Adaptive and Robust Cross-Voltage-Level Power Flow Control of Active Distribution Networks

The large-scale integration of Distributed Energy Resources (DERs) into the electric power system offers new opportunities to ensure stability. For example, Active Distribution Networks (ADNs) can be used in (sub-)transmission systems in the emergency state, as far as high robustness and performance of the ADN control are guaranteed. This paper presents an adaptive control system for ADN's cross-voltage-level power flow control. For this purpose, the gain scheduling approach is used. Furthermore, this work introduces a method for control parameter tuning. In order to validate the control parameter tuning, the adaptive control system is analyzed regarding robustness and performance using an exemplary medium voltage grid. In addition, the influence of uncertainties is examined. Finally, the operation of the adaptive control system is demonstrated by performing time-domain simulations.Comment: In proceedings of the 11th Bulk Power Systems Dynamics and Control Symposium (IREP 2022), July 25-30, 2022, Banff, Canad

Probabilistic load flow for uncertainty based grid operation

Traditional algorithms used in grid operation and planning only evaluate one deterministic state. Uncertainties introduced by the increasing utilization of renewable energy sources have to be dealt with when determining the operational state of a grid. From this perspective the probability of certain operational states and of possible bottlenecks is important information to support the grid operator or planner in their daily work. From this special need the field of application for Probabilistic Load Flow methods evolved. Uncertain influences like power plant outages, deviations from the forecasted injected wind power and load have to be considered by their corresponding probability. With the help of probability density functions an integrated consideration of the partly stochastic behaviour of power plants und loads is possible

Modeling and Contribution of Flexible Heating Systems for Transmission Grid Congestion Management

The large-scale integration of flexible heating systems in the European electricity market leads to a substantial increase of transportation requirements and consecutively grid congestions in the continental transmission grid. Novel model formulations for the grid-aware operation of both individual small-scale heat pumps and large-scale power-to-heat (PtH) units located in district heating networks are presented. The functionality of the models and the contribution of flexible heating systems for transmission grid congestion management is evaluated by running simulations for the target year 2035 for the German transmission grid. The findings show a decrease in annual conventional redispatch volumes and renewable energy sources (RES) curtailment resulting in cost savings of approximately 6 % through the integration of flexible heating systems in the grid congestion management scheme. The analysis suggests that especially large-scale PtH units in combination with thermal energy storages can contribute significantly to the alleviation of grid congestion and foster RES integration

Bottom-up self-organization of unpredictable demand and supply under decentralized power management

In the DEZENT1 project we had established a distributed base model for negotiating electric power from widely distributed (renewable) power sources on multiple levels in succession. Negotiation strategies would be intelligently adjusted by the agents, through (distributed) Reinforcement Learning procedures. The distribution of the negotiated power quantities (under distributed control as well) occurs such that the grid stability is guaranteed, under 0.5 sec. The major objective in this paper was to deal, on the same level of granularity, with short-term power balance fluctuation, in terms of a peak demand and supply management exhibiting highly dynamic, self-organizing, autonomous yet coordinated algorithms under fine-grained distributed control. Our extensive experiments show very clearly that these short-term fluctuations could be leveled down by 70 - 75 %. In this way we have tackled, for the quickly increasing renewable power systems, a crucial problem of its stability, in a novel way that scales very easily due to the completely decentralized control

On-line stable state determination in decentralized power grid management

Both the coordination of international energy transfer and the integration of a rapidly growing number of decentralized energy resources (DER) throughout most countries causes novel problems for avoiding voltage band violations and line overloads. Traditional approaches are typically based on global off-line scheduling under globally available information and rely on iterative procedures that can guarantee neither convergence nor execution time. In this paper we focus on stability problems in power grids based on widely dispersed (renewable) energy sources. In this paper we will introduce an extension of the DEZENT algorithm, a multi-agent based coordination system for DER, that allows for the feasibility verification in constant and predetermined time. We give a numerical example showing the legitimacy of our approach and mention ongoing and future work regarding the implementation and utilization

Towards autonomous distributed coordination of fast power flow controllers

The liberalization of the power market, an overall increase in power demand and the integration of high capacity unpredictable renewable resources (e.g. wind power) pose a challenge to transmission network operators that have to guarantee a stable and efficient operating of the grid. A way to improve the stability and efficiency of the existing network – aside from expensive reconstruction – is the integration of fast power flow controllers in order to dynamically redirect power flows away from critically loaded resources that may be threatened by an overload. In this paper we outline our current work in progress on developing a multi-agent model that allows for an autonomous distributed coordination of fast power flow controllers without the need for global information