Uncertain information combination for decision making in smart grid BDI agent systems

In a smart grid SCADA (supervisory control and data acquisition) system, sensor information (e.g. temperature, voltage, frequency, etc.) from heterogeneous sources can be used to reason about the true system state (e.g. faults, attacks, etc.). Before this is possible, it is necessary to combine information in a consistent way. However, information may be uncertain or incomplete while the sensors may be unreliable or conflicting. To address these issues, we apply Dempster-Shafer (DS) theory to model the information from each source as a mass function. Each mass function is then discounted to reflect the reliability of the source. Finally, relevant mass functions (after evidence propagation) are combined using a context-dependent combination rule to produce a single combined mass function used for reasoning. We model a smart grid SCADA system in the belief-desire-intention (BDI) multi-agent framework to demonstrate how our approach can be used to handle the combined uncertain sensor information. In particular, the combined mass function is transformed into a probability distribution for decision-making. Based on this result, the agent can determine which state is most plausible and insert a corresponding AgentSpeak belief atom into its belief base. These beliefs about the environment affect the selection of predefined plans, which in turn determine how the agent will behave. We also identify conditions when a combination should occur to ensure the reactiveness of the agent

Parameterizable Byzantine Broadcast in Loosely Connected Networks

We consider the problem of reliably broadcasting information in a multihop asynchronous network, despite the presence of Byzantine failures: some nodes are malicious and behave arbitrarly. We focus on non-cryptographic solutions. Most existing approaches give conditions for perfect reliable broadcast (all correct nodes deliver the good information), but require a highly connected network. A probabilistic approach was recently proposed for loosely connected networks: the Byzantine failures are randomly distributed, and the correct nodes deliver the good information with high probability. A first solution require the nodes to initially know their position on the network, which may be difficult or impossible in self-organizing or dynamic networks. A second solution relaxed this hypothesis but has much weaker Byzantine tolerance guarantees. In this paper, we propose a parameterizable broadcast protocol that does not require nodes to have any knowledge about the network. We give a deterministic technique to compute a set of nodes that always deliver authentic information, for a given set of Byzantine failures. Then, we use this technique to experimentally evaluate our protocol, and show that it significantely outperforms previous solutions with the same hypotheses. Important disclaimer: these results have NOT yet been published in an international conference or journal. This is just a technical report presenting intermediary and incomplete results. A generalized version of these results may be under submission

Comparative analysis of the seismic hazard of Central China

Seismic hazard assessment is globally recognised as a tool in identifying levels of earthquake ground shaking within an area. However, methodologies for seismic hazard calculation are wide ranging and produce variations in results and maps. As a case study seismic hazard and results from Gumbel’s method of extremes are determined for the area of greatest intraplate seismicity in China covering the provinces of Gansu, Sichuan and Yunnan. This area is termed the North-South Seismic Zone. Devastating earthquakes in this zone include the 8.4 MS 1920 Haiyuan earthquake causing over 220,000 deaths and the 1996 Lijiang earthquake. Most recently the 2008 Wenchuan earthquake caused over 69,000 deaths with more than 18,000 people missing. These results and seismic hazard maps are compared with the publicly available maps of GSHAP and the national seismic hazard map of China at the level of 10% probability of exceedance in a 50 year period. The distributions of high and low hazard areas are similar and adjacent to the major thrust and strike-slip faults dominating in this area. However, results from the Gumbel method of extremes suggest that the hazard levels within certain areas are slightly different compared to the other two models. This is primarily because the Gumbel methodology is based on determining hazard from earthquakes that have already taken place whereas the other two models determine maximum hazard levels in areas which may exhibit no previous strong hazard. Additionally the Chinese national hazard map does not indicate levels of ground shaking intensity greater than IX in detail, whereas such zones are identified using the extreme value method. This work should be used to strengthen the seismic hazard analysis of this area of China

Review of recent research towards power cable life cycle management

Power cables are integral to modern urban power transmission and distribution systems. For power cable asset managers worldwide, a major challenge is how to manage effectively the expensive and vast network of cables, many of which are approaching, or have past, their design life. This study provides an in-depth review of recent research and development in cable failure analysis, condition monitoring and diagnosis, life assessment methods, fault location, and optimisation of maintenance and replacement strategies. These topics are essential to cable life cycle management (LCM), which aims to maximise the operational value of cable assets and is now being implemented in many power utility companies. The review expands on material presented at the 2015 JiCable conference and incorporates other recent publications. The review concludes that the full potential of cable condition monitoring, condition and life assessment has not fully realised. It is proposed that a combination of physics-based life modelling and statistical approaches, giving consideration to practical condition monitoring results and insulation response to in-service stress factors and short term stresses, such as water ingress, mechanical damage and imperfections left from manufacturing and installation processes, will be key to success in improved LCM of the vast amount of cable assets around the world

Data Challenges and Data Analytics Solutions for Power Systems

L'abstract è presente nell'allegato / the abstract is in the attachmen

Analyzing the EGEE production grid workload: application to jobs submission optimization

International audienceGrids reliability remains an order of magnitude below clusters on production infrastructures. This work is aims at improving grid application performances by improving the job submission system. A stochastic model, capturing the behavior of a complex grid workload management system is proposed. To instantiate the model, detailed statistics are extracted from dense grid activity traces. The model is exploited in a simple job resubmission strategy. It provides quantitative inputs to improve job submission performance and it enables quantifying the impact of faults and outliers on grid operations