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...

The improved bacterial foraging algorithmwas applied in this paper to schedule the bus departing interval. Optimal interval can decrease the total operation cost and passengers’ mean waiting time. The principles of colony sensing, chemotactic action, and improved foraging strategy made this algorithm adaptive. Based on adaptive bacteria foraging algorithm ABFA , a model on one bus line in Hohho...

This paper presents a new Hybrid Particle Swarm optimization with Time Varying Acceleration Coefficients (HPSOTVAC) and Bacteria Foraging Algorithm (BFA) namely (PSOTVAC/BFA) base fuzzy stochastic long term approach for determining optimum location and size of Distributed Energy Resources (DERs). The Monte Carlo simulation method is used to model the uncertainties associated with long-term load...

this paper presents a new hybrid particle swarm optimization with time varying acceleration coefficients (hpsotvac) and bacteria foraging algorithm (bfa) namely (psotvac/bfa) base fuzzy stochastic long term approach for determining optimum location and size of distributed energy resources (ders). the monte carlo simulation method is used to model the uncertainties associated with long-term load...

This paper proposes an improved adaptive approach involving Bacterial Foraging Algorithm (BFA) to optimize both the amplitude and phase of the weights of a linear array of antennas for maximum array factor at any desired direction and nulls in specific directions. The Bacteria Foraging Algorithm is made adaptive using principle of adaptive delta modulation. To show the improvement in making the...

This paper presents a new Hybrid Particle Swarm optimization with Time Varying Acceleration Coefficients (HPSOTVAC) and Bacteria Foraging Algorithm (BFA) namely (PSOTVAC/BFA) base fuzzy stochastic long term approach for determining optimum location and size of Distributed Energy Resources (DERs). The Monte Carlo simulation method is used to model the uncertainties associated with long-term load...

This paper presents a bacterial foraging algorithm (BFA) for null steering of linear antenna arrays by controlling only the element amplitudes. The BFA is a new evolutionary computing technique based on the foraging behavior of Escherichia (E.) coli bacteria in human intestine. To show the accuracy and flexibility of the proposed BFA, several examples of Chebyshev array pattern with the imposed...

In this paper, an improved bacterial foraging algorithm (IBFA) is employed to solve economicemission dispatch (EED) problem. Regarding to more interest to renewable energy sources especially wind energy in recent years, it is necessary to use of incorporate wind power plants into EED problem. To consider realistic conditions, EED is included bi-objective of cost and NOx emission. The problems e...