基于粒子群矢量搜索融合的射流轨迹识别方法

为解决消防炮射流轨迹识别受到摄像头晃动或背景变化的影响,从而导致定位精度降低的问题,提出了一种将矢量搜索法和粒子群算法相融合的射流轨迹识别方法。结合矢量搜索法和粒子群算法在射流轨迹识别中的特点,给出了融合算法中矢量搜索法和粒子群算法的对应关系、粒子点初始位置设置和适应度值计算方法以及迭代求解流程和射流落水点确定方法。实验结果表明,本方法实现了对消防炮射流轨迹的识别定位,图像背景环境变动对结果影响较小,可实现摄像头晃动或背景变化情况下的射流轨迹查找,轨迹搜索的效率和准确性优于单向搜索等方法。     

Proposal of a cannibalism bug‐based search strategy using genetic algorithms (C‐BUGS) and its application to multiobjective optimization problems

For decision support under a multiobjective environment, it is effective to offer a Pareto optimal solution set with uniform distribution to the decision‐maker. In this paper, a new optimization method for obtaining a Pareto optimal solution set with such uniform distribution is proposed. In order to overcome the difficulty of realizing this goal, the concept of cannibalism is introduced in BUGS (a bug‐based search strategy using genetic algorithms). Introducing the concept of cannibalism achieves the uniform distribution of Pareto optimal solutions. A numerical experiment using typical continuous and discrete multiobjective optimization problems clarifies the usefulness of the proposed method. © 2002 Scripta Technica, Electr Eng Jpn, 139(1): 51–64, 2002; DOI 10.1002/eej.1146     

Allocation of capacitor banks in distribution systems through a modified monkey search optimization technique

This work presents a methodology for the allocation of fixed capacitor banks in electrical power distribution systems by applying a bio-inspired optimization technique. The goal is to optimize the distribution network operation over a planning horizon by minimizing the system losses with minimum cost of investment in capacitors. For this aim to be achieved, this work proposes improvements to the Monkey Search optimization technique to achieve a better representation of the capacitor allocation problem and to increase the computational efficiency. Distribution systems that are widespread in the literature are used to evaluate the proposed methodology.     

An application of reactive tabu search for service restoration in distribution systems and its comparison with the genetic algorithm and parallel simulated annealing

Service restoration in distribution systems can be formulated as a combinatorial optimization problem. It is the problem to determine power sources for each load considering various operational constraints in distribution systems. Up to now, the problem has been dealt with using conventional methods such as the branch and bound method, expert systems, neural networks, and fuzzy reasoning. Recently, modern heuristic methods such as genetic algorithms (GA), simulated annealing (SA), and tabu search (TS) have been attracting notice as efficient methods for solving large combinatorial optimization problems. Moreover, reactive tabu search (RTS) can solve the parameter tuning problem, which is recognized as the essential problem of the TS. Therefore, RTS, GA, and SA can be efficient search methods for service restoration in distribution systems. This paper develops an RTS for service restoration and compares RTS, GA, and PSA (parallel SA) for the problem. The feasibility of the proposed methods is shown and compared on a typical distribution system model with promising results. © 2000 Scripta Technica, Electr Eng Jpn, 133(3): 71–82, 2000     

A multi‐objective optimization model for determining urban energy systems under integrated energy service in a specific area

The integrated energy service system for a specific area is supposed to deliver electric and thermal energy in an integrated manner for the purpose of reducing cost, primary energy consumption, and CO₂ emission. Under an assumption of the service system, this paper develops a multi‐objective optimization model for determining urban energy systems. Considering the various energy system alternatives, such as photovoltaic generations for residential houses and fuel‐cell cogenerations for business and commercial customers, the model determines the share of the energy system alternatives in order to minimize the above three indices. As numerical examples, this paper illustrates trade‐off analyses in the case when the proposed model is applied to a 2 km × 2 km square area in Osaka. Finally, this paper illustrates the role of various energy system alternatives from CO₂ reduction and fossil energy reduction points of view. © 2004 Wiley Periodicals, Inc. Electr Eng Jpn, 147(3): 20–31, 2004; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.10275     

Determination of loss‐minimum configuration with mathematical optimality in a three‐sectionalized three connected distribution feeder network

In a distribution system, in order to enhance the reliability of power supply, the distribution feeder is divided into several sections by installing sectionalizing switches, and then each of the sectionalized sections is connected to a different feeder. For example, one feeder is divided into three sections by two sectionalizing switches, and then each of the divided sections is connected to the other feeder through sectionalizing switch. Since a distribution system with many feeders has many sectionalizing switches, the system configuration is determined by states (opened or closed) of sectionalizing switches. Usually, a power utility tries to obtain distribution loss‐minimum configuration among large numbers of configuration candidates. However, it is very difficult to determine the loss‐minimum configuration such that the mathematical optimality is guaranteed, because it is well known that determination of a distribution system's configuration is to decide whether each sectionalizing switch is opened or closed by solving a combinatorial optimization problem. In this paper, the authors propose a determination method of loss‐minimum configuration by which the mathematical optimality is guaranteed for a three‐sectionalized three‐connected distribution feeder network. A problem to determine the loss‐minimum configuration is formulated as a combinatorial optimization problems with four operational constraints ( feeder capacity, voltage limit, radial structure, and three‐sectionalization). In the proposed method, after picking up all partial configurations satisfied with radial structure constraint by using enumeration method, optimal combination of partial configurations is determined under the other operational constraints by using conventional optimization method. Numerical simulations are carried out for a distribution network model with 140 sectionalizing switches in order to examine the validity of the proposed algorithm in comparison with one of conventional meta‐heuristics (tabu search). © 2009 Wiley Periodicals, Inc. Electr Eng Jpn, 167(1): 56– 65, 2009; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20530