Log in / Register
Home arrow Computer Science arrow Harmonic Balance Finite Element Method: Applications in Nonlinear Electromagnetics and Power Systems

HBFEM Modeling of the DC-Biased Transformer in GIC Event

GIC Effects on the Transformer

During a space weather storm, which is a result of solar activity, the magnetosphere- ionosphere system becomes disturbed, with intense and rapidly changing currents. At the Earth’s surface, varying space currents manifest themselves as disturbances or storms in the geomagnetic field. As expressed by Faraday’s law of induction, a geoelectric field also exists in connection with a geomagnetic storm. The electric field produces currents, known as “geomagnetically induced currents” (GIC), in ground-based

Waveforms of magnetic flux in the side yoke

Figure 6.20 Waveforms of magnetic flux in the side yoke

technological networks, such as high-voltage electric power transmission systems, oil and gas pipelines, telecommunication cables and railway equipment [7]. GIC thus constitute the ground end of the complicated space weather chain originating from the sun [8]. In power grids, GIC can saturate transformers, which may cause different problems, ranging from harmonics in the electricity to a blackout of the whole system and permanent damage of transformers [9].

Power transformers are one of the most strategic parts of the power system. They are in operation with long-distance transmission lines and complex intermeshed power grids, which have to contend with exposure to quasi-stationary low DC currents, or even high-amplitude geomagnetically induced currents (GIC) caused by recurrent solar magnetic disturbances. Although transformers are generally designed for operation under sinusoidal waves (including the harmonics), in reality they may be subjected to superimposed DC current excitation with varying levels. These levels may reach up to a few hundreds amps. These DC currents may be of external origin, as GIC or HVDC ground return mode stray currents.

Depending on their magnitude, the DC bias currents may have a detrimental effect on the integrity of the power transformers or their long-term performance, which may affect the power system’s reliability. With respect to this, user specifications relating to concern with superimposed DC excitations are generally clear enough regarding expected levels and possible durations. On the other hand, a good understanding of the behavior of power transformers under combined AC and DC excitations, as well as comprehensive modeling tools, are essential to enable the design of power transformers that fit these requirements [11].

To solve and analyze the GlC-related problems in transformers, several GIC modeling techniques are developed, including transmission line models, magnetic equivalent models, FEM-based numerical models and so forth [7, 11-13]. Among these, the equivalent circuit network based model is the most common method used to analyze GIC flow (from grounded transformer neutrals, through the HV windings into the transmission lines, with some impacts on the transformer). For structural problems with the transformer, the conventional finite element method has often been used to solve GIC- related DC biased transformer problems [12-14]. However, the well-established and accurate HBFEM approach has not been used in GIC modeling and simulation, due to the lack of technology transferring across disciplines and the complexity of HBFEM theory. As introduced and discussed in previous chapters, the HBFEM-based full-wave computational electromagnetic method has been employed in HVDC transformer analyses in the DC biased condition. The computer modeling techniques are well established [15, 16].

Since the transformer is a nonlinear magnetic structure with an arbitrary size, a full- wave computational electromagnetic technique is required. Within the various full- wave techniques, the solution can be found in either the frequency or time domain. Each technique has its own strengths and weaknesses. Which technique is most appropriate for a particular problem depends upon the problem. There is no single numerical technique that will solve all GIC problems that an electrical engineer is likely to model. Different numerical techniques can be used to solve different application problems. For GIC effects on the transformer in combination with the grid, transient electromagnetic network models are required. However, a time domain technique will be more appropriate for a transient problem during the GIC event. In this case. the transformer is modeled as a magnetic subsystem of the total grid, to allow determination of the reactive power consumption and the harmonics of the current [7, 14].

It is common practice to design power transformers operated under sinusoidal conditions. However, in reality, some power transformers need to be able to maintain normal operations under increasingly complex excitation waveforms. The most common case of this is where DC currents are superimposed on the normal AC excitation. Users located in areas where GIC may occur often specify that the transformers or shunt reactors must be able to withstand the DC currents, superimposed to the rated AC current in the windings, without damage or excessive hot spot temperature rises. The currents are specified in absolute numerical values by the user, and may be as high as 100 A, having a duration that varies from a few seconds to several minutes.

The capability of the transformers or shunt reactors to withstand DC currents is normally demonstrated in the “Design Review” [10]. Since the main requests in user specifications are related to transformers/shunt reactors prone to combined DC/AC excitation, the impact on transformer design and design verification processes needs to be investigated. HBFEM-based numerical modeling techniques will play an important role to support the design verification process, in order to mitigate the problems caused by the combined AC and DC excitations.

Found a mistake? Please highlight the word and press Shift + Enter  
< Prev   CONTENTS   Next >
Business & Finance
Computer Science
Language & Literature
Political science