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系統連系型太陽光発電システムにおける時間別動的排出係数と電力市場価格の統合最適化：販売割当量と脱炭素シナリオ下での感度分析

Hourly Dynamic Emission Factors and Integrated Optimization of Electricity Market Prices in Grid-Connected Photovoltaic Systems: Sensitivity Analysis Under Sales Quotas and Decarbonization Scenarios (原題)

Gizem Nur Bulanık Durmuş

Mathematics📚 査読済 / ジャーナル2026-09-02#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: 10.3390/math14173151
原典: https://doi.org/10.3390/math14173151

🤖 gxceed AI 要約

日本語

本研究は、系統連系型太陽光発電(PV)システムにおいて、時間別の電力市場価格と動的排出係数(DEF)を考慮した単一レベル最適化モデルを開発。売電収入と炭素クレジットを最大化し、販売割当量制約下で最適な時間別売電計画を決定する。ベースラインでは、売電割当60%、炭素クレジット価格15 USD/tCO2で、8062 MWhの出力抑制が発生し、売電収入100万USD、炭素クレジット8.1万USDを得た。感度分析により、DEFがPVシステムの経済・環境性能に重要な影響を与えることを示した。

English

This study develops a single-level optimization model for grid-connected PV systems that integrates hourly electricity market prices and dynamic emission factors (DEF). It maximizes revenue from electricity sales and carbon credits under a sales quota constraint. In the baseline scenario (60% sales quota, $15/tCO2), 8062 MWh was curtailed, yielding $1,007,770 in sales revenue and $81,460 in carbon credits. Sensitivity analyses reveal DEF's critical role in economic and environmental performance under various quotas, carbon prices, and grid decarbonization scenarios aligned with Türkiye's 2053 net-zero target.

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

日本のFIT制度終了後のPV事業では、市場連動型の売電戦略が重要となる。本モデルは、時間別の排出係数と市場価格を考慮した最適売電計画を示しており、日本でも再エネの市場統合やカーボンプライシング導入を検討する際の参考になる。

In the global GX context

This paper provides a framework for optimizing PV sales under dynamic emission factors and carbon pricing, relevant to global discussions on grid decarbonization and renewable integration. It offers insights for markets with high renewable penetration and carbon credit mechanisms, complementing TCFD/ISSB-aligned disclosure of avoided emissions.

👥 読者別の含意

🔬研究者:Provides a quantitative model linking dynamic emission factors to PV dispatch optimization, useful for energy systems research.

🏢実務担当者:Offers a decision-support tool for PV plant operators to optimize sales timing and carbon credit revenue.

🏛政策担当者:Highlights the impact of sales quotas and carbon pricing on renewable deployment, informing policy design.

📄 Abstract（原文）

This study develops a single-level energy management optimization model that evaluates hourly electricity market data and hourly dynamic emission factors (DEF) within a grid-connected photovoltaic (PV) system. The model uses hourly PV production data for 2025, hourly market clearing price (MCP) data from the EPİAŞ day-ahead market, and hourly dynamic emission factors. The aim is to maximize total benefit by considering both the revenue from electricity sales and the carbon credits associated with the estimated avoided emissions resulting from PV energy exported to the grid during periods of high grid carbon intensity. To represent real grid operating conditions, a quota constraint for annual energy sales to the grid is defined, and the model is tasked with distributing this quota to the most optimal hours throughout the year. According to the baseline scenario results, where 60% of annual PV production is allowed to be sold to the grid and the carbon credit price is set at USD 15/tCO2, 8062.04 MWh was curtailed due to quota restrictions. As a result of the optimum hourly sales plan, electricity sales revenue of USD 1,007,770.44 and carbon credits of USD 81,460.01 were obtained. The estimated quantity of avoided emissions, calculated according to dynamic emission factors, was 5430.67 tons of CO2. In this study, comprehensive sensitivity analyses were conducted to evaluate the effects of different grid sales quota levels, carbon credit prices, and hourly emission factor reduction scenarios, representing the long-term decarbonization of the grid in line with Türkiye’s 2053 Net Zero Emissions Target. The findings suggest that dynamic emission factors are one of the key elements determining the economic and environmental performance of PV systems under different sales limits, carbon credit prices, and emission reduction scenarios.

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