A Power Quality Parameters Setup for Power Quality Management Model as an Integrate Part of Active Demand Side Management
VSB - Technical University of Ostrava
VSB – Technical University of Ostrava, Czech Republic
Abstract— This paper presents the determination of parameters for the power quality management system using Artificial Intelligence (probably multilayer neural networks with feedback learning algorithm). This predictive model will be used as a complementary tool for controlling and maintaining electrical power quality parameters within Off-Grid systems that are powered by renewable sources. Maintaining the power parameters within the limit in the Off-Grid system is very important and complicated because the stochastic nature of supply from renewable sources, which are used as dominant electric power sources in the system. Differences in short-circuit power can significantly affect the stability of the system and it may have a negative impact on the operation of sensitive appliances. We develop tools and methods to maintain energy quality parameters in Off-Grid systems within the limits by an intelligent approach based on artificial intelligence techniques. This paper presents the results of the most important and narrowest links of the parameters of the power quality to meteorological conditions, from which it can be deduced the prediction of the parameters of the power quality. The output data will be used for the Power Quality Management (PQM) model algorithm which will be implemented into the Active Demand Side Management system (ADSM) of the Off-Grid system.
Keywords—Power Quality Management; Active Demand Side Management; Artificial Intelligence, Neural Network