This paper studies power management in a grid-tied hybrid Energy system consisting of photovoltaic array, wind turbine, fuel cell, electrolyzer, hydrogen storage tank and a combinational heating system to supply the thermal and electrical demand of a building. Moreover, the hybrid system is capable of exchanging power with local grid. Thus, variable daily buying and selling tariffs are also taken into account so as to cover a wide range of operational conditions. The thermal demand is supplied by both electric heating system and the fuel cell exhaust heat. The paper formulates the matter in the form of a nonlinear constrained optimization problem and then evaluates several well-known heuristic optimization techniques. The performance of each of these algorithms is discussed in detail and the elite algorithm is introduced. Furthermore, the effect of the initial charge of the hydrogen storage tank on total operation cost and also charge remained are fully discussed. In order to fulfill this intention, a novel criterion is presented to determine the optimal initial charge. The validation of the results will be implemented based on simulations.

The increasing use of wind resources has led to new challenges in transmission network expansion planning (TNEP). Wind curtailment due to improper expansion of transmission lines prevents the optimal use of these renewable resources. In addition, the uncertainty of these resources puts expansion decisions at risk. In this paper, risk-constrained TNEP in electricity markets in the presence of wind resources is presented with the aim of increasing the utilization of these resources by considering the wind curtailment cost and reducing expected Energy not supplied (EENS). For this purpose, a risk-constrained bi-level stochastic model is used. At the upper level, transmission network expansion decisions are made by the independent system operator (ISO) with the aim of minimizing network investment cost and EENS cost. At the lower level, the market-clearing problems are solved maximizing social welfare. Using duality theory, the bi-level problem is converted into a mixed-integer linear programming (MILP) problem. The proposed framework is analyzed using Garver’s six-bus test system and the IEEE 24-bus reliability test system (RTS). The simulation results indicate that considering wind curtailment cost has increased the use of wind units and reduced the expected Energy produced by fossil units, which is important from an environmental point of view. However, considering the risk, due to the uncertainty of wind resources, the Energy produced by these resources has decreased.

Background and Objectives: Distributed generations (DGs) based on renewable Energy, such as PV units, are becoming more prevalent in distribution networks due to technical and environmental benefits. However, the intermittency and uncertainty of these sources lead to technical and operational challenges. Energy storage application, uncertainty analysis, and network reconfiguration are apt therapies to resist these challenges. Methods: Energy management of modern, smart, and renewable-penetrated distribution networks is tailored here considering the uncertainties correlations. Network operation costs including switching operations, the expected Energy not served (EENS) index as the reliability objective, and the node voltage deviation suppression as the technical objective are mathematically modeled. Multi-objective particle swarm optimization (MOPSO) is considered as the optimization engine. Scenario generation method and Nataf transformation are used in probabilistic evaluations of the problem. Moreover, the technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) is deployed to make a final balance between different objectives to yield a unified solution.Results: To show the effectiveness of the proposed approach, the IEEE 33-node distribution network is put under extensive simulations. Different cases are simulated and interrogated to assess the performance of the proposed model.Conclusion: For different objectives dealing with different aspects of the network, remarkable achievements are attained. In brief, the final solution shows 4.50% decrease in operation cost, 13.07% improvement in reliability index, and 18.85% reduction in voltage deviation compared to the initial conditions.

This research focuses on the effect of passive methods in the field of Energy storage, produce Energy by using renewable energies, and also to achieve the construction patterns of residential buildings in the climate conditions of Shiraz, with the aim reducing Energy consumption. Statistics show that in Iran, fuel consumption in residential and commercial buildings with an average annual growth of 7. It is about 2.37% of the country's total fuel consumption. One way to minimize Energy consumption in this sector is to increase the role of zero-Energy buildings. Zero-Energy buildings provide technical ways to consume less Energy in buildings. These buildings are designed and built so that all or a large part of these provide the Energy they need through the combination of Energy saving and the use of renewable Energy technology. In this research, after studying the climate condition of the city of Shiraz, a building in the Energy Plus software, the simulation and climatic data of the Shiraz station was introduced to the software. To achieve the most optimal conditions of Energy consumption in the climatic conditions of Shiraz, each of the building elements Residential was optimized. The simulation shows that it is possible to reduce the Energy consumption of the building by using passive building materials and designs, including double-glazed glass, Wall insulation, etc. On the other hand, by using solar Energy, using pvsyst software, you can supply the Energy needed by the building.

Cooperative sector is mentioned as one of the sectors of the economy in the Article 44 of the constitution of the Islamic Republic of Iran. Accordingly, many cooperatives are formed and operated in the country. However, cooperatives are faced with problems, some of which date back to the internal structure of the company. So the world today is witnessing the development of new types of cooperatives that are trying to solve some problems through changing their structure. Investor-Share Cooperation is one of the new models of this type. This thesis focuses on the issue that, how a cooperative can offer its shares in the stock market, but still adheres to cooperative principles. For doing this, we describe and analyze some different new models and we use the results to design the model. Our model has three important components: take holders, the rights and preferred stock. Members and investors (take holders) have one same voting right and they contribute to the ultimate benefit of its profitable activities. The share of this company will publish in market and the shareholders of the company are joint owners. According to the new legal relationship, "pseudo investor-share cooperation" for the company is more favorable. At the end, we checked out the model with Shi’a jurisprudence and in conclusion the application of this model was known permissible in Sharia.

In this article, an attempt has been made to estimate the amount of sound transmission loss in a flat oval channel by applying the approach of statistical Energy analysis. Correct estimation of sound transmission loss in an air conditioning channel is of great importance due to the harmful effects of noise pollution in the environment on human health. Simulation with the statistical Energy analysis method is a powerful approach to estimate sound and vibration in problems in which we deal with complex and multi-part systems; is considered. In this method, first, a system is divided into several subsystems, and then by writing a matrix equation that includes the Energy exchanges between subsystems and Energy loss coefficients; It is investigated from the perspective of vibration and sound estimation.On average, the model presented in this research is able to estimate the sound transmission loss in different dimensions of the air conditioning channels according to the experimental results in the accuracy range of ± 2.5 dB. Considering that it seems that the results obtained from modeling with this method are in good agreement with the experimental data; The results of this research can be used as an efficient approach to estimate noise in oval shaped channels stretched in different lengths.

Due to the increasing load growth and expansion and significant changes in structure of electricity distribution networks, the issues related to the optimization of these networks face many challenges. Optimal placement and capacity of Distribution substations and their feeder networks are among the important issues of optimization of distribution networks from technical and economic viewpoints. In this paper, considering two important factors including loss reduction and improvement of reliability in distribution networks, a new multi-objective function was presented for optimal placement of location and capacity of Distribution substations based on their service area. The proposed objective function includes all construction and operation costs of equipment, loss costs, and reliability index (Energy Not supplied). The Artificial Bee Colony (ABC) algorithm was applied to optimize the proposed objective function with the purpose of determining the optimal placement and capacity of substations of two sample distribution networks. A comparison of results obtained from optimization of the proposed objective function by the Artificial Bee Colony (ABC) algorithm with results of other algorithms in two sample networks indicates the efficiency and effectiveness of the proposed algorithm and objective function.