Sharif Digital Repository

This paper presents a dynamic multi objective model for distribution network expansion, considering the distributed generators (DGs) and network reinforcements. The proposed model simultaneously optimizes three objective functions namely, total cost, emission cost and technical satisfaction (voltage profile) by finding the optimal schemes of timing, sizing, placement and DG technologies in a long term planning period (dynamic planning). The importance of each objective function can be changed in the interactive steps. The calculation algorithm is based on Chaotic Local Search with Modified Honey Bee Mating Optimization (CLSMHBMO). The effectiveness of the proposed model and the calculation... 

This paper presents a short term multi-objective planning model for Distributed Generators (DGs) deployment in an electrical network. "Total Cost" and "Emission Cost" are two objective functions which have been going to be minimized in this model by finding the optimal schemes of sizing, placement and DG technologies over a short planning period (static planning). The proposed model can be used for a long term planning period (dynamic planning) in order to consider the timing concept. An interactive fuzzy satisfying method based on Chaotic Local Search and Modified Honey Bee Mating Optimization (CLS-MHBMO) is used to choose the final solution. The effectiveness of the proposed model and... 

This paper presents a long-term dynamic multi-objective planning model for distribution network expansion along with distributed energy options. The proposed model optimizes two objectives, namely costs and emissions and determines the optimal schemes of sizing, placement and specially the dynamics (i.e., timing) of investments on distributed generation units and network reinforcements over the planning period. An efficient two-stage heuristic method is proposed to solve the formulated planning problem. The effectiveness of the proposed model is demonstrated by applying it to a distribution network and comparing the simulation results with other methods and models  

This paper presents a long-term dynamic multi-objective model for distributed generation investment. The proposed model optimizes three objectives, namely active losses, costs and environmental emissions and determines the optimal schemes of sizing, sitting of DG units and specially the dynamics of investment over the planning period. The Pareto optimal solutions of the problem are found using a GA algorithm and finally a fuzzy satisfying method is applied to select the optimal solution considering the desires of the planner. The solutions of Pareto optimal front are analyzed to extract general useful information for planners about the appropriate DG technologies and placement schemes. The...