This paper presents a multi-objective formulation for optimal siting and sizing of distributed generation (DG) resources in distribution systems in order to minimize the cost of power losses and energy not supplied. The implemented technique is based on a genetic algorithm (GA) and weight method that employed to obtain the best compromise between these costs. Simulation results on 33-bus distri...

this paper presents a multi-objective formulation for optimal siting and sizing of distributed generation (dg) resources in distribution systems in order to minimize the cost of power losses and energy not supplied. the implemented technique is based on a genetic algorithm (ga) and weight method that employed to obtain the best compromise between these costs. simulation results on 33-bus distri...

In the present day power systems, Distributed generation (DG) technologies are becoming more significant due to the increased demand for electrical power. Integration of DG affects the performance of distribution network significantly. DG placement key benefits are power loss reduction and improved voltage profiles which are the objectives in this problem. This paper presents a new efficient te...

Distributed generation (DG) offers several benefits to the electrical system, such as reduction of losses and improvement voltage profile. DG can be maximized when allocation sizing are optimal — a problem known Optimal Sizing Placement Generation (OSPDG). This paper presents new meta-heuristic that associates PSO (Particle Swarm Optimization) with L´evy flights (LF) solve OSPDG, identified in ...

With the emergence of smart grid, distribution network is facing various problems, such as power limitations, voltage uncertainty, and many others. Apart from sector, growth electric vehicles (EVs) leading to a rising demand. These problems can potentially lead blackouts. This paper presents three meta-heuristic techniques: grey wolf optimization (GWO), whale algorithm (WOA), dandelion optimize...

This paper proposes an advanced Pareto-front non-dominated sorting multi-objective particle swarm optimization (Advanced-PFNDMOPSO) method for optimal configuration (placement and sizing) of distributed generation (DG) in the radial distribution system. The distributed generation consists of single and multiple numbers of active power DG, reactive power DG and simultaneous placement of active-r...

Distributed Generations (DGs) are utilized to supply the active and reactive power in the transmission and distribution systems. These types of power sources have many benefits such as power quality enhancement, voltage deviation reduction, power loss reduction, load shedding reduction, reliability improvement, etc. In order to reach the above benefits, the optimal placement and sizing of DG is...

distributed generations (dgs) are utilized to supply the active and reactive power in the transmission and distribution systems. these types of power sources have many benefits such as power quality enhancement, voltage deviation reduction, power loss reduction, load shedding reduction, reliability improvement, etc. in order to reach the above benefits, the optimal placement and sizing of dg is...