In this paper, a novel risk-based, two-objective (technical and economical) optimal reactive Power dispatch method in a wind-integrated Power system is proposed which is more consistent with operational criteria.  The technical objective includes the minimization of the new voltage instability risk index. The economical objective includes cost minimization of reactive Power generation and active Power loss. The proposed voltage instability risk employs a hybrid possibilistic (Delphi-Fuzzy)-probabilistic approach that takes into consideration the operator’s experience, the wind speed and demand forecast uncertainties when quantifying the risk index. The decision variables are the reactive Power resources of the system. To solve the problem, the modified multi-objective particle swarm optimization algorithm with sine and cosine acceleration coefficients is utilized. The method is implemented on the modified IEEE 30-bus system. The proposed method is compared with those in the previously published literature, and the results confirm that the proposed risk index is better at estimating the voltage instability risk of the system, especially in cases with severe impact and low probability. In addition, according to the simulation results compared to typical security-based planning, the proposed risk-based planning may increase the security and economy of the system due to better utilization of system resources.

In this paper, a new method for extending and relaxing the noise-coupling (NC) technique is proposed to enhance the noise-shaping order without adding the number of integrators. The noise-shaping order of the introduced ∑∆ modulator whit applying a second-order noise-coupling technique is enhanced and its performance with optimizing the noise transfer function (NTF) zeros is improved. Also, by removing the analog adder at feedforward path and transferring it to a new feedback branch before the last integrator and adding second-order NC path can be decreased the input voltage swing to the quantizer. Thus, by improving the modulator resolution, Power consumption can be reduced. Mathematical analyses and behavioural simulation results confirm the effectiveness of the new NC method. To examine its performance, a 2nd-order single loop ΣΔ modulator was designed. The new noise-coupling method is used to achieve the three-order noise shaping to increase the resolution with low complexity and low-Power. The results show an outstanding improvement in signal-to-noise and distortion ratio (SNDR) compared to the conventional structure.

A study of the impact of merger of economic units, in any sector, including electricity generation is important in order to arrive at a logical choice. There are two different approaches to the issue. On the one hand some are against any merger of economic units, while others say they should be welcomed if they lead to increase efficiency and hence profitability of the operating units.This research investigates the problem from the perspective of a market regulator and therefore its concern is whether the merger will lead to increased concentration in the sector and hence lead to monopoly Power. Any market regulator has to be sensitive to these issues and study them carefully. Research result shows that if Power plants merge, the sector will approach to the limits in terms of effective competition and can move to a situation of restricted competition.If there were no limitation on the capacity of merged Power plants, the number of mergers that led to simultaneous change of HHI and CR4 indices over the threshold is 111 cases, and when a limit of 2000 MW of capacity is imposed on Power plant capacity, the number of mergers that increase market concentration, drops down to 22 cases.

State estimation of nuclear reactors often plays a crucial role in accomplishing load-following control. This study presents a novel approach that leverages a weighted particle filter to address the challenges associated with estimating these crucial parameters, including relative precursor concentration (C_r) and fuel temperature (T_f), under varying reactor Power conditions. A high-fidelity nonlinear dynamic reactor model was developed, incorporating noises in both process and measurement models. The proposed method was evaluated by extensive simulations under a wide range of operational scenarios. The particle filter demonstrated exceptional performance in tracking the time-varying states of the nuclear reactor. Comparative analysis with a conventional Kalman filter and the extended Kalman filter revealed the superior robustness of the particle filter in handling nonlinearities inherent in nuclear systems. The proposed approach offers several advantages, including the ability to capture multimodal distributions, handle non-Gaussian noise, and provide probabilistic estimates. Despite the increased computational cost associated with particle filtering, the benefits in terms of estimation accuracy and reliability justify its application in nuclear Power plant monitoring and control systems.

Monitoring and evaluation of transformers are essential to prevent their insulation failure. In this paper, the use of 2-furan-carboxaldehyde (2-FAL) and methanol (MeOH) concentrations as the main products of paper insulation degradation, and insulation condition markers, has been studied. In order to study the degradation process and production of degradation products, the thermal aging process of the transformer insulation system was implemented in laboratory conditions. The results of laboratory studies show that in the early stages of degradation the amount of MeOH is significant compared to 2-FAL. Also, the estimation of the degree of polymerization (DP) in the early stages of degradation (DP>800) through MeOH concentration and with decreasing DP (DP <800) through 2-FAL concentration is closer to the real value. The results of studies performed on 35 distribution transformers confirm the production of significant amounts of MeOH in the early stages of degradation. Also, the estimated DP values for the studied transformers were obtained through 2-FAL and MeOH concentration. The results show that estimating the amount of DP through MeOH concentration is associated with a probability of error of about 9% compared to estimating DP through 2-FAL concentration.

Assessing market Power and determining market structure of various agricultural as well as industrial products have always been considered as important issues in microeconomics. Different market structures can have major effects on levels of productions as well as on prices of various products. This study was conducted to determine the structure of meat sale market applying New Empirical Industrial Organization (NEIO) approach to a sample of meat prices, to investigate market Power and cost efficiency of meat industry in Fars province. Date used in this study consist of sheep and cow and calf carrion price at the stockyard door, retail price of sheep and cow and calf meat, wage price index, energy price index and transportation price index in the industry sector. The results revealed that firms in sheep and cow slaughter industry have market Power (market Power effect for firms in sheep and cow slaughter are respectively 0.893 and 0.751) and can gain from collusions with each others to supply their products to the retailers with higher prices and therefore, decreasing concentration in this industry is suggested.