<p>Carbon–neutral supercapacitors play an important role in renewable energy investments as environmentally friendly devices that both function as energy storage and aim to reduce carbon footprint. This situation can cause waste of resources and wrong prioritization decisions. In this context, the main problem is that the most important factors affecting the technical investment performance of carbon–neutral supercapacitors have not been determined. To fill this gap, this study proposes an original decision-making model to determine the importance levels of variables affecting the performance of these devices and to present appropriate investment strategies. The proposed model includes the integrated use of Entropy-game-based expert weighting method, Q-learning algorithm, molecular fuzzy intelligence algorithms, Bayesian network-based weighting (BANEW) and ant colony optimization (ACO) techniques. This study contributes to making more accurate and effective technical decisions for sustainable energy investments by filling an important gap in the literature with its original decision model. It is determined that recyclability rate is the most significant factor because it has the highest weight (0.316). On the other side, the best investment choice for carbon–neutral supercapacitors in renewable energy systems is gravity-based energy storage with the greatest fitness value of 4.044.</p>

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Assessing carbon–neutral supercapacitors in renewable energy systems with self-improving agent-based molecular fuzzy intelligent algorithms

  • Oscar Castillo,
  • Hasan Dinçer,
  • Serhat Yüksel,
  • Serkan Eti

摘要

Carbon–neutral supercapacitors play an important role in renewable energy investments as environmentally friendly devices that both function as energy storage and aim to reduce carbon footprint. This situation can cause waste of resources and wrong prioritization decisions. In this context, the main problem is that the most important factors affecting the technical investment performance of carbon–neutral supercapacitors have not been determined. To fill this gap, this study proposes an original decision-making model to determine the importance levels of variables affecting the performance of these devices and to present appropriate investment strategies. The proposed model includes the integrated use of Entropy-game-based expert weighting method, Q-learning algorithm, molecular fuzzy intelligence algorithms, Bayesian network-based weighting (BANEW) and ant colony optimization (ACO) techniques. This study contributes to making more accurate and effective technical decisions for sustainable energy investments by filling an important gap in the literature with its original decision model. It is determined that recyclability rate is the most significant factor because it has the highest weight (0.316). On the other side, the best investment choice for carbon–neutral supercapacitors in renewable energy systems is gravity-based energy storage with the greatest fitness value of 4.044.