Sergiu Stelian Iliescu

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.

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.

Forecasting Energy Consumption in Dwellings

Energy consumption is a major issue nowadays. The importance of forecasting energy consumption from end-user to power system operator becomes more obvious than ever. The consumption in the residential sector represents a significant percentage in the total electricity demand in Europe and all over the world and it is expected to grow. So, the prediction of energy consumption becomes a key component in the management (e.g. power flow) of the electrical grid. This paper presents different methods for prediction of energy consumption of electrical appliances used in dwellings. A stochastic approach is used since forecasting the consumption for a single appliance is more difficult that predicting the overall consumption. Different basic predictors are presented and a stochastic predictor is proposed and tested according to a prediction precision criterion. The enhancement of forecast precision is done by segmentation and aggregation of data. Several experiments are conducted for different appliances in the house and the results are discussed.

Building the DES-Plant Model in a Class of Hybrid Control Systems

Abstract The hybrid control system (HCS) considered in this paper comprises a continuous plant that is controlled, through an interface, by a discrete event system (DES). The continuous plant is abstracted to a DES-plant model and the DES controller is designed, within the DES theory. The paper discusses the extraction of the DES-plant model and proposes an algorithm, which avoids the integration of the plants state equations. Two examples and general conclusions are finally presented.

Automatic voltage regulation of the transformer units implemented in digital multifunction protection systems

The paper below present the main features of a digital multifunction protection system and of a voltage control function implemented in this kind of protection system, which control the voltage on the secondary side of a transformer. The paper also analyzes the functionality of a voltage control function included into a multifunction protection system of a 400/220 kV and 400 MVA power transformer unit from a transmission network. The simulation results relieve a prompt and secure action of the voltage control function, maintaining in tolerable ranges the voltage in the specified bus of the study network.

Evolved Fuzzy Control System for a Steam Generator

Poor control of steam generator water level is the main cause of unexpected shutdowns in nuclear power plants. Particularly at low powers, it is a difficult task due to shrink and swell phenomena and flow measurement errors. In addition, the steam generator is a highly complex, nonlinear and time-varying system and its parameters vary with operating conditions. Therefore, there is a need to systematically investigate the problem of controlling the water level in the steam generator in order to prevent such costly reactor shutdowns. The objective of this paper is to design, evaluate and implement a water level controller for steam generators based on a fuzzy model predictive control approach. An original concept of modular evolved control system, seamless and with gradual integration into the existent control system is proposed as base of implementation of the presented system.

Product defect prediction model

The prediction of software reliability can determine the current reliability of a product, using statistical techniques based on the failures data, obtained during testing or system usability. Software reliability growth models attempt to predict the number of defect using a correlation between exponential function and defect data. The purpose of this paper is to study the evolution of a real-life product over three releases, using the Rayleigh function in order to predict the number of defects. Our paper offers two possibilities for computing the model parameters, and then we should be able to decide which is better and what can be improved. Results from this study will be used to determine which approach is best to be used.

Potential and Application of Fuzzy Technology in Power Systems: A Survey

Abstract This paper presents practical applications of fuzzy sets methods to power systems control, design, operation and management. The paper includes an exposition of basic elements of fuzzy sets theory including basic properties, operations on fuzzy sets, fuzzy relations and their composition, linguistic variables, etc. Modern tools based on fuzzy sets theory to solve difficult power system problems such as: control applications, distribution system planning, load modeling and forecasting, in the case of unknown system structures and parameters or in the case of unknown process in absence of certain and reliable data are presented. The paper demonstrates that fuzzy methods can solve many difficult problems bringing new quality tor a more effective and reliable power supply.

Temperature control of a greenhouse heated by renewable energy sources

The paper proposes a system developed to provide heat for a greenhouse using parabolic trough collectors (GHPTC). The GHPTC control system has the goal to maintain the temperature inside the greenhouse at a desired level, with the actuating variable the flow of the conducting fluid through collector pipes. Considering this aspect, the proposed model takes into account as an output variable the internal temperature of the greenhouse as it influences directly the growth of the plants. The GHTPC model consists of two individual parts: the greenhouse model and the collectors model. Both were validated using real data, considering the maxim error between the real and simulated data on a period of one day. A nonlinear and linear model were deducted for the complex GHPTC system. Based on the linearized model, a PID controller was tuned and used to control the internal temperature in the greenhouse. The control method is suited for the system according to the obtained stationary and transient response performances.