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Energy storage systems have an important effect on increasing the flexibility of power grids and are necessary to achieve the goals of smart grids. So far, many researches have been conducted in the field of optimal utilization of batteries, but most of them have studied the effects of batteries only on the side of the transmission or distribution network. In the present study, the effect of the installation and optimal operation of energy storage systems on both sides of the transmission and distribution network has been investigated. This paper presents a bi-level optimization model for integrated energy management in transmission and distribution smart grids along with demand management issues. Considering that both proposed models are mixed integer linear programming models, it is difficult to solve them by direct methods. Therefore, a method based on the change of variables and KKT equations is presented to solve these problems, and globally optimal solutions to these problems are guaranteed. Several integrated systems that include transmission and distribution networks are considered to evaluate the proposed model and method, and the results show that the proposed model is efficient and shows the positive effect of modeling energy storage systems on both sides of the network. [ABSTRACT FROM AUTHOR]

In today's competitive world, maintaining competitive power of industries is the requirement of remaining in the competition. In the case of small industries, it also needs to think about strategies of making the industries more competitive in order to survive and have successful activity in competition. In many countries, one of the methods that have gained successful experience in increasing competitive power of SMEs is clustering these firms in a frame of “industrial clusters”. Considering the importance of industrial clusters’ role in regional economic development programs, providing the solutions of improving the performance of the clusters was always a concern for researchers and specialists of this field. In this study, the process of product pricing as one of the most important factors which affects the profitability of industrial clusters is discussed by game theory approach. The proposed model focuses on the structural differences between supply chains and industrial clusters where the concept of Stackelberg game and bilevel programming model is used to determine the price of cluster’s products. In order to test the validity of the proposed model, the stone cluster data of Tehran are collected and using MATLAB software they are implemented in propose pricing game. Then, the results of the Stackelberg game between leader and cluster’s Stakeholders is been analysed.