Integrated Multi-Scenario OPF-Based Economic Dispatch for Grid-Connected Microgrids Considering Bidirectional Power Flow and Technical Constraints
双方向電力潮流と技術制約を考慮した系統接続マイクログリッドのための統合マルチシナリオOPFベース経済ディスパッチ (AI 翻訳)
Cabana Jimánez, Katherine, Sousa Santos, Vladimir, Cancelo Ferreira, Jonh, García Sánchez, Zaid, Hoyos, fredy
🤖 gxceed AI 要約
日本語
本論文は、系統接続マイクログリッドにおける経済ディスパッチ問題に対して、最適潮流計算（OPF）を基盤とした統合予測型経済ディスパッチ戦略を提案する。ハイブリッド構成と再生可能エネルギーのみの構成を比較し、ハイブリッド構成が最大7.3 MWの損失削減、50 MW以上の予備力増加、そして高需要時には約50 MWの純輸入から純輸出への転換を達成することを示す。提案手法は双方向電力潮流と技術制約を単一の決定論的OPF枠組みに統合し、運用効率と技術的実現可能性の評価を可能にする。
English
This paper proposes an integrated predictive economic dispatch strategy for grid-connected microgrids using Optimal Power Flow (OPF). It compares hybrid and renewable-only configurations across three load scenarios. The hybrid configuration achieves up to 7.3 MW loss reduction, over 50 MW increase in spinning reserve, and a shift from net import to export of about 50 MW under high demand. The framework integrates bidirectional power flow and technical constraints into a single deterministic OPF assessment.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
本論文は、日本の地域分散型エネルギーシステムの最適運用に示唆を与える。日本では再生可能エネルギー導入に伴うマイクログリッドの経済運用が課題であり、本手法は技術的制約を考慮した運用計画の立案に貢献する可能性がある。
In the global GX context
Globally, this paper contributes to the operational optimization of microgrids with high renewable penetration. Its multi-scenario OPF framework provides a deterministic method for ensuring reliability while maximizing economic efficiency, which is valuable for utilities and microgrid operators facing variable generation. The findings on hybrid vs renewable-only configurations inform design choices for grid-connected microgrids.
👥 読者別の含意
🔬研究者:This paper offers a detailed OPF-based optimization framework for microgrid economic dispatch that can be extended or compared with other methods.
🏢実務担当者:Microgrid operators can use the multi-scenario analysis to evaluate trade-offs between hybrid and renewable-only configurations under different load conditions.
📄 Abstract（原文）
Economic dispatch in grid-connected microgrids is challenged by the variability of renewable generation, the uncertainty of demand, and the need to simultaneously satisfy technical and economic constraints under different operating conditions. This study proposes an integrated predictive economic dispatch strategy for power grids with interconnected microgrids, structured as a unified optimization framework. The approach integrates nodal electrical modeling, Optimal Power Flow (OPF)-based optimization, multi-scenario analysis, and post-optimization feasibility verification based on performance indicators within a single decision-support structure. The methodology is applied to a modified 14-node power grid interconnected with a microgrid, where simulations are conducted under three representative load scenarios (100%, 70%, and 40%) and two operational configurations (hybrid and renewable-only), enabling a comprehensive assessment of system behavior. Results show that the hybrid configuration consistently outperforms the renewable-only case, achieving loss reductions of up to 7.3 MW, increases in spinning reserve exceeding 50 MW, and a transition from net power import to export of approximately 50 MW under high demand. Additionally, the microgrid plays an active operational role, dynamically switching between import and export modes based on load levels and the generation mix. The proposed framework enables identification of operationally efficient and technically feasible configurations by incorporating bidirectional power exchange, electrical constraints, and reserve requirements. The main contribution lies in integrating technical, operational, and interaction variables within a single deterministic Optimal Power Flow (OPF)-based assessment scheme to support decision-making in interconnected microgrid-based power grids.
🔗 Provenance — このレコードを発見したソース
- Zenodo https://zenodo.org/records/21216360first seen 2026-07-07 04:16:08
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