Ioana Fagarasan

Brief Causal fault detection and isolation based on a set-membership approach

This paper presents a diagnostic methodology relying on a set-membership approach for fault detection and on a causal model for fault isolation. Set-membership methods are a promising approach to fault detection because they take into account a priori knowledge of model uncertainties and measurement errors. Every uncertain model parameter and/or measurement is represented by a bounded variable. In this paper, detection consists of verifying the membership of measurements to an interval. First order discrete time models are used and their output is explicitly computed with interval arithmetic. Fault isolation relies on a causal analysis and the exoneration principle, which allows focusing the consistency tests on simple local models. The isolation strategy consists of two steps: performing minimal tests found with the causal graph and determining on line additional relevant tests that reduce the final diagnosis. An application for a nuclear process is used in order to illustrate the methods efficiency.

Increasing Energy Efficiency in Data Centers Using Energy Management

Data centers provide the global community withan indispensable service: nearly unlimited access to almost any kind of information we can imagine. With the increasing demand of information, the high energy costs has raised the issue of power consumption. The main goal in achieving data center energy efficiency can be translated into the ensuring that IT equipment uses, as maximum power as possible from the power entering the data center to compute useful work but at the same time the service level agreement between costumers and managers has to be satisfied. In this paper, different concepts of efficiency that are linked with multiple methods of increasing energy efficiency into a data center, will be presented, as well as different principles of energy management. A comprehensive overview of the currently available energy metrics will be provided, followed by an in-depth analysis of their commonalities and differences. An analyze about the degree of freedom encountered into the process of energy management, will be afforded. This paper presents a global overview of the energy efficiency management process into a data center.

Embedded networked monitoring and control for renewable energy storage systems

Energy storage plays an important role in managing effectively the integration of distributed renewable energy generation within the electrical networks of the future. Pervasive monitoring and control of these systems makes growing use of information and communication technologies, which aim at secure and economic operation at various scales from microgrids to system-wide integration. Among these, low power wireless communication and computing embedded systems, in the main form of wireless sensor networks (WSN), have become a robust solution. Through hardware and software architectures, along with appropriate mechanisms e.g. for data collection and aggregation, wireless communication protocols and standards, they represent a valid solution in assuring continuous and reliable operation. The paper introduces a cyber-physical framework for renewable storage systems monitoring and control and discusses the application of wireless sensor networks to densely instrument such deployments. A hardware-in-the-loop type structure is designed which allows both testing various types of real storage systems, as well as more complex simulated models derived from large scale applications. We argue that the specific advantages brought forward by the advances in WSN technology can be put to efficient use for local distributed intelligence and control. Experimental data collected is analyzed in order to achieve an insight into the characteristics of the proposed solution.

Modern approaches in power system control

The structure and coordination of the electrical power system (EPS) are presented in this paper with respect to three concepts: system theory, systems analysis and multi-agent techniques. The above mentioned concepts are discussed approaching the EPS behaviour and functioning based on actual problems regarding the globalisation of the energy production and transportation, integration of different renewable sources of energy with the conventional power systems and the safety aspects of connecting the distributed generation to the interconnected large system.

Fuzzy decision support system for solar tracking optimization

This paper presents the design and implementation of a fuzzy decision support system for control of photovoltaic panel movement in order to improve the availability of solar energy and the systems total efficiency. The designed algorithm is implemented on a solar tracking experimental platform using a fuzzy logic control strategy. It makes use of measured values for radiation from appropriate sensors and assures command of the platforms two positioning motors. The solution was developed as a virtual instrument, using a graphical programming environment. This allows for fast deployment, versatility and scalability.

Parity equations for fault detection and isolation

Sensors, actuators or physical components in engineering systems are often subjected to un-permitted or unexpected deviations from usual operating conditions. With a relatively small computing effort and with good results to unmeasured disturbances, the parity equations build for a specific process are proven to be very useful to provide fault detection residuals in order to identify the fault.

Advanced Control of a Steam Generator

Economic feasibility of a nuclear power plant requires smooth and uninterrupted plant operation in the face of varying electrical power demand. The feed-water system in a nuclear power plant is a major contributor to plant unavailability. The investigations about operation experiences of a power plant show that one of frequent causes of shutdowns is by violation of safety limits on the water level and is common at low operating power where the plant exhibits strong non-minimum phase characteristics. This paper presents a framework for addressing this problem based on a method of advanced control based on fuzzy model predictive control. Furthermore, fuzzy model based fault detection methods are elaborated envisaging fault tolerant control. Results from validation of the advanced control system are presented. A new concept of modular advanced control system designed for a seamless and gradual integration into the existing distributed control system is proposed

Bounding Approach for Fault Detection and Diagnosis

Abstract This paper focuses on a fault detection method taking model uncertainties into account. Every uncertain parameter is represented by a bounded variable. The proposed strategy for fault detection and diagnosis consists in modeling the uncertainties, in generating output envelopes and then in testing their coherency with measurements. An application of the method was carried out on a nuclear fuel reprocessing plant simulator. A fault scenario will be presented in order to enlighten the methodology

Distributed Generation Influence on Smart Distribution Grids

Abstract This paper presents a methodology for choosing the best location of a distributed generation (DG) unit in a distribution grid considering the short-circuit current values. The optimum position into the grid is searched according to the minimum short circuit current. A three bus network was used in order to test the methodology and a real distribution network in Romania was proposed.

Process modelling for Load Frequency Control in power systems

Underlining first the principle of Load Frequency Control (LFC) according to the UCTE regulations this paper also presents simple continuous time models identified for the main hydro and thermal power generation units used by the LFC in Romanian Power System. Different models were proposed in previous articles but they are very complex for LFC studies. An experimental identification procedure based on deterministic methods with rectangular pulse sample signal is proposed to estimate the values of models parameters. These models can be used for tuning LFC systems as well as for building and setting up a real-time simulator for dispatcher training.