IEET: OUREL (DFG)

Research Project

OUREL

Optimal Utilization of Renewable Energies in Low Voltage (LV) Distribution Grids

Abstract

The decentralization of electricity generation on one hand and the electrification of e.g. the heat and mobility sectors on the other hand are important cornerstones of the energy transition. Their realization implies that a multitude of Decentral Energy Resources (DER), i.e. generation, consumption and storage units, have to be integrated into existing low-voltage distribution grids. To optimally utilize the potential of renewable energies, new grid operation concepts are required that include all the flexible DERs. The high degrees of decentralization and the high volatility of electricity generation from renewables pose substantial challenges for such concepts. Within the OUREL project, we develop a distributed operation management method for low-voltage grids with a high share of controllable DERs. It aims at optimizing the injected and consumed powers with regard to a utility measure that considers all participating units. This concept has been thoroughly investigated in the communication network domain and is transformed to electric power grids here. In doing so, we especially focus on a high update rate and the resulting tradeoff between enabling model reduction on one hand, and increasing communication demand on the other hand. The ieet scope covers modelling of the electric low-voltage grid including the connected passive loads and DERs, with a focus on photovoltaic power plants, electric vehicles and heat pumps. Furthermore, we develop the algorithms to estimate the grid state based on data from different sources. With regard to the optimization algorithms, we contribute our expertise to develop methods on how to consider grid constraints like voltage and current limits.

Tools

In the OUREL project, we use Matlab and Simulink to model the low-voltage grids and to develop and simulate the grid state estimation and optimization algorithms. To consider realistic communication network characteristics, we utilize co-simulations using a communication network emulator that was developed at the TUHH (FlowEmu) . We complement the software simulations with controller-hardware-in-the-loop (CHiL) simulations, where the developed algorithms are implemented on actual controller hardware and tested under real-time conditions using the OPAL real-time digital simulator of the PHiLsLab.