, optimal capacity planning and real-time adaptation to the unpredicted internal or external electricity distribution branch grid demand changes. Additionally, a contribution to better energy production planning, which is a must for future power networks that benefit from an important renewable energy contribution, is intended. The proposed methodology is validated through a case study based on data supplied by a real power grid from a medium sized populated European region that has both economic usage of electricity—industrial or commercial—and household consumption. The analysis performed in the proposed case study reveals the possibility of accurate energy contour forecasting with an acceptable maximum error. Commonly, an error of 1% was obtained and in the case of the exceptional events considered, a maximum 15% error resulted

Energy Contour Forecasting Optimization with Smart Metering in Distribution Power Networks

Smart metering systems development and implementation in power distribution networks can be seen as an important factor that led to a major technological upgrade and one of the first steps in the transition to smart grids. Besides their main function of power consumption metering, as is demonstrated in this work, the extended implementation of smart metering can be used to support many other important functions in the electricity distribution grid. The present paper proposes a new solution that uses a frequency feature-based method of data time-series provided by the smart metering system to estimate the energy contour at distribution level with the aim of improving the quality of the electricity supply service, of reducing the operational costs and improving the quality of electricity measurement and billing services. The main benefit of this approach is determining future energy demand for optimal energy flow in the utility grid, with the main aims of the best long term energy production and acquisition planning, which lead to lowering energy acquisition costs, optimal capacity planning and real-time adaptation to the unpredicted internal or external electricity distribution branch grid demand changes. Additionally, a contribution to better energy production planning, which is a must for future power networks that benefit from an important renewable energy contribution, is intended. The proposed methodology is validated through a case study based on data supplied by a real power grid from a medium sized populated European region that has both economic usage of electricity—industrial or commercial—and household consumption. The analysis performed in the proposed case study reveals the possibility of accurate energy contour forecasting with an acceptable maximum error. Commonly, an error of 1% was obtained and in the case of the exceptional events considered, a maximum 15% error resulted

Telocytes’ Role in Modulating Gut Motility Function and Development: Medical Hypotheses and Literature Review

This review article explores the telocytes’ roles in inflammatory bowel diseases (IBD), presenting the mechanisms and hypotheses related to epithelial regeneration, progressive fibrosis, and dysmotility as a consequence of TCs’ reduced or absent number. Based on the presented mechanisms and hypotheses, we aim to provide a functional model to illustrate TCs’ possible roles in the normal and pathological functioning of the digestive tract. TCs are influenced by the compression of nearby blood vessels and the degree of fibrosis of the surrounding tissues and mediate these processes in response. The changes in intestinal tube vascularization induced by the movement of the food bowl, and the consequent pH changes that show an anisotropy in the thickness of the intestinal tube wall, have led to the identification of a pattern of intestinal tube development based on telocytes’ ability to communicate and modulate surrounding cell functions. In the construction of the theoretical model, given the predictable occurrence of colic in the infant, the two-layer arrangement of the nerve plexuses associated with the intestinal tube was considered to be incompletely adapted to the motility required with a diversified diet. There is resulting evidence of possible therapeutic targets for diseases associated with changes in local nerve tissue development