dan florin | University of Oradea (original) (raw)

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Papers by dan florin

Research paper thumbnail of Consumers Load Profile Classification Corelated to the Electric Energy Forecast

Research paper thumbnail of Assesment of Energy Efficiency for Urban Electric Transport Systems

Research paper thumbnail of Optimizing Phosphorus Removal by Chemical Addition at Oradea Wastewater Treatment Plant

The effluent contains a range of pollutants, some of which are removed more or less conventional ... more The effluent contains a range of pollutants, some of which are removed more or less conventional in the purification steps, while others are held very little or at all, in the conventional treatment plants. Acute problems of water protection have led to the imposition of the severe conditions of concentrations limit permitted to the effluent discharged into the natural emissaries.

Research paper thumbnail of Electric Energy Consumption Forecast Within the Wastewater Treatment Plant Oradea

A B S T R A C T This paper focuses over short term load forecast (STLF) at wastewater treatment p... more A B S T R A C T This paper focuses over short term load forecast (STLF) at wastewater treatment plant Oradea which is an important consumer of electricity from the national energy system. The method used for forecasting and database analysis is to examine the statistical database containing the values of power measurements and analyse the correlation between them and performing forecast by a classical method (linear regression LR) and forecast using dynamic method (artificial neural networks ANN). Conclusions will be drawn on the basis of research results.

Research paper thumbnail of THE POWER ELECTRIC AUDIT OF AN  URBAN TRANSPORT OPERATOR

THE POWER ELECTRIC AUDIT OF AN URBAN TRANSPORT OPERATOR, Jun 7, 2009

Abstract – The paper is structured in four parts. In the first part we justify our concern regard... more Abstract – The paper is structured in four parts. In the first part we justify our concern regarding the power audit. In the second part we define the contours and how to work making AEE for an operator of urban transport. Part three contains a summary of the results, and the last part presents the conclusions of the analysis.

Research paper thumbnail of Methodological Considerations and Conclusions of Power Supply Load Forecast

Methodological Considerations and Conclusions of Power Supply Load Forecast, Jun 5, 2012

Abstract— The paper is structured in four parts. The first part presents the actuality and the op... more Abstract— The paper is structured in four parts. The first part presents the actuality and the opportunity of the subject, of the power supply load forecast in the context of EU policy objectives on energy efficiency and operation processes in an open market for electricity. The second part presents the methodological steps to be completed to forecast electricity consumption at a consumer or at a group of consumers. Mathematical models are outlined and also the software packages used to forecast electricity consumption. Part Three contains an application of power supply load forecast. Of the 12 consumers analysed by the authors, in this paper is presented the algorithm and results for one consumer. Conclusions of this paper present, in fact, a summary of conclusions with reference to the 12 consumers categorized in 3 categories (industrial users, residential users and service providers) which have been subject to detailed analysis.

Research paper thumbnail of CONSUMERS LOAD PROFILE CLASSIFICATION CORELATED TO THE ELECTRIC ENERGY FORECAST

text This paper focuses over short term load forecast (STLF). The method used for classification ... more text This paper focuses over short term load forecast (STLF). The method used for classification of consumers is to examine the statistical database containing the values of power measurements and analyse the correlation between them. Based on two types of forecasting and database analysis, namely the correlation, a consumer classification in consumer profiles will be done. Later we will highlight the best performing forecast method for a consumer, comparing forecast by a classical method (linear regression -LR) and forecast using dynamic method (artificial neural networks -ANN). Conclusions will be drawn on the basis of research results.

Research paper thumbnail of Consumers Load Profile Classification Corelated to the Electric Energy Forecast

Research paper thumbnail of Assesment of Energy Efficiency for Urban Electric Transport Systems

Research paper thumbnail of Optimizing Phosphorus Removal by Chemical Addition at Oradea Wastewater Treatment Plant

The effluent contains a range of pollutants, some of which are removed more or less conventional ... more The effluent contains a range of pollutants, some of which are removed more or less conventional in the purification steps, while others are held very little or at all, in the conventional treatment plants. Acute problems of water protection have led to the imposition of the severe conditions of concentrations limit permitted to the effluent discharged into the natural emissaries.

Research paper thumbnail of Electric Energy Consumption Forecast Within the Wastewater Treatment Plant Oradea

A B S T R A C T This paper focuses over short term load forecast (STLF) at wastewater treatment p... more A B S T R A C T This paper focuses over short term load forecast (STLF) at wastewater treatment plant Oradea which is an important consumer of electricity from the national energy system. The method used for forecasting and database analysis is to examine the statistical database containing the values of power measurements and analyse the correlation between them and performing forecast by a classical method (linear regression LR) and forecast using dynamic method (artificial neural networks ANN). Conclusions will be drawn on the basis of research results.

Research paper thumbnail of THE POWER ELECTRIC AUDIT OF AN  URBAN TRANSPORT OPERATOR

THE POWER ELECTRIC AUDIT OF AN URBAN TRANSPORT OPERATOR, Jun 7, 2009

Abstract – The paper is structured in four parts. In the first part we justify our concern regard... more Abstract – The paper is structured in four parts. In the first part we justify our concern regarding the power audit. In the second part we define the contours and how to work making AEE for an operator of urban transport. Part three contains a summary of the results, and the last part presents the conclusions of the analysis.

Research paper thumbnail of Methodological Considerations and Conclusions of Power Supply Load Forecast

Methodological Considerations and Conclusions of Power Supply Load Forecast, Jun 5, 2012

Abstract— The paper is structured in four parts. The first part presents the actuality and the op... more Abstract— The paper is structured in four parts. The first part presents the actuality and the opportunity of the subject, of the power supply load forecast in the context of EU policy objectives on energy efficiency and operation processes in an open market for electricity. The second part presents the methodological steps to be completed to forecast electricity consumption at a consumer or at a group of consumers. Mathematical models are outlined and also the software packages used to forecast electricity consumption. Part Three contains an application of power supply load forecast. Of the 12 consumers analysed by the authors, in this paper is presented the algorithm and results for one consumer. Conclusions of this paper present, in fact, a summary of conclusions with reference to the 12 consumers categorized in 3 categories (industrial users, residential users and service providers) which have been subject to detailed analysis.

Research paper thumbnail of CONSUMERS LOAD PROFILE CLASSIFICATION CORELATED TO THE ELECTRIC ENERGY FORECAST

text This paper focuses over short term load forecast (STLF). The method used for classification ... more text This paper focuses over short term load forecast (STLF). The method used for classification of consumers is to examine the statistical database containing the values of power measurements and analyse the correlation between them. Based on two types of forecasting and database analysis, namely the correlation, a consumer classification in consumer profiles will be done. Later we will highlight the best performing forecast method for a consumer, comparing forecast by a classical method (linear regression -LR) and forecast using dynamic method (artificial neural networks -ANN). Conclusions will be drawn on the basis of research results.

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