Decentralized Voltage Control Model by Linear Approximation of Minimum Voltage Deviation Control in Distribution System

Systems of distributed generation have shown to be a remarkable alternative to a rational use of energy. Nevertheless, the proper functioning of them still manifests a range of challenges, including both the adequate energy dispatch depending on the variability of consumption and the interaction between generators. This paper describes the implementation of an adaptive neurofuzzy system for voltage control, regarding the changes observed in the consumption within the distribution system. The proposed design employs two neurofuzzy systems, one for the plant dynamics identification and the other for control purposes. This focus optimizes the controller using the model achieved through the identification of the plant, whose changes are produced by charge variation; consequently, this process is adaptively performed. The results show the performance of the adaptive neurofuzzy system via statistical analysis.

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Study on System Loss in Distribution Network with DG

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.672-674.1085 ◽

2014 ◽

Vol 672-674 ◽

pp. 1085-1089

Author(s):

Jia Meng ◽

Zai Lin Piao ◽

Feng Zhou

Keyword(s):

Theoretical Analysis ◽

Real Number ◽

Distribution System ◽

Distribution Network ◽

Output Current ◽

Load Current ◽

Radial Distribution System ◽

Operation Optimization ◽

Voltage Deviation ◽

Node Voltage

The access of DG changes the operation and structure of traditional distribution network. This study mainly focused on controlling DG output current to reduce network loss of the system. Select a simple radial distribution system as example for theoretical analysis and derive the expressions of load current and node voltage. Assuming that there exists a real number k between DG output current and load. Then list the network loss and voltage deviation expressions. For the purpose of operation optimization, k can be determined by mathematical calculations. It proves that the method has a certain rationality to be effective in controlling network loss.

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A day-ahead hybrid optimization algorithm for finding the dispatch schedule of VPP in a distribution system

10.48011/sbse.v1i1.2476 ◽

2020 ◽

Author(s):

Seyed Iman Taheri ◽

Lucas Lima Rodrigues ◽

Mauricio B. C. Salles ◽

Alfeu Joãozinho Sguarezi Filho

Keyword(s):

Open Source Software ◽

Optimization Algorithm ◽

Distribution System ◽

Hybrid Optimization ◽

Genetic Optimization ◽

Hybrid Optimization Algorithm ◽

System Operator ◽

Voltage Deviation ◽

Ieee Standard ◽

Load Shape

Distributed renewable generations such as photovoltaic units are electricity generators for installing close to the loads on the distribution system. In this paper, the dispatch function of a non-centralized Virtual Power Plant (VPP) with having a photovoltaic unit in each bus is considered to optimize. This dispatch function is assigned based on the predicted load shape of the next day. A new day-ahead hybrid optimization algorithm is presented to optimize the dispatch function. The proposed algorithm implements a new hybrid combination of Particle Swarm Optimization (PSO) and Genetic Optimization (GA) algorithms simultaneously to benefit both algorithms’ advantages. The objective function is the optimization of the voltage deviation of the VPP. The suggested algorithm is executed on a 13-bus-radial IEEE standard VPP system using MATLAB software coupled with open-source software called Open-DSS. The results show the importance of the proposed algorithm to optimize the voltage deviation of the VPP. The superiority of the proposed algorithm is related to the accuracy and calculation velocity in comparison with the other tested evolutionary algorithms. The Distribution System Operator could map and move towards its full benefits of the increasing integration of DGs with a strategic placement that could keen prosumers on integrating these actions.

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