Scenario-Based Multi-Objective Optimisation for Rural Electrification Under Carbon, Economic, and Equity Constraints
炭素、経済、公平性の制約下における農村電化のためのシナリオに基づく多目的最適化 (AI 翻訳)
D. Ighravwe, O. Babatunde, O. Olanrewaju, E. Adetiba
🤖 gxceed AI 要約
日本語
本論文は、サブサハラアフリカの農村電化における炭素排出削減、経済性、公平なエネルギーアクセスのトリレンマを解決する多目的最適化フレームワークを開発した。ナイジェリアの農村共同体を対象に、太陽光、発電機、薪、LPGの4つのエネルギー源を3つの人口グループに配分するモデルを構築し、炭素価格、補助金、マイクロファイナンスなどの政策シナリオを分析。炭素価格が8ドル/トン未満ではシステム最適化が誘発されず、補助金シナリオで最大のエネルギー供給が達成される一方、公平性と効率性のトレードオフが示された。
English
This paper develops a multi-objective optimization framework for rural electrification in Sub-Saharan Africa, addressing the trilemma of carbon emissions, economic viability, and equitable energy access. Using a case study in Nigeria with 7,000 people, the model allocates energy from solar, generator, firewood, and LPG to men, women, and children. Six policy scenarios are analyzed, revealing that carbon prices below $8/ton fail to induce optimal system reconfiguration, and government subsidies maximize energy supply but exacerbate equity-efficiency trade-offs. The framework integrates carbon finance and health benefits to unlock sustainable energy access.
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
本論文はナイジェリアを対象とするが、日本のGX政策（特に途上国向け支援やJCM）への示唆を含む。炭素価格の閾値分析や公平性の定量化手法は、日本企業がアフリカなどで行う電化プロジェクトの設計に応用可能。
In the global GX context
This paper contributes to global GX scholarship by providing a quantitative framework for integrating carbon finance, health co-benefits, and equity into energy planning. The findings on carbon price thresholds and subsidy effects are relevant for developing countries' NDCs and for international climate finance mechanisms such as the Green Climate Fund.
👥 読者別の含意
🔬研究者:The multi-objective optimization methodology and hybrid NSGA-PSO algorithm offer a template for energy planning studies incorporating carbon and equity constraints.
🏢実務担当者:Energy project developers can use the framework to evaluate trade-offs between carbon revenue, cost, and equitable access when designing off-grid solutions.
🏛政策担当者:The analysis of carbon price thresholds and subsidy impacts provides evidence for designing carbon pricing and energy access policies in developing countries.
📄 Abstract（原文）
Rural electrification in Sub-Saharan Africa faces a trilemma: cutting carbon emissions, making it economically viable, and achieving fair access to energy for all. This paper develops a multi-objective framework that optimises carbon revenue, net present value (NPV), total energy supply, cooking fuel (firewood and LPG), health costs, and benefit to society. The model uses continuous decision variables: daily energy allocation among four sources (solar, generator, firewood, LPG) to three population groups (men, women, children). The case study is a rural community of 7000 people in Nigeria (Tier 1 energy consumers). Six policy scenarios are considered: baseline, high carbon price, low carbon price, microfinance, government subsidy and community cooperative. This study compared algorithms and identified a hybrid Non-dominated Sorting Genetic Algorithm and Particle Swarm Optimisation II as the most suitable algorithm for solving the formulated optimisation problem. It was found that NPV and unit cost of energy would increase to $175,500 and 26.4 ¢/kWh, respectively, by increasing the price of carbon from $8/ton to $12/ton. Firewood generates health savings and carbon revenue in the range of $4100–$12,270/year. Prices below $8/ton do not induce optimal reconfigurations in the system. The best energy supply (2825 kWh/day) and the lowest unsatisfied demand occur in the government subsidy scenario with the greatest disparity index, displaying an equity-efficiency trade-off. The framework shows that sustainable access to energy can be unlocked using strategic integration of carbon finance, valuation of health benefits and equity constraints.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.3390/en19122922first seen 2026-07-04 05:19:13
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