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This paper proposes a hybrid meta-heuristic method of parallel tabu search (PTS) and ordinal optimization (OO) for transmission network expansion planning in power systems. It determines the optimal structure that keeps the balance between generations and loads. The formulation is expressed as a combinatorial optimization problem that is very hard to solve. PTS is one of meta-heuristics that is useful for solving a combinatorial optimization. To speed up computational time of PTS, OO is used to reduce the number of solution candidates in a probabilistic way. The proposed method with OO-TS is successfully applied to a sample system.

High performance normal incidence multilayer optics has been required for water-window wavelengths raging from 2.33 to 4.37 nm, at which soft x-ray microscope can be expected for living cells. Various fabrication studies have been reported with multilayer structures of W/Sc, W/B4C, and so on. However, high reflectance enough to be practically used has not been obtained, because surface roughness, imperfections of interfaces and atomic-scale controllability of layer thickness are technical issues to be solved in these wavelengths. We have developed novel metal oxide multilayers with amorphous titanium oxide and aluminum oxide fabricated by atomic layer deposition technique, which can preferably prevent from making an alloy at the interface. This technique makes it possible to control the film thickness on an atomic scale due to self-limiting adsorption mechanism in surface chemical reactions.

This paper proposes an efficient method for distribution network expansion planning under new environment. The proposed method optimizes the distribution network expansion planning with two-layered tabu search that considers different neighborhood creation. In this paper, a new network expansion planning method is presented to consider distributed generation and the outage cost in distribution systems. The problem formulation may be expressed as a more complicated combinatorial optimization problem. As a result, a new technique is required to solve the problem. This paper proposed a two-layered tabu search that deals with the optimal location of distribution generation at layer 1 and the feeder and substation at layer 2. The technique allows tabu search to handle different types of integer variables. The proposed method is tested in a sample system.

In this paper, dual tabu search is presented for capacitor control in distribution systems. Capacitor control is important in maintaining power quality in distribution systems. The problem formulation of capacitor control may be expressed as a combinatorial optimization problem of capacitor banks. Meta-heuristics is more efficient for solving a combinatorial optimization problem. In particular, tabu search of meta-heuristics is one of the promising meta-heuristics. However, tabu search still has room for improving the solution quality in a large-scale combinatorial optimization problem. This paper proposes a new tabu search that makes use of the dual code for the initial value. For a given initial value, the dual code is considered and a couple of initial values allow the algorithm to evaluate better solutions. The effectiveness of the proposed method is demonstrated in the 32-node and 69-node distribution systems.

This paper proposes a parallel tabu search (PTS) based method for distribution network expansion planning in consideration of distributed generation (DG). It may be expressed as a combinatorial optimization problem that determines the location and capacity of feeders and substations while minimizing the network loss and installation cost. In this paper, DG is considered in the network expansion planning due to the importance in the deregulated distribution network. At the same time, the outage cost is introduced to improve the power quality in distribution systems. As a result, the formulation makes the network expansion planning problem much more complicated. To overcome the problem, this paper applies PTS of meta-heuristics to the distribution network expansion planning so that computational effort is reduced and the diversity of solution candidate is improved to evaluate a better solution. The proposed method is successfully applied to a sample system.