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

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

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