Distribution State Estimation using Multiple Stages considering Asynchronous Measurement Data by Dependable Parallel Multi-population Global-best Brain Storm Optimization with Differential Evolution Strategies

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  • 非同期計測を考慮した複数時間断面を用いた配電系統状態推定への並列複数集団型GBSODEによるディペンダブルな方式の提案
  • ヒドウキ ケイソク オ コウリョ シタ フクスウジカン ダンメン オ モチイタ ハイデン ケイトウ ジョウタイ スイテイ エ ノ ヘイレツ フクスウ シュウダンガタ GBSODE ニ ヨル ディペンダブル ナ ホウシキ ノ テイアン

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Abstract

<p>This paper proposes distribution state estimation (DSE) using multiple stages considering asynchronous measurement data by dependable parallel multi-population global-best brain storm optimization with differential evolution strategies. In actual distribution systems, measurement data are obtained asynchronously by polling in distribution automation systems. However, conventional DSE methods have not considered the asynchronous measurement data. Therefore, new DSE formulation using multiple stages is proposed in order to consider the asynchronous measurement data. Since actual distribution system equipment causes a nonlinear characteristic of an objective function, evolutionary computation techniques have been applied to DSE problems. Moreover, parallel and distributed processing should be applied to the DSE problems considering penetration of renewable energies. In such a case, appropriate estimation results should be obtained even if various faults of distributed processes occur. Namely, fast and dependable computation is necessary for the DSE problems. The proposed method is verified to be more effective than conventional DSE using a single stage without considering the asynchronous measurement data.</p>

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