Fuzzy multi-objective placement of renewable energy sources in distribution system with objective of loss reduction and reliability improvement using a novel hybrid method

• Published in: Applied soft computing Vol. 77; pp. 761 - 779
• Main Authors: Arabi Nowdeh, S., Davoudkhani, I. Faraji, Hadidian Moghaddam, M.J., Najmi, E. Seifi, Abdelaziz, A.Y., Ahmadi, A., Razavi, S.E., Gandoman, F.H.
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.04.2019
• Subjects: Fuzzy decision making; Loss; Multi-objective hybrid teaching–learning based optimization-Grey Wolf Optimizer; Reliability; Renewable energy; Fuzzy decision making; Multi-objective hybrid teaching–learning based optimization-Grey Wolf Optimizer; Renewable energy; Reliability; Loss
• ISSN: 1568-4946; 1872-9681
• DOI: 10.1016/j.asoc.2019.02.003

One of methods for loss reduction and reliability improvement of radial distribution system is using of renewable energy generation. In this paper, a new optimal placement and sizing of renewable energy sources based on photovoltaic panels (PVs) and wind turbines (WTs) in the distribution network is presented with the objective of loss reduction and reliability improvement based on energy not-supplied (ENS). A multi-objective evolutionary algorithm based on fuzzy decision-making method, called the Multi-Objective Hybrid Teaching–Learning Based Optimization-Grey Wolf Optimizer (MOHTLBOGWO) is proposed to solve the optimization problem. The proposed hybrid method has a high convergence speed and not trapped at all in local optimal. The proposed method is implemented in the form of single-objective and multi-objective on 33 and 69 bus IEEE radial distribution networks. The simulation results clear that the multi-objective optimization is a more precise approach to network utilization taking into account all objective indices than the single objective method. The results show that the proposed method has better convergence speed and less convergence tolerance in achieving to best solution in comparison with TLBO and GWO methods in loss reduction, reliability improvement and increasing the net saving and also in comparison with last studies. Moreover, the results show that dispersion of the size and location of distributed renewable generation leads to a further reduction in losses and a better improvement of the reliability criterion. •MOTLBOGWO is proposed for optimal placement and sizing of PVs and WTs.•The objective function is designed to reduce loss and reliability improvement.•The placement results are compared in single and multi-objective optimization.•The effectiveness of proposed method is verified compared with other algorithms.•PVs and WTs dispersion is caused less loss and more reliability improvement.