Towards a future SCADA

Currently, Power Systems (PS) already accommodate a substantial penetration of DG and operate in competitive environments. In the future PS will have to deal with largescale integration of DG and other distributed energy resources (DER), such as storage means, and provide to market agents the means to ensure a flexible and secure operation. This cannot be done with the traditional PS operation. SCADA (Supervisory Control and Data Acquisition) is a vital infrastructure for PS. Current SCADA adaptation to accommodate the new needs of future PS does not allow to address all the requirements. In this paper we present a new conceptual design of an intelligent SCADA, with a more decentralized, flexible, and intelligent approach, adaptive to the context (context awareness). Once a situation is characterized, data and control options available to each entity are re-defined according to this context, taking into account operation normative and a priori established contracts. The paper includes a case-study of using future SCADA features to use DER to deal with incident situations, preventing blackouts.

Scheduling distributed energy resources in an isolated grid - an artificial neural network approach

Power Systems (PS), have been affected by substantial penetration of Distributed Generation (DG) and the operation in competitive environments. The future PS will have to deal with large-scale integration of DG and other distributed energy resources (DER), such as storage means, and provide to market agents the means to ensure a flexible and secure operation. Virtual power players (VPP) can aggregate a diversity of players, namely generators and consumers, and a diversity of energy resources, including electricity generation based on several technologies, storage and demand response. This paper proposes an artificial neural network (ANN) based methodology to support VPP resource schedule. The trained network is able to achieve good schedule results requiring modest computational means. A real data test case is presented.

A study on the authentication method for TAmI in ambient intelligence (secure group decision making toolkit)

It is difficult to get the decision about an opinion after many users get the meeting in same place. It used to spend too much time in order to find solve some problem because of the various opinions of each other. TAmI (Group Decision Making Toolkit) is the System to Group Decision in Ambient Intelligence [1]. This program was composed with IGATA [2], WebMeeting and the related Database system. But, because it is sent without any encryption in IP / Password, it can be opened to attacker. They can use the IP / Password to the bad purpose. As the result, although they make the wrong result, the joined member can’t know them. Therefore, in this paper, we studied the applying method of user’s authentication into TAmI.

Risk criteria in occupational environments: critical overview and discussion

The current work can be seen as a starting point for the discussion of the problematic on risk acceptance criteria in occupational environments. Some obstacles to the quantitative acceptance criteria formulation and use were analyzed. A look to the long tradition of major hazards accidents was also performed. This work shows that organizations can have several difficulties in acceptance criteria formulation and that the use of pre-defined acceptance criteria in risk assessment methodologies can be inadequate in some cases. It is urgent to define guidelines that can help organizations in the formulation of risk acceptance criteria for occupational environments.

LNT: a logical neighbor tree secure group communication scheme for wireless sensor networks

Secure group communication is a paradigm that primarily designates one-to-many communication security. The proposed works relevant to secure group communication have predominantly considered the whole network as being a single group managed by a central powerful node capable of supporting heavy communication, computation and storage cost. However, a typical Wireless Sensor Network (WSN) may contain several groups, and each one is maintained by a sensor node (the group controller) with constrained resources. Moreover, the previously proposed schemes require a multicast routing support to deliver the rekeying messages. Nevertheless, multicast routing can incur heavy storage and communication overheads in the case of a wireless sensor network. Due to these two major limitations, we have reckoned it necessary to propose a new secure group communication with a lightweight rekeying process. Our proposal overcomes the two limitations mentioned above, and can be applied to a homogeneous WSN with resource-constrained nodes with no need for a multicast routing support. Actually, the analysis and simulation results have clearly demonstrated that our scheme outperforms the previous well-known solutions.

Time-bounded distributed QoS-aware service configuration in heterogeneous cooperative environments

The scarcity and diversity of resources among the devices of heterogeneous computing environments may affect their ability to perform services with specific Quality of Service constraints, particularly in dynamic distributed environments where the characteristics of the computational load cannot always be predicted in advance. Our work addresses this problem by allowing resource constrained devices to cooperate with more powerful neighbour nodes, opportunistically taking advantage of global distributed resources and processing power. Rather than assuming that the dynamic configuration of this cooperative service executes until it computes its optimal output, the paper proposes an anytime approach that has the ability to tradeoff deliberation time for the quality of the solution. Extensive simulations demonstrate that the proposed anytime algorithms are able to quickly find a good initial solution and effectively optimise the rate at which the quality of the current solution improves at each iteration, with an overhead that can be considered negligible.

Dynamic Approach and Testbed for Small and Medium Players Simulation in Smart Grid Environments

The Smart Grid environment allows the integration of resources of small and medium players through the use of Demand Response programs. Despite the clear advantages for the grid, the integration of consumers must be carefully done. This paper proposes a system which simulates small and medium players. The system is essential to produce tests and studies about the active participation of small and medium players in the Smart Grid environment. When comparing to similar systems, the advantages comprise the capability to deal with three types of loads – virtual, contextual and real. It can have several loads optimization modules and it can run in real time. The use of modules and the dynamic configuration of the player results in a system which can represent different players in an easy and independent way. This paper describes the system and all its capabilities.

Application of Visual-Inertial SLAM for 3D Mapping of Underground Environments

The underground scenarios are one of the most challenging environments for accurate and precise 3d mapping where hostile conditions like absence of Global Positioning Systems, extreme lighting variations and geometrically smooth surfaces may be expected. So far, the state-of-the-art methods in underground modelling remain restricted to environments in which pronounced geometric features are abundant. This limitation is a consequence of the scan matching algorithms used to solve the localization and registration problems. This paper contributes to the expansion of the modelling capabilities to structures characterized by uniform geometry and smooth surfaces, as is the case of road and train tunnels. To achieve that, we combine some state of the art techniques from mobile robotics, and propose a method for 6DOF platform positioning in such scenarios, that is latter used for the environment modelling. A visual monocular Simultaneous Localization and Mapping (MonoSLAM) approach based on the Extended Kalman Filter (EKF), complemented by the introduction of inertial measurements in the prediction step, allows our system to localize himself over long distances, using exclusively sensors carried on board a mobile platform. By feeding the Extended Kalman Filter with inertial data we were able to overcome the major problem related with MonoSLAM implementations, known as scale factor ambiguity. Despite extreme lighting variations, reliable visual features were extracted through the SIFT algorithm, and inserted directly in the EKF mechanism according to the Inverse Depth Parametrization. Through the 1-Point RANSAC (Random Sample Consensus) wrong frame-to-frame feature matches were rejected. The developed method was tested based on a dataset acquired inside a road tunnel and the navigation results compared with a ground truth obtained by post-processing a high grade Inertial Navigation System and L1/L2 RTK-GPS measurements acquired outside the tunnel. Results from the localization strategy are presented and analyzed.

Children’s Indoor Exposures to (Ultra)Fine Particles in an Urban Area: Comparison Between School and Home Environments

Due to their detrimental effects on human health, scientific interest in ultrafine particles (UFP), has been increasing but available information is far from comprehensive. Children, who represent one of the most susceptible subpopulation, spend the majority of time in schools and homes. Thus, the aim of this study is to (1) assess indoor levels of particle number concentrations (PNC) in ultrafine and fine (20–1000 nm) range at school and home environments and (2) compare indoor respective dose rates for 3- to 5-yr-old children. Indoor particle number concentrations in range of 20–1000 nm were consecutively measured during 56 d at two preschools (S1 and S2) and three homes (H1–H3) situated in Porto, Portugal. At both preschools different indoor microenvironments, such as classrooms and canteens, were evaluated. The results showed that total mean indoor PNC as determined for all indoor microenvironments were significantly higher at S1 than S2. At homes, indoor levels of PNC with means ranging between 1.09 × 104 and 1.24 × 104 particles/cm3 were 10–70% lower than total indoor means of preschools (1.32 × 104 to 1.84 × 104 particles/cm3). Nevertheless, estimated dose rates of particles were 1.3- to 2.1-fold higher at homes than preschools, mainly due to longer period of time spent at home. Daily activity patterns of 3- to 5-yr-old children significantly influenced overall dose rates of particles. Therefore, future studies focusing on health effects of airborne pollutants always need to account for children’s exposures in different microenvironments such as homes, schools, and transportation modes in order to obtain an accurate representation of children overall exposure.

ezGo: A voice operated wheelchair with biosignal monitoring for home environments

In this paper we present ezGo, an electric powered wheelchair with a speech based interface and biosignal monitoring instrumentation. The user can use the voice, a natural communication method, for controlling the chair movement and obtain information about his health. Additionally a set of semi-autonomous modes with macro recording enable the execution of navigation tasks with little effort and improved precision. The main purpose of the system is to provide severely disabled persons with an assistive device that can improve their confidence and daily independence. The obtained results on usability tests showed that users consider ezGo a valuable help on their daily tasks and a very desirable addition to standard wheelchairs.