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不確実性を考慮した再生可能エネルギー相互接続マイクログリッドの取引エネルギー管理：柔軟な暗号通貨マイニング負荷を考慮して

Uncertainty-Aware Transactive Energy Management of Renewable Interconnected Microgrids with Flexible Cryptocurrency Mining Loads (原題)

Yarandi HK, Ghobadzadeh M, Hajiaghapour-Moghimi M

Research Squareプレプリント2026-09-01#エネルギー転換経営インパクト: コスト削減対象セクター: power
DOI: 10.21203/rs.3.rs-10569341/v1
原典: https://doi.org/10.21203/rs.3.rs-10569341/v1

🤖 gxceed AI 要約

日本語

再生可能エネルギー比率の高い相互接続マイクログリッドにおいて、柔軟な暗号通貨マイニング負荷（CML）を取引エネルギー市場に統合する不確実性対応の運用フレームワークを提案。確率計画法と情報ギャップ理論を組み合わせ、価格不確実性に対するロバスト性を評価。IEEE 14バス系統でのシミュレーションにより、CMLの柔軟性がシステム利益を最大2.4%向上させ、再生可能エネルギーの出力抑制を緩和することを示した。

English

This paper proposes an uncertainty-aware energy management framework for interconnected microgrids with high renewable penetration, integrating flexible cryptocurrency mining loads (CMLs) into a local transactive energy market. Using stochastic programming and information-gap decision theory, it addresses price and renewable uncertainties. Simulations on a modified IEEE 14-bus system show that flexible CMLs increase total system profit by up to 2.4% and reduce renewable curtailment.

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

日本では再生可能エネルギーの導入拡大に伴い、系統安定化と出力抑制対策が課題。本提案は需要側の柔軟性を活用したマイクログリッド運用の一例であり、今後の分散型エネルギーリソース活用や需給調整市場への示唆を与える。

In the global GX context

Globally, this research contributes to the growing literature on demand-side flexibility and transactive energy markets, which are key for integrating high shares of renewables. The use of cryptocurrency mining as a flexible load is novel and could inform grid operators and market designers on leveraging new types of flexible demand.

👥 読者別の含意

🔬研究者:Provides a novel framework combining IGDT and stochastic programming for microgrid energy management with flexible loads.

🏢実務担当者:Offers insights into how flexible loads like cryptocurrency mining can be integrated into local energy markets to improve profitability and reduce curtailment.

🏛政策担当者:Highlights the potential of demand-side flexibility in renewable-rich grids, which could inform policies on demand response and market design.

📄 Abstract（原文）

<title>Abstract</title> <p>The increasing penetration of renewable energy sources (RESs) and the emergence of flexible loads necessitate advanced operational frameworks for interconnected microgrids (MGs). This paper proposes a tractable uncertainty-aware energy management framework for transactive operation of renewable-dominated interconnected MGs, explicitly incorporating flexible cryptocurrency mining loads (CMLs) within a local transactive energy market (LTEM). In the proposed framework, the upper-level problem maximizes the admissible electricity price uncertainty radius to preserve market profitability. The lower-level problem determines the optimal scheduling of MG resources, including battery energy storage systems (BESSs), thermal energy storage systems (TESSs), and flexible demand-side loads. Uncertainties in renewable generation and electricity prices are addressed using a hybrid approach combining stochastic programming and information-gap decision theory (IGDT). IGDT is employed to characterize robustness against price uncertainty by quantifying the admissible deviation in electricity price forecasts under both risk-averse and risk-seeking strategies. The proposed model captures the flexibility of CMLs as profit-driven dispatchable loads that dynamically adjust their computational demand in response to price signals and renewable generation availability. This flexibility enables load shifting, improving local energy absorption and mitigating renewable curtailment within the LTEM framework. Simulation results based on a modified IEEE 14-bus test system demonstrate that integrating CMLs as flexible load increases total system profit by up to 2.4% compared to a firm CML load. Furthermore, CML integration enhances operational adaptability, improves supply-demand balancing under uncertainty, and increases energy trading volume within the LTEM. Moreover, CMLs exhibit operational behaviors under risk-averse and risk-seeking strategies, enabling greater operational flexibility under uncertainty.</p>

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