Optimal allocation of a cross-connection and sectionalizers in distribution systems

In this paper, the placement of sectionalizers, as well as, a cross-connection is optimally determined so that the objective function is minimized. The objective function employed in this paper consists of two main parts, the switch cost and the reliability cost. The switch cost is composed of the cost of sectionalizers and cross-connection and the reliability cost is assumed to be proportional to a reliability index, SAIDI. To optimize the allocation of sectionalizers and cross-connection problem realistically, the cost related to each element is considered as discrete. In consequence of binary variables for the availability of sectionalizers, the problem is extremely discrete. Therefore, the probability of local minimum risk is high and a heuristic-based optimization method is needed. A Discrete Particle Swarm Optimization (DPSO) is employed in this paper to deal with this discrete problem. Finally, a testing distribution system is used to validate the proposed method.

Variations in MIMO-OFDM channel capacity due to random human movement in an indoor environment

Channel measurements and simulations have been carried out to observe the effects of pedestrian movement on multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) channel capacity. An in-house built MIMO-OFDM packet transmission demonstrator equipped with four transmitters and four receivers has been utilized to perform channel measurements at 5.2 GHz. Variations in the channel capacity dynamic range have been analysed for 1 to 10 pedestrians and different antenna arrays (2 × 2, 3 × 3 and 4 × 4). Results show a predicted 5.5 bits/s/Hz and a measured 1.5 bits/s/Hz increment in the capacity dynamic range with the number of pedestrian and the number of antennas in the transmitter and receiver array.

Optimal allocation and sizing of capacitors to minimize the transmission line loss and to improve the voltage profile

To allocate and size capacitors in a distribution system, an optimization algorithm, called Discrete Particle Swarm Optimization (DPSO), is employed in this paper. The objective is to minimize the transmission line loss cost plus capacitors cost. During the optimization procedure, the bus voltage, the feeder current and the reactive power flowing back to the source side should be maintained within standard levels. To validate the proposed method, the semi-urban distribution system that is connected to bus 2 of the Roy Billinton Test System (RBTS) is used. This 37-bus distribution system has 22 loads being located in the secondary side of a distribution substation (33/11 kV). Reducing the transmission line loss in a standard system, in which the transmission line loss consists of only about 6.6 percent of total power, the capabilities of the proposed technique are seen to be validated.

Random Indexing K-tree

Random Indexing K-tree is the combination of two algorithms suited for large scale document clustering.

Fundamental solution and discrete random walk model for time-space fractional diffusion equation

In this paper, we consider a time-space fractional diffusion equation of distributed order (TSFDEDO). The TSFDEDO is obtained from the standard advection-dispersion equation by replacing the first-order time derivative by the Caputo fractional derivative of order α∈(0,1], the first-order and second-order space derivatives by the Riesz fractional derivatives of orders β 1∈(0,1) and β 2∈(1,2], respectively. We derive the fundamental solution for the TSFDEDO with an initial condition (TSFDEDO-IC). The fundamental solution can be interpreted as a spatial probability density function evolving in time. We also investigate a discrete random walk model based on an explicit finite difference approximation for the TSFDEDO-IC.

Optimal allocation and sizing of DGs in distribution networks

In this paper, the placement and sizing of Distributed Generators (DG) in distribution networks are determined optimally. The objective is to minimize the loss and to improve the reliability. The constraints are the bus voltage, feeder current and the reactive power flowing back to the source side. The placement and size of DGs are optimized using a combination of Discrete Particle Swarm Optimization (DPSO) and Genetic Algorithm (GA). This increases the diversity of the optimizing variables in DPSO not to be stuck in the local minima. To evaluate the proposed algorithm, the semi-urban 37-bus distribution system connected at bus 2 of the Roy Billinton Test System (RBTS), which is located at the secondary side of a 33/11 kV distribution substation, is used. The results finally illustrate the efficiency of the proposed method.

Portfolio size effect in retirement accounts : what does it imply for lifecycle asset allocation funds?

Lifecycle funds offered by retirement plan providers allocate aggressively to risky asset classes when the employee participants are young, gradually switching to more conservative asset classes as they grow older and approach retirement. This approach focuses on maximizing growth of the accumulation fund in the initial years and preserving its value in the later years. The authors simulate terminal wealth outcomes based on conventional lifecycle asset allocation rules as well as on contrarian strategies that reverse the direction of asset switching. The evidence suggests that the growth in portfolio size over time significantly impacts the asset allocation decision. Due to the portfolio size effect that is observed by the authors, the terminal value of accumulation in retirement accounts is influenced more by the asset allocation strategy adopted in later years relative to that adopted in early years. By mechanistically switching to conservative assets in the later years of a plan, lifecycle strategies sacrifice significant growth opportunity and prove counterproductive to the participant's wealth accumulation objective. The authors' conclude that this sacrifice does not seem to be compensated adequately in terms of reducing the risk of potentially adverse outcomes.

Optimal allocation and sizing of DGs in a distribution system using PSO

In this paper, the optimal allocation and sizing of distributed generators (DGs) in a distribution system is studied. To achieve this goal, an optimization problem should be solved in which the main objective is to minimize the DGs cost and to maximise the reliability simultaneously. The active power balance between loads and DGs during the isolation time is used as a constraint. Another point considered in this process is the load shedding. It means that if the summation of DGs active power in a zone, isolated by the sectionalizers because of a fault, is less than the total active power of loads located in that zone, the program start shedding the loads in one-by-one using the priority rule still the active power balance is satisfied. This assumption decreases the reliability index, SAIDI, compared with the case loads in a zone are shed when total DGs power is less than the total load power. To validate the proposed method, a 17-bus distribution system is employed and the results are analysed.