| Project/Area Number |
15560252
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
電力工学・電気機器工学
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| Research Institution | Tokyo Metropolitan University |
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Principal Investigator |
YASUDA Keiichiro Tokyo Metropolitan University, Associate Professor, 都市教養学部, 助教授 (30220148)
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| Co-Investigator(Kenkyū-buntansha) |
ISHIGAME Atsushi Osaka Prefecture University, Associate Professor, 大学院・工学研究科, 講師 (60212867)
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| Project Period (FY) |
2003 – 2005
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| Project Status |
Completed (Fiscal Year 2005)
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| Budget Amount *help |
¥3,300,000 (Direct Cost: ¥3,300,000)
Fiscal Year 2005: ¥1,000,000 (Direct Cost: ¥1,000,000)
Fiscal Year 2004: ¥900,000 (Direct Cost: ¥900,000)
Fiscal Year 2003: ¥1,400,000 (Direct Cost: ¥1,400,000)
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| Keywords | Energy Systems / Dispersed Generation / Autonomous Decentralized Control / Systems Optimization / Meta-heuristics / エネルギーシステム工学 / 電力システム工学 |
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| Research Abstract |
1. The Basic Concept and Decentralized AutonomousControl of Super Distributed Energy Systems
New small-scale dispersed generation systems, such as fuel cells and micro gas-turbines have made remarkable advances lately and they will be applied practically in the near future. Although a large number of researches on the introduction of small-scale dispersed generation systems have been carried out, only a small number of small-scale dispersed generation systems are considered in these researches. Therefore, little is known about problems to be solved in case where a large number of small-scale dispersed generation systems are introduced into electric power systems. This study deals with a super distributed energy system that consists of a great number of dispersed generation systems such as fuel cells, micro gas turbines and so on. The behavior of a customer with a dispersed generation system is simulated as the Ising model in statistical mechanics. The necessity of a distribution network
… More
in super distributed energy systems is discussed based on the Ising model. The feasibility of decentralized autonomous control using vicinity information is also investigated on the basis of stability analysis of the Hopfield neural network model.
2. Proximate Optimality Principle Based Tabu Search
An algorithm - Multi Criteria Tabu Search coordinating the intensification and the diversification based on a Proximate Optimality Principle (POP)-, which has several advantages for solving combinatorial optimization problems, is proposed. The proposed algorithm is applied to some traveling salesman problems, which are typical combinatorial optimization problems in order to verify the performance of the proposed algorithm.
3. Adaptive Particle Swarm Optimization
The purpose of this study is to realize the proper transition from global search to local search for any types of optimization problems. Then the activity of swarm is introduced in order to measure the diversity of search. And an adaptive adjustment strategy of own parameters in order to realize proper transitions from global search to local search is proposed. The simulation results indicate that proposed method has higher optimality than conventional method. Less
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