Journal of Modeling and Simulation in Electrical and Electronics Engineering
No. 0, 2015

Energy price forecast is the key information for generating companies to prepare their bids in the electricity markets. However, this forecasting problem is complex due to nonlinear, non-stationary, and time variant behavior of electricity price time series. Accordingly, in this paper a new strategy is proposed for electricity price forecast. The forecast strategy includes Wavelet Transform (WT), Auto-Regressive Integrated Moving Average (ARIMA) and Radial Basis Function Neural Networks (RBFN). Also, an intelligent algorithm is applied to optimize the RBFN structure, which adapts it to the specified training set, reduce computational complexity and avoids overfitting. In the proposed forecast strategy, the WT provides a set of better-behaved constitutive series, ARIMA generates a linear forecast and RBFN is developed as a tool for nonlinear pattern recognition to correct the forecast error. The proposed strategy is applied for price forecasting of electricity market of mainland Spain and its results are compared with the results of several other price forecast methods. These comparisons confirm the validity of the developed approach.

In this paper, an efficient and comprehensive hybrid intelligent technique for the optimal placement of phasor measurement units (PMUs) is proposed to minimize the number of PMU installation subjected to full network observability. Three main purposes of PMUs output synchronous measurements are monitoring, control, and protection of power system. We have combined Binary Imperialistic Competition Algorithm (BICA) and Genetic Algorithm (GA) for assuring complete observability under normal and single PMU loss or single line outage cases. Zero-injected buses which are transfer buses in the power system network are considered to obtain the best performance. They have capability to reduce the number of required PMUs for full observation of the power system network. The effectiveness of the proposed method is verified via 400 kV Khorasan network using MATLAB software environment. Experimental results show that minimum number of required PMUs and maximum bus observations can be achived by the proposed method.

This paper discusses the control of flexible microgrids, consisting of a Redox Flow Batteries (RFB) and a new power conditioning system (PCS) for the RFB. Considering the importance of energy storage, this study is essential in power systems that are developed cautiously. RFB is connected to power system by a DC/DC or DC/AC converter to produce a DC voltage. It is very important that this converter be effectively modeled and controlled for applications in microgrids. This paper focuses on simultaneous active and reactive power control in RFB systems. In this regard, this study proposes a new Flexible AC Transmission System (FACTS) compensator for microgrids which is able to control the active and reactive power. This type of compensator presents a good transient response. The simulation results, performed by MatlabSimulink toolbox, show the validity of the proposed system.

In this paper, a multi-objective reconfiguration problem has been solved simultaneously by a modified ant colony optimization algorithm. Two objective functions, real power loss and energy not supplied index (ENS), were utilized. Multi-objective modified ant colony optimization algorithm has been generated by adding non-dominated sorting technique and changing the pheromone updating rule of original ACO. By proposed algorithm, a group of the best solutions can be obtained thatcalled pareto front. None of these solutions are completely better than others among this pareto front. Furtheremore, another objective function, i.e., voltage profile index has been separately considered to have better comparison between pareto front members. Simulations have been performed on two standard IEEE 16-bus and 33-bus test systems. The results show that the proposed heuristic modifiedalgorithm generates welldistributed Pareto optimal solutions for the multi-objective reconfiguration problem.

In this paper, an Adaptive Neuro Fuzzy Inference System (ANFIS) based control is proposed for the tracking of a Micro-Electro Mechanical Systems (MEMS) gyroscope sensor. The ANFIS is used to train parameters of the controller for tracking a desired trajectory. Numerical simulations for a MEMS gyroscope are looked into to check the effectiveness of the ANFIS control scheme. It proves that the system using the proposed ANFIS controller has better tracking performance than that using only a fuzzy control or Neural network approach to control over the existence of external perturbations.

Image completion is one of the subjects in image and video processing which deals with restoration of and filling in damaged regions of images using correct regions. Exemplar-based image completion methods give more pleasant results than pixel-based approaches. In this paper, a new algorithm is proposed to find the most suitable patch in order to fill in the damaged parts. This patch selection method is recommended for exemplar-based approaches. The proposed method consists of three modifications: First, the selected patch’s size is considered bigger and then different weights are applied to different sections of the patch. Second, harmonic inpainting method is used in order to reduce the error propagation. Third, limiting the search space is done to improve and reduce the executing time. The acquired results depict that this method is effective and there is an improvement for quality of exemplar-based approaches.

Frequency Response Analysis (FRA) is popular technique which has been used since the last decade as a diagnostic method for transformers. However, accurate interpretation of FRA measurements is still challenging. Recent studies reveal that apart from winding deformation, FRA data can also be influenced by moisture variation in transformer paper insulation. Hence, a specific transformer’s model is fabricated for this study and the experiment was concentrated on the paper moisture variation and mechanical deformation influences on FRA spectrum deviation. Different physical changes to the test object are investigated and the results are discussed. At the end, the weakness of FRA evaluation indicators to recognize winding deformation under different circumstances is highlighted and a feasible solution is recommended.