Profit maximization for electricity companies strongly depends on the tender strategies. To trade electricity at a high price and make the most of profits, electricity companies require suitable and optimal price offer models that take into account the operational constraints of electricity and price uncertainty in the market. Nowadays, the electricity industry is mostly inclined towards creating a competitive structure for increasing its productivity as well as technical and managerial efficiency. Here, the optimal distribution of the auction offers by the companies in the fully competitive electricity market is converted into an optimization problem and solved by the developed gray wolf optimizer (GWO) algorithm based on chaos theory. In a competitive electricity market, to increase the profit of the players in the market, the auction offers should be properly selected, because each player intends to increase its own profit. Of course, each of the players can change their level of offers without disrupting the customers’ welfare. This problem is even more important for large manufacturing companies and large loads because a considerable share of the market is allocated to them. Results of this method are compared with those of other evolutionary methods and indicate the suitable efficiency of the proposed method.

Optimal Strategy for Bidding in Deregulated-Structure of Electricity Market: A Competitive Model

Transformers constitute critical components of the power system and are associated with generation, transmission and distribution. So efficient performance of the transformer is highly concerned in the power industry. The harmonic pollution is profoundly affecting the efficiency of the transformer and caused by parasitic capacitance. This paper presents an analytical approach for calculating self-capacitance of power transformers based on the principle of electrostatic energy. The parasitic capacitance calculation for the high voltage side of the power transformer depends on the capacitance between the turns and between the layers investigated in detail.

Estimate the Parasitic Parameters of the Secondary Winding of the Power Transformer

The mechanical and electrical stability of the power and distribution transformers is essential by electricity providers and consumers. The transfer function method, specifically, Frequency Response Analysis (FRA) is quite well-known as the most accurate and reliable technique for determining the mechanical faults in transformer active part. This study presents a comprehensive method for transformer winding disk space variation (DSV) modeling using SPICE netlists. It is based on the elaborated winding RLC model, and the model data are validated with a practical work in this research work. The FRA measurements of normal and deformed scenarios are conducted and evaluated with the introduced technique. The behavior of the FRA spectra for normal and DSV scenarios is analyzed, and the model is validated and revealed a similar trend for both practical and netlists-based winding models. The proposed winding RLC model will enable researchers to study the effect of the other mechanical deformations on the frequency response curve without conducting the irreversible faults to the winding structure.

A New Transformer Winding RLC Model to Study the Effect of the Disk Space Variation on FRA Signature

The integration of distributed generation resources, including electric vehicles (EVs), has become increasingly important in supplying grid loads. EVs have the potential to act as a distributed generation source and help reduce the electrical company's expenses. However, their extensive use in distribution networks may cause some difficulties for the electricity grids, such as economic and scientific functioning problems and the potential for other applications. In this study, we propose a model to control coordinated and uncoordinated charging systems of grid-connected electric cars using two wind turbines and one solar power plant as distributed generation sources. The model divides EVs into four classes based on their grid shares and the number of accidental vehicles per class, utilizing the normal distribution function. The suggested model is solved using a hybrid firefly and cuckoo method. The goal function of the model is a combination of yearly energy loss cost and the operational cost of distributed generating units. The simulation, conducted on a 33-bus IEEE grid, demonstrates that the proposed model is highly effective and efficient. The results indicate that random EV charging leads to significantly higher expenses compared to the coordinated charging approach. Additionally, the peak demand reduces when EV charging is coordinated. 

Optimal energy modeling and planning in the power system via a hybrid firefly and cuckoo algorithm in the presence of renewable energy sources and electric vehicles

Economic, reliability, environmental and operation factors to achieve optimal operations of multiple microgrids

Transformer Frequency Response Analysis (FRA) is one of the most efficient methods to examine the mechanical condition of the transformer without opening the transformer tank and extracting the active part. FRA is a comparative method, where the measured response curve is compared to the reference trace. In this study, various statistical indices for frequency response results interpretation are introduced and the influence of inter-disk fault on each method is evaluated via practical study. Performance of each indicator is discussed and the most reliable index for FRA results interpretation in inter-disk fault suggested. Practical study of inter-disk short-circuit is performed by the rheostat connected in parallel with the winding of distribution transformer. The voltage taps of the transformers are used in order to have the access to different percentage of the transformer winding. Thus by regulating transformer output voltage and emulating short-circuit, there is possibility to distinguish the critical values for "green", "yellow" and "red" zones for transformer FRA and condition evaluation. These critical zone values are advised to be used for assessing the transformer and FRA data via statistical indicators.

Distribution Transformer Frequency Response Analysis: Behavior of Different Statistical Indices During Inter-disk Fault

Transformers are considered as the key components in power system network as they are employed in generation, transmission and distribution sectors. Hence electricity providers are highly concerned about proper operation of these valuable assets and specifically normal performance of the transformer active parts. One of the most reliable techniques to monitor the active part of the transformer is the Frequency Response Analysis (FRA). Given the fact that FRA technique has been successfully utilized in offline application for transformer diagnosis; it has been recently studied to apply the FRA once the transformer is in service, called online FRA. In this study, the transformer winding inter-disk and inter-turn faults are studied along with the effect of the bushing on frequency response signature in online FRA setup. Transformer winding physical model is created, simulated and numerically analyzed. It is revealed that the winding inter-disk and inter-turn faults lead to FRA anti-resonance frequency shift and response magnitude alteration in online FRA. Emulation of transformer bushing in the form of two paralleled capacitors unveils the significant influence of this component over the low frequency band of FRA spectrum. Destructive effect of the bushing reactive impedance should be taken into consideration during online FRA test measurements.

Roya Ahmadi Ahangar

Papers

Distribution Transformer Frequency Response Analysis: Behavior of Different Statistical Indices During Inter-disk Fault

Simulation and Analysis of Transformer Winding Inter-disk and Inter-turn Faults for Online Diagnosis