Tariff-Aware and Carbon-Aware Supervisory Energy Management for the Sustainable Operation of a Grid-Connected Photovoltaic–Battery Energy Storage–Electric Vehicle Charging Station: A Dual-Time-Scale Evaluation
グリッド接続型太陽光発電・蓄電池・電気自動車充電ステーションの持続可能な運転のための関税・炭素考慮型監視エネルギー管理：二重時間スケール評価 (AI 翻訳)
Ziyan Li, Yufei Zhou, Zhenhua Miao, Fubao Jin
🤖 gxceed AI 要約
日本語
本研究は、グリッド接続型PV-BESS-EV充電ステーション向けに、関税・炭素強度・ピーク制約・蓄電池利用を考慮したルールベースの監視エネルギー管理システム（RB-SEMS）を開発。二重時間スケール評価により、コスト・炭素排出・ピーク電力を削減し、PV自家消費率を向上させることを実証した。解釈可能なベースライン手法として、コスト・炭素・ピーク・サイクルのトレードオフ分析に貢献。
English
This paper develops a rule-based supervisory energy management system (RB-SEMS) for grid-connected PV-BESS-EV charging stations that coordinates tariff response, carbon-intensity signals, peak constraints, and storage utilization. A dual-time-scale evaluation framework demonstrates cost reduction (e.g., from 623.57 to 564.05 CNY daily), peak grid import reduction, increased PV utilization (from 71.13% to 78.71%), and carbon emission reduction (from 550.29 to 500.42 kg CO2). The RB-SEMS serves as an interpretable baseline for cost-carbon-peak-cycling trade-off analysis.
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PV・EV充電インフラの拡大に伴い、系統負荷を低減しつつ経済性と環境性を両立する運用管理が重要。本手法は、SSBJやTCFDが求めるエネルギー管理の具体的手法として参考になる可能性がある。
In the global GX context
As global grids integrate more renewables and EVs, tariff- and carbon-aware energy management becomes critical. This paper provides a transparent, rule-based framework for balancing cost, carbon emissions, and peak demand, aligning with ISSB and TCFD emphasis on operational decarbonization and risk management.
👥 読者別の含意
🔬研究者:The dual-time-scale evaluation methodology and trade-off analysis framework offer a benchmark for comparing supervisory control strategies.
🏢実務担当者:The RB-SEMS approach can be implemented in existing charging stations to reduce operational costs and carbon footprint without complex optimization.
🏛政策担当者:The results highlight potential for carbon-aware grid tariffs and peak constraints to drive cleaner operation of charging infrastructure.
📄 Abstract（原文）
Grid-connected photovoltaic–battery energy storage–electric vehicle (PV-BESS-EV) charging stations require supervisory energy management that can coordinate tariff response, carbon-intensity signals, peak constraints, storage utilization, and converter-level operability within a transparent evidential framework. This study develops a bounded-reference rule-based supervisory energy management system (RB-SEMS) that preserves lower-level local converter controllers while generating operating modes and saturated reference commands for BESS power, grid exchange, and EV charging limits. A dual-time-scale evaluation framework is established by combining short-time switching/control simulations for dynamic traceability and SOC-sensitive protection with 24 h, 15 min EMS-level energy-balance simulations for cost, carbon, peak, PV utilization, EV service, and storage throughput assessment. Selected daily reference-injection cases are retained as copied-model diagnostic checks rather than as full-day switching-level validation. Under the D4-LSOC condition, RB-SEMS reduces the reported post-startup DC-bus deviation from 46.13 V to 40.60 V and the filtered BESS peak from 269.18 kW to 84.42 kW. In the E1-TOU scenario, E1-TOU-cost reduces daily total cost from 623.57 CNY to 564.05 CNY, lowers peak-period grid import from 183.75 kWh to 126.75 kWh, and increases local PV utilization from 71.13% to 78.71%; E1-PC66 further reduces the maximum 15 min grid import from 77.88 kW to 66.00 kW. Under the prescribed E2-PCC scenario, E2-CP reduces the calculated grid-related CO2 emissions from 550.29 kg to 500.42 kg, whereas the price-only diagnostic increases them to 572.29 kg. Same-metric PV-SC and MILP comparisons, tested-range sensitivity analysis, and a throughput-based degradation proxy clarify that RB-SEMS is an interpretable supervisory baseline for cost–carbon–peak–cycling trade-off analysis rather than a cost-optimal controller or regionally validated proof of carbon reduction.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.3390/su18136534first seen 2026-07-05 05:32:21
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