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

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

Fast terminal sliding-mode finite-time tracking control with differential evolution optimization algorithm using integral chain differentiator in uncertain nonlinear systems

This paper presents a fast terminal sliding-mode tracking control for a class of uncertain nonlinear systems with unknown parameters and system states combined with time-varying disturbances. Fast terminal sliding-mode finite-time tracking systems based on differential evolution algorithms incorporate an integral chain differentiator (ICD) to feedback systems for the estimation of the unknown system states. The differential evolution optimization algorithm using ICD is also applied to a tracking controller, which provides unknown parametric estimation in the limitation of unknown system states for trajectory tracking. The ICD in the tracking systems strengthens the tracking controller robustness for the disturbances by filtering noises. As a powerful finite-time control effort, the fast terminal sliding-mode tracking control guarantees that all tracking errors rapidly converge to the origin. The effectiveness of the proposed approach is verified via simulations, and the results exhibit high-precision output tracking performance in uncertain nonlinear systems

Impact of hormone replacement therapy on the histologic subtype of breast cancer

Objective: Postmenopausal hormone replacement therapy (HRT) is associated with an increase in breast cancer risk, which correlates to the duration of HRT use. We wanted to investigate a possible association between HRT use and the risk of a histologic subtype of breast cancer. Patients and methods: From 1995 until 2004, 497 cases of primary ductal, lobular or ductulolobular breast cancer in postmenopausal women were diagnosed at the Department of Gynecology and Obstetrics, University Hospital Basel, Switzerland. The data was derived from patient's records. HRT ever use was defined as HRT use for ≥6 months. Results: Of the 99 cases of lobular cancer 72.7% were invasive lobular cancers, 21.2% were invasive ductulolobular cancers and 6.1% were lobular cancers in situ. Of the 398 cases of ductal cancer, 90.5% were invasive ductal cancers and 9.5% were ductal cancers in situ. Totally 144 women were HRT ever users, and 341 women were HRT never users. HRT status could not be defined in 12 women. HRT ever use was associated with an increased risk for lobular cancer (OR 1.67; 95% CI 1.02-2.73). Also, menopause due to bilateral oophorectomy was associated with an increased risk for lobular cancer (OR 2.42; 95% CI 1.06-5.54). Conclusions: There is evidence that HRT as well as menopause due to bilateral oophorectomy may be associated with an increased risk for lobular cancer. This association is of major clinical relevance, since lobular breast cancer is more difficult to diagnose clinically and radiologically than ductal breast cance

Stability of renewable energy based microgrid in autonomous operation

This paper develops a comprehensive small-signal model of hybrid renewable-energy-based microgrid (MG) in an attempt to perceive oscillatory stability performance and capture the potential interaction between low-frequency critical modes within the MG. Trajectories of sensitive modes due to controller gain variations were evaluated in order to determine the stability boundaries. It was noticeable that various power-sharing schemes significantly influenced the small-signal stability of MG. Moreover, modal interaction emerged due to the proximity of RES-based DG units and non-linear dynamic behaviour of the sensitive modes. The interaction may result in a more oscillatory situation which potentially leads to instability of MG. The low-frequency critical modes obtained from eigenvalues analysis were then verified with the help of nonlinear time domain simulations. The presented work contributes to enhance the design and tuning of controller gain and propose appropriate power-sharing scheme within MG

Microgrid Impact on Low Frequency Oscillation and Resonance in Power System

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