Abstract
: Distributed Generations (DGs) have a productive capacity of tens of kilowatts to several megawatts, which are used to produce electrical energy at close proximity to consumers, which of the types of DGs can be named solar cells and Photovoltaics (PVs), fuel cells, micro turbines, wind power plants, and etc. If such kinds of power plants are connected to the network in optimal places, they will have several positive effects on the system, such as reducing network losses, improving the voltage profile, and increasing network reliability. The lack of optimal placement of DGs in the network will increase the costs of energy production and losses in transmission lines. Therefore, it is necessary to optimize the location of such DGs in the network so that the number of DGs, installation locations, and their capacity are determined to which the maximum reduction in network losses occurs. Besides, by applying an appropriate objective function, the evolutionary algorithm can find the optimal location of renewable units with respect to the constraints of the issue. In this paper, the Genetic Algorithm (GA) and the Particle Swarm Optimization (PSO) algorithm are used to address the placement of wind and photovoltaic generators simultaneously in two states: With and without considering the effects of greenhouse gas emission. In this regard, first, an analytical method for optimal DG (wind and PV) placement is presented, then, the proposed approach is applied over a real study case, and the simulation carried out using the MATLAB program; hence, the placement problem was solved using GA and PSO and implemented in the IEEE 33-bus radial distribution system. The obtained results were compared and analyzed. The results of the simulation show the improvement of the voltage profile and the reduction of losses in the network.
Highlights
In order to validate the proposed method, simulation has been performed on the IEEE 33-bus network, the results of which are presented
The results of simulation of the optimal Distributed Generations (DGs) location regardless of greenhouse effects are presented in Table 4; and Table 5 shows the results of optimal location of DG units, considering the cost of greenhouse gas emission of units
Researchers in all domains, in addition to ideas for solving a problem, are always looking for an optimal method to find the best answers, In the field of power systems, because of the high level of risk, researchers and network designers are looking for the most optimal response, and that’s because of the configuration of power grids, even at very small dimensions, which are not optimally designed, the service provider will suffer from irreparable losses
Summary
The access of developing countries to a variety of new energy sources is essential to their economic developments; new research shows that there is a direct relationship between the level of development of a country and its energy consumption. Global trend and attention to the operation of Renewable Energy (RE) and the positive environmental impacts has required that organizations and centers in many countries be interested in implementing projects in this field. These activities are necessary and effective, are these actions carried out according to internationally agreed planning and research, or are these projects passively applied? Different from the existing research that assumes a specific MG topology, the authors presented a planning algorithm that jointly specifies the optimal grid topology, namely AC, DC, or hybrid AC/DC, along with the optimal locations and sizes of distributed energy resources, energy storage systems, and AC-DC converters; and in reference [12], Mostafa F.
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