Semnan University Press Journal of Modeling in Engineering 2008-4854 14 44 2016 03 20 Dynamic expansion planning of power distribution grids with distributed generation resources using a new two-level optimization algorithm Dynamic expansion planning of power distribution grids with distributed generation resources using a new two-level optimization algorithm 143 157 1758 10.22075/jme.2017.1758 FA Masoud Ahmadigorji Nima Amjady Journal Article 2017 01 28 This paper presents a comprehensive model for dynamic expansion planning of distribution grids (DDGEP) considering distributed generation technologies. The proposed model determines the optimal location, capacity and dynamics (i.e. timing) of DG investment as well as optimal time schedule of reinforcement of distribution feeders. The objective function of this model encompasses both investment and operation costs of distribution grids and DG units along a specified planning horizon. To solve the suggested model, a new two-level solution method composed of Binary Enhanced Imperialist Competition Algorithm (BEICA) and Improved Particle Swarm Optimization (IPSO) is introduced. BEICA optimizes the location, capacity and timing of DG investment and also timing of existing feeders' reinforcement while IPSO optimizes the operation point of distributed generator-integrated distribution system. In order to demonstrate the effectiveness of proposed two-level solution approach (BEICA+IPSO), it is applied on a radial distribution test system and the obtained results are compared with several other solution methods. This paper presents a comprehensive model for dynamic expansion planning of distribution grids (DDGEP) considering distributed generation technologies. The proposed model determines the optimal location, capacity and dynamics (i.e. timing) of DG investment as well as optimal time schedule of reinforcement of distribution feeders. The objective function of this model encompasses both investment and operation costs of distribution grids and DG units along a specified planning horizon. To solve the suggested model, a new two-level solution method composed of Binary Enhanced Imperialist Competition Algorithm (BEICA) and Improved Particle Swarm Optimization (IPSO) is introduced. BEICA optimizes the location, capacity and timing of DG investment and also timing of existing feeders' reinforcement while IPSO optimizes the operation point of distributed generator-integrated distribution system. In order to demonstrate the effectiveness of proposed two-level solution approach (BEICA+IPSO), it is applied on a radial distribution test system and the obtained results are compared with several other solution methods. https://modelling.semnan.ac.ir/article_1758_f0475403a69bcb1df503409cec84132d.pdf