Mustafa Bagriyanik

Characterization of transients in transformers using discrete wavelet transforms

This paper presents the characterization of transients resulting from faults in transformers using discrete wavelet transform (DWT). This characterization will aid in the development of an automatic detection method for internal incipient faults in the transformers. The detection method can provide information to predict failures ahead of time so that the necessary corrective actions are taken to prevent outages and reduce down times. The analyzed data are obtained from simulations and experiments for different normal and abnormal operating cases such as external faults, internal short circuit faults, magnetizing inrush, and internal incipient faults. The simulation method and experiment setup are discussed. The experiments and simulations are conducted on a single-phase transformer as an example case. The results of applying the DWT are discussed.

Identifying transformer incipient events for maintaining distribution system reliability

This paper presents the time domain and time-frequency domain analysis results of incipient events in single-phase distribution transformers. This analysis aids in the development of an automatic detection method for internal incipient faults in the transformers. The detection method can provide information to predict failures ahead of time so that the necessary corrective actions are taken to prevent outages and reduce down times. The analyzed data was obtained from simulations and experiments. Time-frequency analysis was performed using discrete wavelet transform (DWT). The obtained results are discussed.

Power loss minimization using fuzzy multiobjective formulation and genetic algorithm

This paper presents a fuzzy multiobjective optimization and genetic algorithm based method to find optimum power system operating conditions. The objectives and constraints are modeled by fuzzy sets. The problem is formulated as a multiple objective problem subject to operational and electrical constraints. The proposed method uses the genetic algorithms (GA) to solve fuzzy optimization problem. In addition to active power losses, series reactive power losses of power transmission system are also considered as one of multiple-objectives. TCSC (thyristor controlled series capacitor) is considered as a control device together with shunt VAR sources, generators and transformers. Simulation results obtained from test systems demonstrate the effectiveness of the proposed method.

Experimental investigation of internal short circuit faults leading to advanced incipient behavior and failure of a distribution transformer

Transformer fault detection and diagnosis is becoming more important due to the restructuring of the electric power industry. In this era of deregulation, loading transformers to their optimum capacity is becoming normal practice, which in turn applies high stresses on the insulation of the transformers and increases the probability of occurrence of internal short circuit winding faults. Such faults can lead to catastrophic failure and hence cause outages. Utilities and other entities in the electric power business are therefore exploring ways of detecting these faults in transformers in the incipient stage. Terminal values, primary and secondary currents and voltages of the transformer convey information that can be used to detect internal transformer failures before developing a detection method. The behavior of these terminal values should be understood. In an effort to characterize the behavior of the terminal values of a transformer during internal short circuit and incipient faults, short circuit faults were staged on a 25 kVA, 7200 V/240 V/120 V two winding custom-built transformer. This paper discusses the results of the field experiments performed over a 19-month period. It presents time domain results of selected short circuit experiments. It also presents recordings of advance incipient-like behavior during the last set of experiments.

Demand Side Management potential of refrigerators with different energy classes

Power systems of today have several problems such as growing demand and fluctuations in energy consumption. Demand Side Management as a subtopic of Smart Grid provides various solutions to these problems. Intelligent Load Control has a great potential for load shifting and savings if used together with thermostatic loads. Cooling systems, especially refrigerators, mostly have a big ratio in residential energy consumption. Refrigerators with close parameters, similar working environments and periodic working schedules can provide accurate estimations of energy consumption with simulations. In this study, DSM potential of two refrigerators with different energy efficiency classes is analyzed. By using a refrigerator model and the measurements collected from real devices, achievable percentage of demand change in peak times and savings in annual electricity bills are estimated. The study showed that with multiple pricing and load control, annual electricity costs of refrigerators can be reduced by 12.60 to 14.78%, while decreasing demand in peak periods by 23.12 to 41.73%.

Evaluation of management strategies for thermostatic loads in Smart Grid

Conventional power system structure needs innovations to increase efficiency, reliability and participation of renewables. Smart Grid provides worthy solutions for achieving these goals. Between these solutions, the interest on Demand Side Management (DSM) options has increased in recent years. Improvements can be made in the intelligence of Demand Response (DR) to increase the benefits of DSM. The controller and the strategy going to be used for Intelligent Demand Response (IDR) need particular attention. In this study, different strategies for control of thermostatic loads are evaluated. Models of refrigerators with different energy efficiency classes are used in simulations to analyze the DSM potential. Various strategies were compared from the perspectives of demand changes in peak periods, savings in annual energy bills, changes of yearly energy consumptions and times of controller intervention.

A fuzzy-genetic algorithm based approach for controlling unscheduled flows using SC and PST

In de-regulated power systems the power flow control problem gains importance when an interconnected power transmission system is operated at or close to its power-carrying limits. Thus, the minimization of unscheduled power flows need to be succeeded efficiently and fast. In this paper, the effects of the devices both series capacitors (SC) and phase shifting transformers (PST) on the minimization of unscheduled power flows are presented. The problem is formulated as a multi-objective optimization problem in fuzzy environment. The constraints and objectives are defined using fuzzy membership functions. A finalized problem after fuzzy decision is solved using genetic algorithm. The method is applied to the IEEE 30 bus test system, and the results are presented.

Preventing loop flows using fuzzy set theory and genetic algorithms

In the de-regulated power systems the loop flow control issue is becoming important. This is especially true when the transmission system is operated at or close to its limits. Thus, prevention and/or control of loop flows problem need be solved efficiently and fast. We suggest a fuzzy set theory based method using genetic algorithm to solve this problem. In the proposed method the constraints and objectives are handled in fuzzy environment and the optimization problem is solved using genetic algorithms. The proposed method is applied to IEEE 14 and 30 bus test systems and the results are presented.

An event-driven energy management system for planned control of thermostatic loads

Thermostatically controlled loads, which represent the major portion of consumptions, have considerable shifting potential for Demand Response (DR) applications. In this study an event-driven intelligent control system for rescheduling thermostatic loads is worked on. In addition to the discussion of areas of use for the proposed system, a number of terms that can be used in decision making processes are defined. The performance of the proposed system for working with refrigerators according to the power output of a local photovoltaic system is simulated by the use of field data. The results are discussed from both grid-side and customer-side perspectives.

An evaluation of demand side management in a grid-connected PV system in Istanbul, Turkey

The application of renewable energy in electric power system is growing fast. There is an increasing need for economic evaluation to inform the photovoltaic (PV) allocation decisions of a range of decision-makers. For economical operation and control purposes, electric power users with PV systems are interested in the availability and the effects of these systems. This paper presents an evaluation of the solar PV systems that would be installed in Istanbul-Turkey. In addition to the technical and commercial parameters, the measurements are also used to carry out the evaluation. The effect of the solar PV on demand side management is also studied