TY - CONF A1 - Rauch, Johannes A1 - Brückl, Oliver T1 - Analysis of the correlation behavior between local available information to the overall reactive power of a medium-voltage grid group T2 - Applied Research Conference - ARC 2017, 7 July 2017 München N2 - The initiated energy transition leads to extensive changes in the supply of energy. The increasing use of renewable energy causes a shift of the produced power from centralized conventional power plants to decentralized energy plants. Because of this redistribution and the related change of load-flows, new challenges and problems for distribution system operators appear. This includes the integration of new loads and plants into the existing power grid and the guarantee of a high supply security and quality. It also includes strengthened requirements for the use and provision of reactive power. The project “SyNErgie” (“Systemoptimierendes Netz- und Energiemanagement für Verteilungsnetze der Zukunft“) deals with the development of a new reactive power management, which gets embedded in grid planning and controlling processes. One focus of the project is on the integration of decentralized energy plants (DEPs) to the reactive power management. The aim is to develop a decentralized and self-sufficient reactive power control system, which only works with local available information (measures). Therefore is no necessity of a complex communication system to the grid control center. Self-controlled Q-controller in the DEPs get characteristic curves and control the reactive power sources with local measurements (e.g. current, voltage, effective power). This new reactive power control management aims for the reactive power compensation in order to increase the integration capacity of loads and plants in a grid [2]. In order to generate characteristic curves for DEPs, it is necessary to analyze the correlation behavior between the local available measurements at the DEPs and the overall-Q-behavior of the grid group at the transformer. In that regard, influencing quantities should be considered. The aim is to involve und evaluate all relevant influencing quantities in order to determine energy plants and certain operating points, in which the correlation behavior and the prediction for the overall-Q-behavior are sufficient. The next step is to develop a model that fits these correlation behaviors and generate characteristic curves. One method to generate characteristic curves for the Q-controllers is regression analysis. The developed Q-control-system with the characteristic curves will be tested, evaluated and optimized in a following field test in cooperation with distribution system operators. KW - Mittelspannungsnetz KW - Blindleistungsmanagement KW - Blindleistung KW - Integration Erneuerbare Energien KW - Potentialerschließung Y1 - 2017 UR - https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/5871 UR - https://nbn-resolving.org/urn:nbn:de:bvb:898-opus4-58712 SP - 224 EP - 230 CY - München ER -