Distribution of distribution networks, which is done with a set of switches, is a simple and low-cost method that reduces the losses of the distribution system. In this paper, first, a genetic algorithm is proposed to optimize distribution network problems. Then, a new More
Distribution of distribution networks, which is done with a set of switches, is a simple and low-cost method that reduces the losses of the distribution system. In this paper, first, a genetic algorithm is proposed to optimize distribution network problems. Then, a new method has been proposed to rearrange the distribution networks in order to reduce losses using a genetic algorithm. This method introduces a combination of rearrangement, genetic algorithm and system automation, which is the main factor in reducing distribution network losses, which can be applied for rearrangement at several load levels as well as real-time load; Then, the use of modern equipment and the use of automation of the switching system are explained, and at the end, how to reduce costs and feedback on consumption costs is also explained. The efficiency of this method with a well-known standard distribution system is also shown.
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In this paper, an approach is proposed for optimum placement and sizing of distributed generation (DG) and battery energy storage system (BESS) in distribution networks. The objective functions in this paper are includes voltage profile improvement of network busses, lo More
In this paper, an approach is proposed for optimum placement and sizing of distributed generation (DG) and battery energy storage system (BESS) in distribution networks. The objective functions in this paper are includes voltage profile improvement of network busses, loss reduction of distribution system, and minimization of installing and operation costs of both DG and BESS. In this paper, the fuel cell-Combined heat and power (CHP) technology is used as DG and nickel/cadmium (Ni/Cd) batteries is used as BESS. It also in this paper are used genetic algorithm (GA) as a means to solve the optimization problem, IEEE 33-bus radial distribution network as test system and Forward/backward sweep technique as load flow method.
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One of the major challenges in the world is the need for energy resources due to its increasing demand and this demand is constantly increasing. In this regard, this paper presents a new method to determine the optimal location and size of energy storage in the micro gr More
One of the major challenges in the world is the need for energy resources due to its increasing demand and this demand is constantly increasing. In this regard, this paper presents a new method to determine the optimal location and size of energy storage in the micro grid by considering discrete models such as power supply and battery charge and discharge to meet technical objectives such as loss reduction and economic objectives. Battery investment and maintenance costs are provided. Based on the results, it can be stated that the batteries will continue to charge and discharge according to the target function selected for their installation and capacity determination.
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Capacitor placement at the substation is one of the effective methods for loss reduction and efficiency increasing of the power systems. In this paper, a novel method for capacitor placement on the secondary side of the distribution transformers is carried out. The math More
Capacitor placement at the substation is one of the effective methods for loss reduction and efficiency increasing of the power systems. In this paper, a novel method for capacitor placement on the secondary side of the distribution transformers is carried out. The mathematical method of Mixed–Integer Linear Programming (MILP) algorithm is used for paper goal to increase the Net Present Value (NPV), resulting from the loss reduction. Due to the variability of the loads, a special template is used for loads modelling. Not only the constant loads, but also three types of industrial, residential and commercial loads are assessed with the proposed method. Then, the results are discussed in order to re-grade loads. Also, the proposed method are compared with two methods as Particle Swarm Optimization (PSO) algorithm and Teaching–Learning Based Optimization (TLBO) algorithm. All of the tests are simulated with MATLAB software and total time of problem is considered as ten years.
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Power system engineers are forced to place more emphasis on reducing losses at the distribution level. From an economic perspective, Joint network reconfiguration and capacitor placement is one of the best ways to save energy. Application of heuristic technique is unavo More
Power system engineers are forced to place more emphasis on reducing losses at the distribution level. From an economic perspective, Joint network reconfiguration and capacitor placement is one of the best ways to save energy. Application of heuristic technique is unavoidable, because of expansion of distribution networks and becoming more complex connections in these grids. In view of this, for the first this paper investigates the ability of Bacterial Foraging Algorithm (BFA) for Joint network reconfiguration and capacitor placement.
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