H. Shayeghi; M. Alilou
Abstract
In the last years, microgrids have been introduced for better managing the overall power network. The two-way communication between supplier and consumer sides of a smart microgrid causes to better apply the demand side management methods to this type of system. For this reason, the multi-objective demand ...
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In the last years, microgrids have been introduced for better managing the overall power network. The two-way communication between supplier and consumer sides of a smart microgrid causes to better apply the demand side management methods to this type of system. For this reason, the multi-objective demand side management of a smart microgrid is investigated in this study. The economic and environmental indices of the microgrid are considered as the primary objective functions of the proposed demand side management method. The load variations of the microgrid are improved based on the applied demand response program. The operator of the microgrid can provide the demand of the system using a wind turbine, photovoltaic panel, diesel generator, micro turbine, fuel cell, energy storage system and the upstream network. The stochastic behavior of renewable units is also considered to evaluate the proposed method in a more realistic condition. The combination of the multi-objective ant lion optimization algorithm and the analytical hierarchy process method is utilized to solve the demand side management problem. Numerical results, which are obtained from evaluating the proposed method in a sample microgrid, demonstrate the high efficiency of the proposed demand side management method in improving the economic and environmental indices of the microgrid.
Distribution Systems
M. Alilou; D. Nazarpour; H. Shayeghi
Abstract
The optimal management of distributed generation (DG) enhances the efficiency of the distribution system; On the other hand, increasing the interest of customers in optimizing their consumption improves the performance of DG. This act is called demand side management. In this study, a new method based ...
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The optimal management of distributed generation (DG) enhances the efficiency of the distribution system; On the other hand, increasing the interest of customers in optimizing their consumption improves the performance of DG. This act is called demand side management. In this study, a new method based on the intelligent algorithm is proposed to optimal operate the demand side management in the presence of DG units and demand response. Firstly, the best location and capacity of different technologies of DG are selected by optimizing the technical index including the active and reactive loss and the voltage profile. Secondly, the daily performance of multi-DG and grid is optimized with and without considering the demand response. The economic and environmental indices are optimized in this step. In both steps, the non-dominated sorting firefly algorithm is utilized to multi-objective optimize the objective functions and then the fuzzy decision-making method is used to select the best result from the Pareto optimal solutions. Finally, the proposed method is implemented on the IEEE 33-bus distribution system and actual 101-bus distribution systems in Khoy-Iran. The obtained numerical results indicate the impact of the proposed method on improving the technical, economic and environmental indices of the distribution system.
Distribution Systems
Hossein Shayeghi; Masoud Alilou
Volume 3, Issue 2 , December 2015, , Pages 131-146
Abstract
In this paper, simultaneous placement of distributed generation, capacitor bank and protective devices are utilized to improve the efficiency of the distribution network. The objectives of the problem are reduction of active and reactive power losses, improvement of voltage profile and reliability indices ...
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In this paper, simultaneous placement of distributed generation, capacitor bank and protective devices are utilized to improve the efficiency of the distribution network. The objectives of the problem are reduction of active and reactive power losses, improvement of voltage profile and reliability indices and increasing distribution companies’ profit. The combination of firefly algorithm, particle swarm optimization and analytical hierarchy process is proposed to solve the multi-objective allocation problem. The proposed method is implemented on IEEE 69-bus and also an actual 22-bus distribution systems in Tehran-Iran. Test results approve the effectiveness of the proposed method for improved reliability and network performance of the distribution network.
