G. Stavrakakis
Technical University of Crete
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Publication
Featured researches published by G. Stavrakakis.
Energy and Buildings | 2001
D. Kolokotsa; D Tsiavos; G. Stavrakakis; Kostas Kalaitzakis; E Antonidakis
The aim of this paper is to present and evaluate control strategies for adjustment and preservation of air quality, thermal and visual comfort for buildings’ occupants while, simultaneously, energy consumption reduction is achieved. Fuzzy PID, fuzzy PD and adaptive fuzzy PD control methods are applied. The inputs to any controller are: the PMV index affecting thermal comfort, the CO2 concentration affecting indoor air quality and the illuminance level affecting visual comfort. The adaptive fuzzy PD controller adapts the inputs and outputs scaling factors and is based on a second order reference model. More specifically, the scaling factors are modified according to a sigmoid type function, in such a way that the measured variable to be as closer as possible to the reference model. The adaptive fuzzy PD controller is compared to a non-adaptive fuzzy PD and to an ON–OFF one. The comparison criteria are the energy required and the controlled variables response. Both, energy consumption and variables responses are improved if the adaptive fuzzy PD type controller is used. The buildings’ response to the control signals has been simulated using MATLAB/SIMULINK.
Advances in Building Energy Research | 2009
D. Kolokotsa; Christina Diakaki; Evangelos Grigoroudis; G. Stavrakakis; Kostas Kalaitzakis
Abstract The aim of the present chapter is to analyse the decision support processes towards energy efficiency and improvement of the environmental quality in buildings. The main criteria in the decision analysis of buildings are categorized. The decision alternatives which may formulate specific actions, or group of actions (strategies) for buildings’ sustainability are analysed. The decision methodologies presented are separated to online (based on real-time operation of buildings) and offline decision approaches. Both approaches are supported by simulation, multi-objective programming optimization techniques, multi-criteria decision analysis techniques and their combinations in order to reach optimum solution, rank alternatives or provide trade-offs between the criteria. The advantages and drawbacks of the various methods are discussed and analysed.
Electric Power Systems Research | 2002
Konstantinos Kalaitzakis; G. Stavrakakis; E.M. Anagnostakis
Abstract This paper presents the development and application of advanced neural networks to face successfully the problem of the short-term electric load forecasting. Several approaches including Gaussian encoding backpropagation (BP), window random activation, radial basis function networks, real-time recurrent neural networks and their innovative variations are proposed, compared and discussed in this paper. The performance of each presented structure is evaluated by means of an extensive simulation study, using actual hourly load data from the power system of the island of Crete, in Greece. The forecasting error statistical results, corresponding to the minimum and maximum load time-series, indicate that the load forecasting models proposed here provide significantly more accurate forecasts, compared to conventional autoregressive and BP forecasting models. Finally, a parallel processing approach for 24 h ahead forecasting is proposed and applied. According to this procedure, the requested load for each specific hour is forecasted, not only using the load time-series for this specific hour from the previous days, but also using the forecasted load data of the closer previous time steps for the same day. Thus, acceptable accuracy load predictions are obtained without the need of weather data that increase the system complexity, storage requirement and cost.
IEEE Transactions on Instrumentation and Measurement | 2002
Stefanos Goumas; Michael E. Zervakis; G. Stavrakakis
Wavelets provide a powerful tool for nonstationary signal analysis. In vibration monitoring, the occurrence of occasional transient disturbances makes the recorded signal nonstationary, especially during the start-up of an engine. Through the wavelet analysis, transients can be decomposed into a series of wavelet components, each of which is a time-domain signal that covers a specific octave frequency band. Disturbances of small extent (duration) are amplified relative to the rest of the signal when projected to similar size wavelet bases and, thus, they can be easily detected in the corresponding frequency band. This paper presents a new method for extracting features in the wavelet domain and uses them for classification of washing machines vibration transient signals. The discrete wavelet transform (DWT), in conjunction with statistical digital signal processing techniques, is used for feature extraction. The Karhunen Loeve transform (KLT) is used for feature reduction and decorrelation of the feature vectors. The Euclidean, Mahalanobis, and Bayesian distance classifiers, the learning vector quantization (LVQ) classifier, and the fuzzy gradient classifier are used for classification of the resulting feature space. Classification results are illustrated and compared for the rising part of vibration velocity signals of a variety of real washing machines with various defects.
Engineering Applications of Artificial Intelligence | 2002
D. Kolokotsa; G. Stavrakakis; Kostas Kalaitzakis; D. Agoris
Abstract In this paper, an optimized fuzzy controller is presented for the control of the environmental parameters at the building zone level. The occupants’ preferences are monitored via a smart card unit. Genetic algorithm optimization techniques are applied to shift properly the membership functions of the fuzzy controller in order to satisfy the occupants’ preferences while minimizing energy consumption. The implementation of the system integrates a smart card unit, sensors, actuators, interfaces, a programmable logic controller (PLC), local operating network (LON) modules and devices, and a central PC which monitors the performance of the system. The communication of the PLC with the smart card unit is performed using an RS 485 port, while the PLC-PC communication is performed via the LON network. The integrated system is installed and tested in the building of the Laboratory of Electronics of the Technical University of Crete.
Journal of Intelligent and Robotic Systems | 2002
Eleftheria S. Sergaki; G. Stavrakakis; A. Pouliezos
This paper considers the control problem of a robotic manipulator with separately excited dc motor drives as actuators. An innovative method is proposed which achieves robot speed-control requirements, with simultaneous minimization of total electromechanical losses, while the drives follow the desired speed profiles of the robot joints under various loads and random load disturbances. If there is no demand for a specific speed profile, the optimal speed trajectory is determined by minimizing an electromechanical losses criterion. Controllable energy losses, such as armature copper losses, armature iron losses, field copper losses, stray load losses, brush load losses, friction and windage losses, can be expressed proportionally to the squares of the armature and the field (exciting) currents, the angular velocity and the magnetic field flux. The controllable energy loss term is also included in the optimal control integral quadratic performance index, defined for the whole operation period. Thus the appropriate control signals required for following the desired trajectory by simultaneous energy loss minimization for the whole operation interval are achieved. Two case studies of optimal robot control with and without minimization of actuator energy losses are presented and compared, showing the energy savings that can be achieved by the proposed methodology.
Measurement | 1999
Nicola Paone; Lorenzo Scalise; G. Stavrakakis; A. Pouliezos
This paper addresses the problem of developing an on-line diagnostic system for mechanical quality control of household appliances. The selection of a suitable measurement technique for feature extraction is discussed; the choice of a laser Doppler vibrometer technique and a laboratory measurement station for washing machines is presented. Vibration velocity and displacement are measured over a grid of points on the machine surface and data are stored in a database suitable for processing, both with good appliances and with defect ones with known defects. Features from the vibration velocity spectrum are used as the input to a likelihood classifier, which is shown to achieve very good classification scores.
Advances in Building Energy Research | 2011
Triantafyllia Nikolaou; D. Kolokotsa; G. Stavrakakis
The energy benchmarking, rating and classification of buildings are necessary procedures for energy certification scheme adoption, energy regulation establishment, energy-efficiency promotion and energy consumption reduction, according to the Directive 2002/91/EC and its implementation in EU member states. The aim of this paper is to investigate and present research works, tools and programs focused on energy benchmarking methods, energy rating procedures and classification schemes for the building sector. The European Committee for Standardization method of benchmarking and rating for buildings are analyzed, as well as a proposed integrated classification method based on the application of clustering techniques to virtual building data sets of office buildings in Greece.
Energy Conversion and Management | 2002
D. Kolokotsa; Kostas Kalaitzakis; E Antonidakis; G. Stavrakakis
Distributed control and energy management for buildings is a viable solution, ensuring both indoor comfort for the occupants and reduction of energy consumption. The aim of this paper is to present the architecture of a distributed building energy management system that can be installed in new as well as in existing buildings, which are more energy inefficient. The system integrates a smart card unit, acting as a user machine interface, sensors, actuators, interfaces, a PLC controller that incorporates the fuzzy control algorithm, local operating network (LON) modules and devices and an optional PC which monitors the performance of the system. The distributed control architecture is based on the properties of the LON. The complete system is installed and tested in the Laboratory of Electronics of the Technical University of Crete.
Renewable Energy | 1997
E. Nogaret; G. Stavrakakis; Georges Kariniotakis; M. Papadopoulos; Nikos D. Hatziargyriou; Aris Androutsos; Stavros A. Papathanassiou; J. A. Peças Lopes; J. Halliday; G. Dutton; J. Gatopoulos; V. Karagounis
An advanced control system for the optimal operation and management of autonomous wind-diesel systems is presented. This system minimises the production costs through an on-line optimal scheduling of the power units, which takes into account the technical constraints of the diesel units, as well as short-term forecasts of the load and renewable resources. The power system security is maximised through on-line security assessment modules, which enable the power system to withstand sudden changes in the production of the renewable sources. The control system was evaluated using data from the island of Lemnos, where it has been installed and operated since January 1995.