The use of new financial instruments, and specifically option contracts, as a tool for risk management and Create Profitability, can help to boom exchanges and reduce the problems of the agricultural sector. Despite price fluctuations of agricultural products, it can be said from a variety of options contracts, an Asian Option can play a more effective part in reducing the risk of these contracts. According to this issue, the aim of this study is to determine the price of Asian Option contract for soybean meal. Monte Carlo simulation method was used to determine the price of Option. Required information includes historical data on the weekly price of soybean meal in the years 2013-16. The results show that this option rather than a simple European Option (Black-Scholes model) is cheaper. In addition to the standard Monte Carlo method, the Control Variates and antithetic Variates methods were used to reduce the variance simulation. The results indicate that the Control Variates in variance reduction Monte Carlo simulation method has a very good performance and significantly reduce the variance.

A known theorem in probability is adopted and through a probabilistic approach, it is generalized to develop a method for generating random deviates from the distribution of any continuous random variable. This method which may be considered as an approximate version of the Inverse Transform algorithm takes two random numbers to generate a random deviate. While maintaining all the other advantages of the Inverse Transform method such as the possibility of generating ordered as well as correlated deviates and being applicable to all density functions regardless of their parameter values.

A common method for Controlling a group of parallel converters in decentralized Control strategy structure in an island microgrid, the use is the droop-down characteristics of frequency ω-P and voltage E-Q. However, the problem with using this method is that the reactive power is not properly distributed (in proportion to the capacity of the micronutrients) between the micronutrients, which may lead to overload in the converters. Microgrids may also suffer from dynamic stability problems such as power fluctuations, which can be increased by switching between active and reactive power Control. To avoid this problem, the X / R ratio of transmission lines is an important parameter that should be carefully considered in the design of micronutrient Controllers. By linearizing and simplifying conditions, the Control system conversion function model becomes a single input-single output system, which is efficient enough to show the relationship between Control parameters such as slope of droop characteristics and derivative sentences, virtual impedance, and voltage Controllers. Using this model, stability conditions for different parameters are analyzed. Also, to improve power distribution stability, common droop strategies are modified by adjusting the slope as well as adding nonlinear sentence sections. This approach reduces the coupling between active and reactive power Control and reduces the dependence of power distribution on grid parameters such as the X / R ratio. To evaluate the reliability of the proposed model, the simulation results in a sample island microgrid in MATLAB software are presented.

One of the issues of reliable performance in the power grid is the existence of electromechanical oscillations between interconnected generators. The number of generators participating in each electromechanical oscillation mode and the frequency oscillation depends on the structure and function of the power grid. In this paper, to improve the transient nature of the network and damping electromechanical fluctuations, a decentralized robust adaptive Control method based on dynamic programming has been used to design a stabilizing power system and a complementary static var compensator (SVC) Controller. By applying a single line to ground fault in the network, the robustness of the designed Control systems is demonstrated. Also, the simulation results of the method used in this paper are compared with Controllers whose parameters are adjusted using the PSO algorithm. The simulation results show the superiority of the decentralized robust adaptive Control method based on dynamic programming for the stabilizing design of the power system and the complementary SVC Controller. The performance of the Control method is tested using the IEEE 16-machine, 68-bus, 5-area is verified with time domain simulation.

Non-cooperative intelligent Control agents (ICAs) with dedicated cost functions, can lead the system to poor performance and in some cases, closed-loop instability. A robust solution to this challenge is to place the ICAs at the feedback Nash equilibrium point (FNEP) of the differential game between them. This paper introduces the designation of a robust decentralized infinite horizon LQR Control system based on the FNEP for a linear time-invariant system. For this purpose, two Control strategies are defined. The first one is a centralized infinite horizon LQR (CIHLQR) problem (i.e. a supervisory problem), and the second one is a decentralized Control problem (i.e. an infinite horizon linear-quadratic differential game). Then, while examining the optimal solution of each of the above strategies on the performance of the other, the necessary and sufficient conditions for the equivalence of the two problems are presented. In the absence of the conditions, by using the least-squares error criterion, an approximated CIHLQR Controller is presented. It is shown that the theorems could be extended from a two-agent Control system to a multi-agent system. Finally, the results are evaluated using the simulation results of a Two-Area non-reheat power system.