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Dalla complessita alla sostenibilita: un modello basato su agenti per lo sviluppo e la governance delle Comunita Energetiche Rinnovabili

複雑性から持続可能性へ：再生可能エネルギーコミュニティの開発とガバナンスのためのエージェントベースモデル (AI 翻訳)

GIANNI DI LERNIA

IRIS Research product catalog (Sapienza University of Rome)ジャーナル2026-05-15#エネルギー転換Origin: EU
原典: https://hdl.handle.net/11573/1767916

🤖 gxceed AI 要約

日本語

本研究は、再生可能エネルギーコミュニティ（REC）への市民参加を分析するため、エージェントベースモデルを構築しました。個人の意思決定、社会的相互作用、ガバナンスツールを統合し、インセンティブと教育政策の組み合わせが参加率を28-29%から47-48%に、社会的厚生を68%向上させることを示しました。この結果は、RECの成功には経済的インセンティブと教育的介入の統合が不可欠であることを強調しています。

English

This study develops an Agent-Based Model to analyze citizen participation in Renewable Energy Communities (RECs), integrating bounded rationality, social interactions, and governance tools. Simulations show that a synergistic strategy combining incentives and education raises participation from 28-29% to 47-48% and aggregate social welfare by 68%. The findings highlight the necessity of integrated economic and educational policies for successful REC adoption.

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

日本では地域エネルギー自給率向上やカーボンニュートラル達成のため、再生可能エネルギーコミュニティの導入が進められています。本論文は、インセンティブと教育施策の最適な組み合わせが参加率や社会的厚生に与える影響を定量的に示しており、日本の自治体やエネルギー政策担当者にとって有用な示唆を提供します。

In the global GX context

As decentralized energy models gain attention globally, this paper provides a rigorous simulation framework to evaluate policy mixes for Renewable Energy Communities. Its findings on the complementarity of economic incentives and educational efforts are directly relevant to policymakers and practitioners designing community energy schemes, particularly in the context of the energy transition.

👥 読者別の含意

🔬研究者:For researchers in energy policy and complex systems, the ABM framework offers a replicable method to simulate participation dynamics and policy impacts in community energy projects.

🏢実務担当者:Community energy project developers can use the insights on combining incentives with education to design more effective engagement strategies and governance structures.

🏛政策担当者:Policymakers should note that without economic incentives, even high education efforts yield negligible participation, and a synergistic policy mix is critical to trigger collective adoption.

📄 Abstract（原文）

Renewable Energy Communities (RECs) represent a decentralised model of sustainable energy production and consumption, consistent with ESG principles and aimed at improving energy self-sufficiency, reducing environmental impacts and strengthening social cohesion. This study uses an Agent-Based Model (ABM) to analyse citizen participation in RECs, integrating individual decisions influenced by bounded rationality, social interactions and governance tools, together with a technical simulation of photovoltaic energy production. System performance is evaluated using an aggregate utility index that combines economic, environmental, and social benefits. The simulations, implemented in NetLogo, show that in the absence of educational policies (education-effort = 0), incentives of 0.15 generate stable participation rates of 28–29%. A synergistic strategy combining education-effort = 0.4 and incentives = 0.15 increases participation to 47–48%, exceeding the theoretical critical threshold of 42%. Aggregate social welfare (ASW) follows a similar trend, growing from around 0.29 in the baseline scenario to 0.47 in the synergistic scenarios, with an overall increase of around +68%. In the absence of incentives, participation remains negligible (≈0–0.5%) even with high levels of education, highlighting the need for combined governance policies to trigger collective adoption dynamics. These results confirm that the success of RECs depends crucially on the integration of economic incentives, educational interventions and social dynamics, as well as on the technical feasibility of the energy system.

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gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。