English title

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Demand response (DR) has many beneficiaries in the electricity market. There are independent players who are interested in DR, which include: transmission system owners, distributors, retailers, and aggregators. In this paper DR is introduced as a tradable commodity that can be exchanged between DR buyers and sellers in a pool-based market which is called demand response exchange (DRX). DRX operator (DRXO) collects DR offers and bids from the buyers and sellers. In this paper, a novel approach has been presented for buyers to bid in a DRX market. Also a dynamic approach has been proposed for DR sellers’ participation in DRX market. In the proposed approach, the buyers should forecast their loads and energy market prices. An ARIMA method is used for these forecasts. Then, a dynamic approach is proposed for DR sellers in order to maximize their profits. The proposed scheme is tested using Spain market data. The results show the efficiency and accuracy of the proposed approach.

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This paper proposes a dynamic game approach to distributed energy resource (DER) expansion planning from investors’ viewpoint with incomplete information. An innovative framework is proposed here to encounter different aspects of DER planning. Wind turbines, gas engines and combined heat and power (CHP) are considered as DERs in this study. For reducing the risk of investment, some support schemes are proposed for wind and CHP. Furthermore, strategic uncertainty of rival behavior as one of the uncertainties has been modeled in electricity market using incomplete information game theory. By the proposed model, the dynamic behaviors of DERs investors and the effects of regulatory intervention on expansion planning are analyzed. The proposed model is capable of evaluating the mutual effects of supporting policies on penetration rate of multi-resources simultaneously. The effectiveness of the proposed model is illustrated through implementing on a test system.

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Image segmentation is one of the most important and difficult steps in machine vision problems and achieving the desired results often requires satisfaction of different objectives. One approach to face this situation uses multi-objective fuzzy clustering of pixels in the feature space. This paper proposes a new strategy for search within the family of multi-objective differential evolution algorithms with the purpose of finding optimal partitions of pixels.  Based on this, all of the encoded clusters in the population of one generation are clustered and each centroid of one donor vector is made with centers from a unique cluster. Through the search space dimension is reduced and searching for each centroid focused on the different area of input space while cluster centers of one fuzzy partition preserve separation. The performance of the proposed method is compared with two other multi-objective fuzzy clustering methods to segment a number of images from the Berkeley segmentation database. Visual and quantitative evaluations show that the proposed method has a better match with the ground truths than the other methods.

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In this paper, a simple method for the discretization of planar continuous current sources is presented. First, the planar current distribution is determined by the Fourier and Inverse Hankel Transforms. Then it is discretized for the design of a planar array. The radiation pattern of the array of discrete elements will be quite different from that of the planar continuous current source. Therefore, for the improvement of its radiation characteristics, such as side-lobe level and ripple in the pattern, the iterative method of least squares is used. The desired radiation characteristics of the array, such as​​ the side-lobe level and ripple of pattern, are achieved by an iterative algorithm of the method of least squares together with the array element excitations. Indeed, first, in each iteration, in order to properly adjust the radiation pattern, the values of radiation pattern at the maximum points of the side-lobes and at the maximum and minimum points of the main-lobe, are replaced with the desired values. Then, by sampling of the adjusted radiation pattern, a linear equation system is obtained which by solving this linear equation system by using the method of least squares, the excitation currents of array elements are determined. The proposed method can be used to optimize any array with arbitrary configuration. Several examples of simulations have been presented to verify the efficacy of the proposed method.