Renewable Energy Focus最新文献_第6页

Location, location, location: optimal placement of new electricity production in the nordic energy system amidst large-scale electrification 位置，位置，位置：在大规模电气化的北欧能源系统中，新电力生产的最佳位置

IF 5.9 Q2 ENERGY & FUELS

Renewable Energy Focus

Pub Date : 2025-09-30 DOI: 10.1016/j.ref.2025.100765

Joel Bertilsson, Lisa Göransson, Filip Johnsson

Renewable electricity generation is expected to play a pivotal role in the global shift toward electrification. However, the inherent variability of renewable energy sources, in addition to factors such as local weather patterns and grid limitations, poses a significant challenge in terms of determining the optimal size and placement of distributed generation units. This study tackles this issue by applying a novel, high-resolution energy systems model that is tailored to the Nordic region. The model is designed to capture with high accuracy local nuances in relation to grid infrastructure, weather patterns, and demand profiles. The model minimizes the total system costs, accounting for both investment and operational expenditures, through the optimal integration of variable renewable energy sources and dispatchable generation units. The findings indicate that the siting of renewable generation is primarily influenced by a combination of a high number of full-load hours and proximity to the electricity demand, with the latter becoming increasingly important under high-demand conditions. Among renewable technologies, solar photovoltaic systems exhibit the strongest correlation with demand center proximity, whereas offshore wind is mainly constrained by a high potential annual production capacity. In addition, assumptions regarding the availability of electricity grid capacity are shown to have a significant impact on the results, with up to 26% of production being relocated when 100 % thermal grid capacity is available, as compared to when 30% of grid capacity is reserved for contingency events.

可再生能源发电预计将在全球向电气化的转变中发挥关键作用。然而，可再生能源的内在可变性，加上当地天气模式和电网限制等因素，在确定分布式发电机组的最佳规模和位置方面构成了重大挑战。本研究通过应用一种为北欧地区量身定制的新颖的高分辨率能源系统模型来解决这个问题。该模型旨在以高精度捕获与电网基础设施、天气模式和需求概况相关的局部细微差别。该模型通过可变可再生能源和可调度发电机组的最佳整合，将投资和运营支出都考虑在内，使系统总成本最小化。研究结果表明，可再生能源发电的选址主要受到满载小时数高和接近电力需求的综合影响，后者在高需求条件下变得越来越重要。在可再生能源技术中，太阳能光伏系统表现出与需求中心接近程度最强的相关性，而海上风能主要受到高潜在年生产能力的限制。此外，关于电网容量可用性的假设对结果有重大影响，当100%的热网容量可用时，高达26%的生产被重新安置，相比之下，当30%的电网容量保留用于应急事件时。

{"title":"Location, location, location: optimal placement of new electricity production in the nordic energy system amidst large-scale electrification","authors":"Joel Bertilsson, Lisa Göransson, Filip Johnsson","doi":"10.1016/j.ref.2025.100765","DOIUrl":"10.1016/j.ref.2025.100765","url":null,"abstract":"<div><div>Renewable electricity generation is expected to play a pivotal role in the global shift toward electrification. However, the inherent variability of renewable energy sources, in addition to factors such as local weather patterns and grid limitations, poses a significant challenge in terms of determining the optimal size and placement of distributed generation units. This study tackles this issue by applying a novel, high-resolution energy systems model that is tailored to the Nordic region. The model is designed to capture with high accuracy local nuances in relation to grid infrastructure, weather patterns, and demand profiles. The model minimizes the total system costs, accounting for both investment and operational expenditures, through the optimal integration of variable renewable energy sources and dispatchable generation units. The findings indicate that the siting of renewable generation is primarily influenced by a combination of a high number of full-load hours and proximity to the electricity demand, with the latter becoming increasingly important under high-demand conditions. Among renewable technologies, solar photovoltaic systems exhibit the strongest correlation with demand center proximity, whereas offshore wind is mainly constrained by a high potential annual production capacity. In addition, assumptions regarding the availability of electricity grid capacity are shown to have a significant impact on the results, with up to 26% of production being relocated when 100 % thermal grid capacity is available, as compared to when 30% of grid capacity is reserved for contingency events.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"56 ","pages":"Article 100765"},"PeriodicalIF":5.9,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145227241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Understanding malaysian homeowners’ intention to adopt photovoltaic systems for EV charging: An integrated theory of planned behaviour and diffusion of innovation approach 了解马来西亚房主采用光伏系统为电动汽车充电的意图：计划行为和创新扩散方法的综合理论

IF 5.9 Q2 ENERGY & FUELS

Renewable Energy Focus

Pub Date : 2025-09-30 DOI: 10.1016/j.ref.2025.100767

Raymond Chew Yuet Mun , Cindy Chuah , Stephen T. Homer

This study investigates the behavioural and innovation-related factors influencing Malaysian homeowners’ intention to adopt photovoltaic (PV) systems for electric vehicle (EV) charging. Despite Malaysia’s push toward sustainability, current policies treat PV and EV technologies in isolation, missing opportunities for integrated, low-carbon solutions. By combining the Theory of Planned Behaviour and Diffusion of Innovation theory, the study examines how attitudes, subjective norms, and perceived behavioural control impact intention, and how these relationships are mediated by relative advantage and compatibility. Data from 197 EV-owning homeowners were analysed using Partial Least Squares Structural Equation Modelling. Results show that attitude and perceived behavioural control significantly influence intention, mediated by relative advantage, while subjective norms had no significant effect. Compatibility influenced intention directly but not as a mediator. The findings contribute to understanding sustainable technology co-adoption in emerging markets, offering practical and policy insights for promoting PV adoption to support EV charging in Malaysia.

本研究调查了影响马来西亚房主采用光伏（PV）系统进行电动汽车（EV）充电意图的行为和创新相关因素。尽管马来西亚在推动可持续发展，但目前的政策将光伏和电动汽车技术孤立对待，错失了综合低碳解决方案的机会。本研究结合计划行为理论和创新扩散理论，探讨了态度、主观规范和感知行为控制对意向的影响，以及相对优势和兼容性如何调节这些关系。使用偏最小二乘结构方程模型分析了197名拥有电动汽车的房主的数据。结果表明，态度和感知行为控制通过相对优势对意向有显著影响，而主观规范对意向无显著影响。相容性直接影响意向，但不作为中介。研究结果有助于理解新兴市场的可持续技术共同采用，为促进光伏采用提供实践和政策见解，以支持马来西亚的电动汽车充电。

{"title":"Understanding malaysian homeowners’ intention to adopt photovoltaic systems for EV charging: An integrated theory of planned behaviour and diffusion of innovation approach","authors":"Raymond Chew Yuet Mun , Cindy Chuah , Stephen T. Homer","doi":"10.1016/j.ref.2025.100767","DOIUrl":"10.1016/j.ref.2025.100767","url":null,"abstract":"<div><div>This study investigates the behavioural and innovation-related factors influencing Malaysian homeowners’ intention to adopt photovoltaic (PV) systems for electric vehicle (EV) charging. Despite Malaysia’s push toward sustainability, current policies treat PV and EV technologies in isolation, missing opportunities for integrated, low-carbon solutions. By combining the Theory of Planned Behaviour and Diffusion of Innovation theory, the study examines how attitudes, subjective norms, and perceived behavioural control impact intention, and how these relationships are mediated by relative advantage and compatibility. Data from 197 EV-owning homeowners were analysed using Partial Least Squares Structural Equation Modelling. Results show that attitude and perceived behavioural control significantly influence intention, mediated by relative advantage, while subjective norms had no significant effect. Compatibility influenced intention directly but not as a mediator. The findings contribute to understanding sustainable technology co-adoption in emerging markets, offering practical and policy insights for promoting PV adoption to support EV charging in Malaysia.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"56 ","pages":"Article 100767"},"PeriodicalIF":5.9,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145227290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

DER flexibility procurement in a centralized ancillary services market: the significance of positive TSO-DSO interaction 集中式辅助服务市场中的DER柔性采购：TSO-DSO正交互的意义

IF 5.9 Q2 ENERGY & FUELS

Renewable Energy Focus

Pub Date : 2025-09-23 DOI: 10.1016/j.ref.2025.100764

Rohit Vijay, Parul Mathuria

The integration of high levels of renewables necessitates the procurement of distributed energy resources (DERs) for flexibility-based services, such as frequency, reactive power provisions, and congestion management, to ensure secure operation at both transmission and distribution levels. However, procuring flexibility-based services from DERs presents challenges due to the interdependencies in service activations between the TSO and DSO. One potential solution is to acquire DER flexibility through a centralized market jointly managed by the TSO and DSO. This presents two key challenges: i) the allocation of DER services cost between TSO and DSO based on their specific objectives; and ii) the quantification of the cross-impact cost. To address these challenges, this manuscript proposes cost allocation by considering the TSO’s objective of global balancing and the DSO’s responsibilities for congestion management and maintaining reactive power provisions. The obtained results show that the cost distribution shifts due to the cross-impact of one system operator’s actions on the other, highlighting the need for coordination, though the total cost of flexibility procurement remains largely unchanged outside peak times. Further, the reactive power provision and distribution system congestion lead to increased cost share for the DSO, despite stable overall procurement costs. This is driven by the DER’s active power adjustments to maintain the Q/P ratio, leading to subsequent opportunity cost for the DSO.

高水平可再生能源的整合需要采购分布式能源（DERs），以实现基于灵活性的服务，如频率、无功供应和拥塞管理，以确保输电和配电层面的安全运行。然而，由于TSO和DSO之间服务激活的相互依赖性，从DERs获取基于灵活性的服务面临挑战。一个可能的解决方案是通过由TSO和DSO共同管理的集中市场来获得DER灵活性。这就提出了两个关键的挑战：i)基于特定目标，在TSO和DSO之间分配DER服务成本；(2)交叉影响成本的量化。为了解决这些挑战，本文建议通过考虑TSO的全局平衡目标和DSO的拥塞管理和维持无功供应的责任来分配成本。得到的结果表明，成本分布的变化是由于一个系统运营商的行为对另一个系统运营商的交叉影响，这突出了协调的必要性，尽管灵活性采购的总成本在高峰时段之外基本保持不变。此外，尽管总体采购成本稳定，但无功供应和配电系统拥塞导致DSO的成本份额增加。这是由DER的有功功率调整驱动的，以保持Q/P比，从而导致DSO的后续机会成本。

{"title":"DER flexibility procurement in a centralized ancillary services market: the significance of positive TSO-DSO interaction","authors":"Rohit Vijay, Parul Mathuria","doi":"10.1016/j.ref.2025.100764","DOIUrl":"10.1016/j.ref.2025.100764","url":null,"abstract":"<div><div>The integration of high levels of renewables necessitates the procurement of distributed energy resources (DERs) for flexibility-based services, such as frequency, reactive power provisions, and congestion management, to ensure secure operation at both transmission and distribution levels. However, procuring flexibility-based services from DERs presents challenges due to the interdependencies in service activations between the TSO and DSO. One potential solution is to acquire DER flexibility through a centralized market jointly managed by the TSO and DSO. This presents two key challenges: i) the allocation of DER services cost between TSO and DSO based on their specific objectives; and ii) the quantification of the cross-impact cost. To address these challenges, this manuscript proposes cost allocation by considering the TSO’s objective of global balancing and the DSO’s responsibilities for congestion management and maintaining reactive power provisions. The obtained results show that the cost distribution shifts due to the cross-impact of one system operator’s actions on the other, highlighting the need for coordination, though the total cost of flexibility procurement remains largely unchanged outside peak times. Further, the reactive power provision and distribution system congestion lead to increased cost share for the DSO, despite stable overall procurement costs. This is driven by the DER’s active power adjustments to maintain the Q/P ratio, leading to subsequent opportunity cost for the DSO.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"56 ","pages":"Article 100764"},"PeriodicalIF":5.9,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145159028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Real-time web inference of a BiLSTM-informer hybrid model for enhanced photovoltaic power output forecasting 基于BiLSTM-informer混合模型的实时网络推理增强光伏发电量预测

IF 5.9 Q2 ENERGY & FUELS

Renewable Energy Focus

Pub Date : 2025-09-23 DOI: 10.1016/j.ref.2025.100763

Kehinde Ridwan Kamil, Umar F. Khan, Ray E. Sheriff, Hafeez Ullah Amin

To ensure an efficient Photovoltaic (PV) renewable energy grid, it is essential to address the uncertainty inherent in power systems. An efficient energy management system must be capable of prioritising energy distribution based on an applicable and effective real-time forecasting of the generation output of the PV system. This study proposes a novel BiLSTM-Informer hybrid model that outperforms benchmarked machine and deep learning approaches in forecasting multi-step PV output by addressing their inability to capture non-linear temporal dependencies and lack of dynamic features weighting. A 39.2 kWp PV system serves as a case study, incorporating location-specific weather parameters. The proposed model integrates Fourier transformation, cyclic encoding, and autoregressive feature optimization to enhance pattern recognition and short-term variability. It achieved superior accuracy, with a mean absolute error (MAE) of 1.22 kWh, a root means square error (RMSE) of 2.21 kWh, and a coefficient of determination (R²) of 0.952. This reflects a 20.1 % increase in online forecasting accuracy. Unlike previous studies, this work integrates real-time web inferencing using a Streamlit interface on Orender, thereby validating the model’s robustness under live deployment. The model demonstrated forecasting accuracy ranging from 89 % to 97.3 % across multiple forecasting (1-hour to monthly) horizons with reduced computational overhead. These results position the BiLSTM-Informer as a novel benchmark for real-time PV forecasting and intelligent power grid management. The data and pre-trained models are available at the dedicated GitHub repository: https://github.com/kamilkenny/EDA and the Inferenced Model link is: https://kamil-deployment-of-edgehill-durning.onrender.com/.

为了确保光伏可再生能源电网的高效运行，必须解决电力系统固有的不确定性问题。一个高效的能源管理系统必须能够根据光伏发电系统发电量的适用和有效的实时预测来优先分配能源。本研究提出了一种新的BiLSTM-Informer混合模型，该模型通过解决无法捕获非线性时间依赖性和缺乏动态特征权重的问题，在预测多步光伏输出方面优于基准机器和深度学习方法。一个39.2 kWp的光伏系统作为案例研究，结合了特定地点的天气参数。该模型集成了傅里叶变换、循环编码和自回归特征优化，以增强模式识别和短期可变性。该方法的平均绝对误差（MAE）为1.22 kWh，均方根误差（RMSE）为2.21 kWh，决定系数（R2）为0.952。这反映了在线预测准确度提高了20.1%。与之前的研究不同，这项工作使用Orender上的Streamlit接口集成了实时web推理，从而验证了模型在实时部署下的鲁棒性。该模型在多个预测（1小时到每月）范围内的预测精度在89%到97.3%之间，并且减少了计算开销。这些结果使BiLSTM-Informer成为实时光伏预测和智能电网管理的新基准。数据和预训练模型可在专用的GitHub存储库中获得：https://github.com/kamilkenny/EDA和推论模型链接是：https://kamil-deployment-of-edgehill-durning.onrender.com/。

{"title":"Real-time web inference of a BiLSTM-informer hybrid model for enhanced photovoltaic power output forecasting","authors":"Kehinde Ridwan Kamil, Umar F. Khan, Ray E. Sheriff, Hafeez Ullah Amin","doi":"10.1016/j.ref.2025.100763","DOIUrl":"10.1016/j.ref.2025.100763","url":null,"abstract":"<div><div>To ensure an efficient Photovoltaic (PV) renewable energy grid, it is essential to address the uncertainty inherent in power systems. An efficient energy management system must be capable of prioritising energy distribution based on an applicable and effective real-time forecasting of the generation output of the PV system. This study proposes a novel BiLSTM-Informer hybrid model that outperforms benchmarked machine and deep learning approaches in forecasting multi-step PV output by addressing their inability to capture non-linear temporal dependencies and lack of dynamic features weighting. A 39.2 kWp PV system serves as a case study, incorporating location-specific weather parameters. The proposed model integrates Fourier transformation, cyclic encoding, and autoregressive feature optimization to enhance pattern recognition and short-term variability. It achieved superior accuracy, with a mean absolute error (MAE) of 1.22 kWh, a root means square error (RMSE) of 2.21 kWh, and a coefficient of determination (R<sup>2</sup>) of 0.952. This reflects a 20.1 % increase in online forecasting accuracy. Unlike previous studies, this work integrates real-time web inferencing using a Streamlit interface on Orender, thereby validating the model’s robustness under live deployment. The model demonstrated forecasting accuracy ranging from 89 % to 97.3 % across multiple forecasting (1-hour to monthly) horizons with reduced computational overhead. These results position the BiLSTM-Informer as a novel benchmark for real-time PV forecasting and intelligent power grid management. The data and pre-trained models are available at the dedicated GitHub repository: <span><span>https://github.com/kamilkenny/EDA</span><svg><path></path></svg></span> and the Inferenced Model link is: <span><span>https://kamil-deployment-of-edgehill-durning.onrender.com/</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"56 ","pages":"Article 100763"},"PeriodicalIF":5.9,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145158269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Hourly energy demand impacts of battery electric vehicle adoption in Italy: A grid simulation and policy analysis 意大利电池电动汽车采用的小时能源需求影响：电网模拟和政策分析

IF 5.9 Q2 ENERGY & FUELS

Renewable Energy Focus

Pub Date : 2025-09-18 DOI: 10.1016/j.ref.2025.100761

Hamid Safarzadeh, Maryam Ebrahimzadeh Sarvestani, Mahdi Enayati, Francesco Di Maria

The growing adoption of Battery Electric Vehicles (BEVs) poses significant challenges to electricity grids, especially in countries aiming for rapid decarbonization. This study evaluates the hourly impact of BEV integration on Italy’s energy system using a Python-based simulation model. Two scenarios are analyzed for 2024: (1) 3.5 million BEVs and (2) 7 million BEVs. The model incorporates hourly charging profiles for household and highway fast-charging, Italy’s renewable energy mix (solar, wind, hydro, bioenergy), and a 5 GWh battery energy storage system. Results show that Scenario 1 increases daily electricity demand by 19 % (to 1.1 TWh), with peak loads of 47–49 GW, requiring 152 GWh of thermal generation and emitting 76,000 tons of CO₂ daily. Scenario 2 raises demand by 40 % (to 1.25 TWh), with peak loads of 50–53 GW, 224 GWh of thermal generation, and 112,000 tons of CO₂ emissions. Existing storage mitigates 20 % of peak load but is insufficient for Scenario 2’s 15 GW shortfall. Key demand spikes occur at 01:00 and 11:00–18:00, coinciding with home and highway charging. Policy strategies such as time-of-use tariffs, expanding storage to 15 GWh, and doubling solar capacity could reduce emissions by up to 35 % and supply 80 % of BEV charging needs during daylight hours. This hourly-resolution analysis offers critical insights for grid planning and supports the EU’s Fit for 55 targets.

电池电动汽车（BEVs）的日益普及对电网构成了重大挑战，特别是在旨在快速脱碳的国家。本研究使用基于python的仿真模型评估BEV集成对意大利能源系统的每小时影响。对2024年的两种情景进行了分析：(1)350万辆纯电动汽车和(2)700万辆纯电动汽车。该模型结合了家庭和高速公路快速充电的每小时充电配置文件，意大利的可再生能源组合（太阳能，风能，水能，生物能源）以及5gwh的电池储能系统。结果表明，情景1每日电力需求增加19%（达到1.1太瓦时），峰值负荷为47-49吉瓦，需要152吉瓦时的火力发电，每天排放76,000吨二氧化碳。方案2将需求提高40%（达到1.25太瓦时），峰值负荷为50-53吉瓦，热发电量为224吉瓦时，二氧化碳排放量为11.2万吨。现有储能可以缓解20%的峰值负荷，但不足以满足方案2的15吉瓦缺口。关键需求高峰出现在01:00和11:00-18:00，与家庭和高速公路收费一致。诸如分时电价、将储能容量扩大到15千兆瓦时以及将太阳能容量翻倍等政策策略可以减少高达35%的排放，并在白天提供80%的纯电动汽车充电需求。这种小时分辨率分析为电网规划提供了关键见解，并支持欧盟的“Fit for 55”目标。

{"title":"Hourly energy demand impacts of battery electric vehicle adoption in Italy: A grid simulation and policy analysis","authors":"Hamid Safarzadeh, Maryam Ebrahimzadeh Sarvestani, Mahdi Enayati, Francesco Di Maria","doi":"10.1016/j.ref.2025.100761","DOIUrl":"10.1016/j.ref.2025.100761","url":null,"abstract":"<div><div>The growing adoption of Battery Electric Vehicles (BEVs) poses significant challenges to electricity grids, especially in countries aiming for rapid decarbonization. This study evaluates the hourly impact of BEV integration on Italy’s energy system using a Python-based simulation model. Two scenarios are analyzed for 2024: (1) 3.5 million BEVs and (2) 7 million BEVs. The model incorporates hourly charging profiles for household and highway fast-charging, Italy’s renewable energy mix (solar, wind, hydro, bioenergy), and a 5 GWh battery energy storage system. Results show that Scenario 1 increases daily electricity demand by 19 % (to 1.1 TWh), with peak loads of 47–49 GW, requiring 152 GWh of thermal generation and emitting 76,000 tons of CO<sub>2</sub> daily. Scenario 2 raises demand by 40 % (to 1.25 TWh), with peak loads of 50–53 GW, 224 GWh of thermal generation, and 112,000 tons of CO<sub>2</sub> emissions. Existing storage mitigates 20 % of peak load but is insufficient for Scenario 2’s 15 GW shortfall. Key demand spikes occur at 01:00 and 11:00–18:00, coinciding with home and highway charging. Policy strategies such as time-of-use tariffs, expanding storage to 15 GWh, and doubling solar capacity could reduce emissions by up to 35 % and supply 80 % of BEV charging needs during daylight hours. This hourly-resolution analysis offers critical insights for grid planning and supports the EU’s Fit for 55 targets.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"56 ","pages":"Article 100761"},"PeriodicalIF":5.9,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145119277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Federated deep MPC-enabled digital twin and multiagent learning framework for secure and scalable smart nano grid energy management 联邦深度mpc支持的数字孪生和多智能体学习框架，用于安全和可扩展的智能纳米电网能源管理

IF 5.9 Q2 ENERGY & FUELS

Renewable Energy Focus

Pub Date : 2025-09-17 DOI: 10.1016/j.ref.2025.100762

Ibrahim Sinneh Sinneh, Sun Yanxia

This study introduces a novel Federated Secure Dynamic Optimization Framework (FSDOF) to improve smart nano grid systems’ energy management, fault tolerance, and cybersecurity. The framework suggested combines Digital Twin (DT) technology and Multiagent Reinforcement Learning (MARL) to assist in real-time decision-making and decentralized control. In essence, FSDOF integrates three major components: Federated Deep Model Predictive Control (FD-MPC) to schedule energy optimally, SecureGraph-FedNet (SG-FedNet) to communicate through Graph Neural Networks and Autoencoders securely, and Dynamic Stochastic Neuro-Evolution Optimizer (DSNEO) to adaptively handle and optimize under uncertainty. The system demonstrated 98.52 % energy efficiency, DC voltage stabilization in 0.5 seconds, and Bit Error Rate (BER) of 0.012, which is better than the traditional DRL methods. SG-FedNet guarantees a security confidence of 0.99 in federated learning with differential privacy. Scalability and resilience of the system were confirmed by large-scale simulations on more than 100 nodes with less than 4 % performance degradation. These findings make FSDOF a scalable and strong solution to next-generation smart energy networks.

本研究提出一种新的联邦安全动态优化框架（FSDOF），以改善智能纳米电网系统的能量管理、容错和网络安全。该框架建议将数字孪生（DT）技术和多智能体强化学习（MARL）相结合，以辅助实时决策和分散控制。从本质上讲，FSDOF集成了三个主要组件：联邦深度模型预测控制（FD-MPC）以优化能源调度，SecureGraph-FedNet （SG-FedNet）通过图神经网络和自编码器安全地通信，动态随机神经进化优化器（DSNEO）在不确定性下自适应处理和优化。该系统节能98.52%，直流稳压时间为0.5秒，误码率为0.012，优于传统的DRL方法。SG-FedNet在差分隐私的联邦学习中保证了0.99的安全置信度。通过在100多个节点上的大规模仿真，验证了系统的可扩展性和弹性，性能下降幅度小于4%。这些发现使FSDOF成为下一代智能能源网络的可扩展且强大的解决方案。

{"title":"Federated deep MPC-enabled digital twin and multiagent learning framework for secure and scalable smart nano grid energy management","authors":"Ibrahim Sinneh Sinneh, Sun Yanxia","doi":"10.1016/j.ref.2025.100762","DOIUrl":"10.1016/j.ref.2025.100762","url":null,"abstract":"<div><div>This study introduces a novel Federated Secure Dynamic Optimization Framework (FSDOF) to improve smart nano grid systems’ energy management, fault tolerance, and cybersecurity. The framework suggested combines Digital Twin (DT) technology and Multiagent Reinforcement Learning (MARL) to assist in real-time decision-making and decentralized control. In essence, FSDOF integrates three major components: Federated Deep Model Predictive Control (FD-MPC) to schedule energy optimally, SecureGraph-FedNet (SG-FedNet) to communicate through Graph Neural Networks and Autoencoders securely, and Dynamic Stochastic Neuro-Evolution Optimizer (DSNEO) to adaptively handle and optimize under uncertainty. The system demonstrated 98.52 % energy efficiency, DC voltage stabilization in 0.5 seconds, and Bit Error Rate (BER) of 0.012, which is better than the traditional DRL methods. SG-FedNet guarantees a security confidence of 0.99 in federated learning with differential privacy. Scalability and resilience of the system were confirmed by large-scale simulations on more than 100 nodes with less than 4 % performance degradation. These findings make FSDOF a scalable and strong solution to next-generation smart energy networks.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"56 ","pages":"Article 100762"},"PeriodicalIF":5.9,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145106263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A bi-Level collaborative optimization strategy for power quality in distribution networks based on fuzzy triple black hole multi-objective optimization algorithm 基于模糊三黑洞多目标优化算法的配电网电能质量双级协同优化策略

IF 5.9 Q2 ENERGY & FUELS

Renewable Energy Focus

Pub Date : 2025-09-16 DOI: 10.1016/j.ref.2025.100760

Xiaohui Yang, Jiajing Xu, Chilv Wu, Lingjun Guo, Zhicong Wang, Rui Zhong, Zekai Tu, Peng Yang

With the large-scale integration of renewable energy units and electric vehicles (EVs) into distribution networks, enhancing the power quality of these networks has emerged as a critical issue requiring immediate attention. Meanwhile, existing solution methods are inadequate for meeting the multi-objective optimization needs of distribution networks. This study establishes a bi-level collaborative optimization strategy for improving power quality in distribution networks. Specifically, the upper planning tier aims to minimize comprehensive costs through multi-component collaborative planning. The lower operational tier, based on the comprehensive performance evaluation decision model (CPEDM), conducts coordinated scheduling of multiple components by considering both economic benefits and power quality indicators. Furthermore, a fuzzy triple black hole multi-objective optimization algorithm (MOFTBH), which boasts high solution quality, uncertainty handling capabilities, and high adaptability, is developed and employed to solve the bi-level collaborative model. The study focuses on the IEEE-33 system as the research subject, leveraging the MOFTBH for analysis. Simulation results indicate that the optimization strategy presented in this study improves economic benefits and power quality by 45.43% and 19.90%, respectively, compared to the case without any optimization. Specifically, indices such as voltage deviation, voltage fluctuation, and harmonic distortion have improved by 39.01% , 127.45% and 113.14% , MOFTBH demonstrates a 30% faster Pareto front convergence rate compared to benchmark algorithms, with a 25% improvement in solution set uniformity. Under equivalent iteration counts, the objective function values show an optimization range of 18.7%–23.4%. This planning model aims to provide intelligent and green strategies for future smart grid construction and facilitate the commercial expansion of distribution network operators.

随着可再生能源机组和电动汽车在配电网中的大规模集成，提高配电网的电能质量已成为一个迫切需要关注的关键问题。同时，现有的求解方法无法满足配电网的多目标优化需求。本研究建立了一种改善配电网电能质量的双层协同优化策略。具体而言，上层规划层旨在通过多组件协同规划使综合成本最小化。下层运行层基于综合性能评价决策模型（CPEDM），综合考虑经济效益和电能质量指标，对多部件进行协调调度。在此基础上，提出了求解质量高、不确定性处理能力强、适应性强的模糊三重黑洞多目标优化算法（MOFTBH），并将其应用于双层协同模型的求解。本研究以IEEE-33系统为研究对象，利用MOFTBH进行分析。仿真结果表明，与未进行优化的情况相比，该优化策略的经济效益和电能质量分别提高了45.43%和19.90%。具体而言，MOFTBH算法的电压偏差、电压波动和谐波失真等指标分别提高了39.01%、127.45%和113.14%，Pareto front收敛速度比基准算法提高了30%，解集均匀性提高了25%。在等效迭代次数下，目标函数值的优化范围为18.7% ~ 23.4%。该规划模型旨在为未来的智能电网建设提供智能化、绿色化的策略，促进配电网运营商的商业扩张。

{"title":"A bi-Level collaborative optimization strategy for power quality in distribution networks based on fuzzy triple black hole multi-objective optimization algorithm","authors":"Xiaohui Yang, Jiajing Xu, Chilv Wu, Lingjun Guo, Zhicong Wang, Rui Zhong, Zekai Tu, Peng Yang","doi":"10.1016/j.ref.2025.100760","DOIUrl":"10.1016/j.ref.2025.100760","url":null,"abstract":"<div><div>With the large-scale integration of renewable energy units and electric vehicles (EVs) into distribution networks, enhancing the power quality of these networks has emerged as a critical issue requiring immediate attention. Meanwhile, existing solution methods are inadequate for meeting the multi-objective optimization needs of distribution networks. This study establishes a bi-level collaborative optimization strategy for improving power quality in distribution networks. Specifically, the upper planning tier aims to minimize comprehensive costs through multi-component collaborative planning. The lower operational tier, based on the comprehensive performance evaluation decision model (CPEDM), conducts coordinated scheduling of multiple components by considering both economic benefits and power quality indicators. Furthermore, a fuzzy triple black hole multi-objective optimization algorithm (MOFTBH), which boasts high solution quality, uncertainty handling capabilities, and high adaptability, is developed and employed to solve the bi-level collaborative model. The study focuses on the IEEE-33 system as the research subject, leveraging the MOFTBH for analysis. Simulation results indicate that the optimization strategy presented in this study improves economic benefits and power quality by 45.43% and 19.90%, respectively, compared to the case without any optimization. Specifically, indices such as voltage deviation, voltage fluctuation, and harmonic distortion have improved by 39.01% , 127.45% and 113.14% , MOFTBH demonstrates a 30% faster Pareto front convergence rate compared to benchmark algorithms, with a 25% improvement in solution set uniformity. Under equivalent iteration counts, the objective function values show an optimization range of 18.7%–23.4%. This planning model aims to provide intelligent and green strategies for future smart grid construction and facilitate the commercial expansion of distribution network operators.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"56 ","pages":"Article 100760"},"PeriodicalIF":5.9,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145106262","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Assessing financial feasibility and equity prospects in agrivoltaics: a case study of Hachinohe, Japan 评估农业发电的财务可行性和公平前景：以日本八县为例

IF 5.9 Q2 ENERGY & FUELS

Renewable Energy Focus

Pub Date : 2025-09-10 DOI: 10.1016/j.ref.2025.100751

Xiao Chen , Vibhas Sukhwani , Bijon Kumer Mitra , Anudari Batsaikhan , Rajib Shaw

Agrivoltaics, which combines the use of land for both agriculture and photovoltaic energy production, is emerging as a promising solution to the land use conflicts between farming and renewable energy. By simultaneously boosting crop yields, enhancing solar panel efficiency and revitalising rural incomes, agrivoltaics is attracting farmers and solar developers, prompting innovation in technology and business models. Nevertheless, the key to scaling agrivoltaics depends on its commercial viability for different stakeholders, an area that still requires further exploration. To bridge this gap, this research examines the business model of an ongoing agrivoltaic project in the Hachinohe region of Aomori Prefecture, Japan, with a particular focus on financial feasibility and equitable distribution of benefits among stakeholders. The study applies multi-criteria decision-making method to assess the project’s overall financial feasibility using NPV, IRR, and payback periods, while also exploring the equity implications through Gini coefficients. Thereafter, a sensitivity analysis is conducted to offer policy suggestions such as revenue-sharing, better lease terms, and subsidies for farmers, with the purpose of enhancing rural economic revitalization and inform equitable business model design in Japan’s energy transition. Drawing on experiences from Europe and the United States, this research emphasizes the active engagement of farm owners in the development and implementation of agrivoltaic projects to enhance financial feasibility, equity and stakeholder participation.

农业发电结合了农业和光伏能源生产的土地使用，正在成为解决农业和可再生能源之间土地使用冲突的一种有希望的解决方案。通过同时提高农作物产量、提高太阳能电池板效率和振兴农村收入，农业发电正在吸引农民和太阳能开发商，推动技术和商业模式的创新。然而，扩大农业发电规模的关键取决于其对不同利益相关者的商业可行性，这一领域仍需要进一步探索。为了弥补这一差距，本研究考察了日本青森县八乡地区正在进行的一个农业光伏项目的商业模式，特别关注财务可行性和利益相关者之间的利益公平分配。本研究采用多准则决策方法，利用净现值、内部收益率和投资回收期对项目的整体财务可行性进行评估，同时通过基尼系数探讨其对股权的影响。在此基础上，通过敏感性分析，提出收益分成、改善租赁条件、补贴农民等政策建议，以期促进日本能源转型中农村经济的振兴，为公平的商业模式设计提供参考。借鉴欧洲和美国的经验，本研究强调农场主积极参与光伏项目的开发和实施，以提高财务可行性、公平性和利益相关者的参与。

{"title":"Assessing financial feasibility and equity prospects in agrivoltaics: a case study of Hachinohe, Japan","authors":"Xiao Chen , Vibhas Sukhwani , Bijon Kumer Mitra , Anudari Batsaikhan , Rajib Shaw","doi":"10.1016/j.ref.2025.100751","DOIUrl":"10.1016/j.ref.2025.100751","url":null,"abstract":"<div><div>Agrivoltaics, which combines the use of land for both agriculture and photovoltaic energy production, is emerging as a promising solution to the land use conflicts between farming and renewable energy. By simultaneously boosting crop yields, enhancing solar panel efficiency and revitalising rural incomes, agrivoltaics is attracting farmers and solar developers, prompting innovation in technology and business models. Nevertheless, the key to scaling agrivoltaics depends on its commercial viability for different stakeholders, an area that still requires further exploration. To bridge this gap, this research examines the business model of an ongoing agrivoltaic project in the Hachinohe region of Aomori Prefecture, Japan, with a particular focus on financial feasibility and equitable distribution of benefits among stakeholders. The study applies multi-criteria decision-making method to assess the project’s overall financial feasibility using NPV, IRR, and payback periods, while also exploring the equity implications through Gini coefficients. Thereafter, a sensitivity analysis is conducted to offer policy suggestions such as revenue-sharing, better lease terms, and subsidies for farmers, with the purpose of enhancing rural economic revitalization and inform equitable business model design in Japan’s energy transition. Drawing on experiences from Europe and the United States, this research emphasizes the active engagement of farm owners in the development and implementation of agrivoltaic projects to enhance financial feasibility, equity and stakeholder participation.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"56 ","pages":"Article 100751"},"PeriodicalIF":5.9,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145106328","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A spatial-techno-economic assessment modeling framework for optimal planning of rooftop photovoltaic systems in urban areas: the case of New Assiut City, Egypt 城市屋顶光伏系统优化规划的空间-技术-经济评估建模框架：以埃及新阿西尤特市为例

IF 5.9 Q2 ENERGY & FUELS

Renewable Energy Focus

Pub Date : 2025-09-08 DOI: 10.1016/j.ref.2025.100752

Mohammed Hussien Yadem Lamien , Hooman Farzaneh

Rooftop photovoltaic (PV) power generation can provide an efficient solution to urban energy needs, benefiting both individual homeowners and the broader community in urban areas. However, identifying suitable rooftop spaces and optimal planning of the rooftop PV systems requires a comprehensive approach. Unlike most previous studies that have concentrated on the technical aspects of rooftop PV systems, this study emphasizes both spatial and techno-economic factors. It explores how the optimal placement of rooftop PV systems can benefit customers and contribute to a more resilient and reliable energy system in newly constructed buildings. To this aim, this study presents a detailed methodology for determining the optimal placement of rooftop PV systems in newly constructed residential areas. By employing a mixed-integer linear programming (MILP) approach, the study aims to maximize the Net Present Value (NPV) of rooftop PV owners through strategically allocating solar PV panels in conjunction with designated central service areas, while adhering to spatial, technical, and economic constraints. The developed model is validated using site-specific data from a residential area, including 12 identical residential buildings in New West Assuit City, Egypt, a newly constructed but currently unoccupied district with significant solar energy potential. The results reveal that, with a latitude-based tilt angle of 27°, each building can support between 9 and 15 PV modules. In a scenario with 15% occupancy, up to 72% of the generated electricity can be sold back to the grid, resulting in the highest NPV. Conversely, a scenario with 100% occupancy leads to the lowest NPV due to the limited surplus energy available for export. Finally, a detailed sensitivity analysis is carried out to assess the impact of the tilt angle of PV panels and feed-in tariff (FiT) on NPV outcomes.

屋顶光伏发电可以为城市能源需求提供有效的解决方案，使个人房主和城市地区更广泛的社区都受益。然而，确定合适的屋顶空间和屋顶光伏系统的最佳规划需要一个综合的方法。与以往大多数集中于屋顶光伏系统技术方面的研究不同，本研究强调空间和技术经济因素。它探讨了屋顶光伏系统的最佳布局如何使客户受益，并为新建建筑物提供更有弹性和更可靠的能源系统。为此，本研究提出了一种详细的方法来确定新建住宅区屋顶光伏系统的最佳位置。通过采用混合整数线性规划（MILP）方法，该研究旨在通过将太阳能光伏板与指定的中央服务区相结合，在遵守空间、技术和经济限制的同时，战略性地分配太阳能光伏板，从而最大化屋顶光伏业主的净现值（NPV）。开发的模型使用来自住宅区的特定地点数据进行验证，该住宅区包括埃及新西阿苏特市的12栋相同的住宅建筑，这是一个新建但目前无人居住的地区，具有巨大的太阳能潜力。结果表明，在纬度为27°的倾斜角度下，每栋建筑可以支持9到15个光伏模块。在占用率为15%的情况下，高达72%的发电量可以卖回电网，从而产生最高的净现值。相反，由于可用于出口的剩余能源有限，100%入住率的情景导致NPV最低。最后，进行了详细的敏感性分析，以评估光伏电池板倾斜角度和上网电价（FiT）对NPV结果的影响。

{"title":"A spatial-techno-economic assessment modeling framework for optimal planning of rooftop photovoltaic systems in urban areas: the case of New Assiut City, Egypt","authors":"Mohammed Hussien Yadem Lamien , Hooman Farzaneh","doi":"10.1016/j.ref.2025.100752","DOIUrl":"10.1016/j.ref.2025.100752","url":null,"abstract":"<div><div>Rooftop photovoltaic (PV) power generation can provide an efficient solution to urban energy needs, benefiting both individual homeowners and the broader community in urban areas. However, identifying suitable rooftop spaces and optimal planning of the rooftop PV systems requires a comprehensive approach. Unlike most previous studies that have concentrated on the technical aspects of rooftop PV systems, this study emphasizes both spatial and techno-economic factors. It explores how the optimal placement of rooftop PV systems can benefit customers and contribute to a more resilient and reliable energy system in newly constructed buildings. To this aim, this study presents a detailed methodology for determining the optimal placement of rooftop PV systems in newly constructed residential areas. By employing a mixed-integer linear programming (MILP) approach, the study aims to maximize the Net Present Value (NPV) of rooftop PV owners through strategically allocating solar PV panels in conjunction with designated central service areas, while adhering to spatial, technical, and economic constraints. The developed model is validated using site-specific data from a residential area, including 12 identical residential buildings in New West Assuit City, Egypt, a newly constructed but currently unoccupied district with significant solar energy potential. The results reveal that, with a latitude-based tilt angle of 27°, each building can support between 9 and 15 PV modules. In a scenario with 15% occupancy, up to 72% of the generated electricity can be sold back to the grid, resulting in the highest NPV. Conversely, a scenario with 100% occupancy leads to the lowest NPV due to the limited surplus energy available for export. Finally, a detailed sensitivity analysis is carried out to assess the impact of the tilt angle of PV panels and feed-in tariff (FiT) on NPV outcomes.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"56 ","pages":"Article 100752"},"PeriodicalIF":5.9,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145106329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

How do environmental values and attributes influence coastal community acceptance of tidal energy? Evidence from the Bristol Channel, UK 环境价值和属性如何影响沿海社区对潮汐能的接受？英国布里斯托尔海峡的证据

IF 5.9 Q2 ENERGY & FUELS

Renewable Energy Focus

Pub Date : 2025-09-02 DOI: 10.1016/j.ref.2025.100748

Andrew Edwards-Jones , Caroline Hattam , Tara Hooper , Nicola J. Beaumont

Early consideration of potential societal issues, including public acceptance, is important for the effective implementation of energy policies and technologies. Conversely, lack of public acceptance can act as a barrier to their uptake, and deployment of renewable technologies has frequently been marked by public opposition at the local level. Levels of support for renewable energy are currently high, although expressions of public support do not always translate into approval for local developments, and there is significant variability in acceptance depending on a wide range of attributes. This paper provides novel insights into potential contributing factors to public acceptance of tidal energy amongst residents of coastal communities along a major inlet in the UK with high potential for tidal energy development. Adopting a largely qualitative empirical approach, nineteen participants from three coastal towns took part in photo-elicitation interviews that utilised self-taken photographs to drive discussions around local environmental (marine and coastal) attributes of importance and how these might influence participants’ attitudes toward tidal energy. Selected data from a previous related energy survey provided a mixed-methods lens to reinforce specific issues raised by participants. Key findings on participants’ perceptions of tidal energy included overall general positivity toward this technology, as well as recognition of its significance for sustainable energy. A range of trade-offs between issues of personal importance and the wider significance of tidal energy were also apparent. The perceived impacts of developments on environmental attributes of greatest importance to participants were thematically analysed revealing particular concerns regarding local environmental impacts and impacts on wildlife. Presented as key influencing issues on participant’s perceptions of tidal energy developments, this new qualitative data improves our understanding of the issues that can lead to acceptance or rejection of proposals and are thus of relevance to a range of users, including decision-makers, consultants and developers.

及早考虑潜在的社会问题，包括公众的接受程度，对于有效实施能源政策和技术是很重要的。相反，缺乏公众的接受可能成为采用可再生技术的障碍，可再生技术的部署经常受到地方一级公众的反对。目前对可再生能源的支持水平很高，尽管公众支持的表达并不总是转化为对地方发展的批准，而且根据各种属性的不同，接受程度也有很大差异。本文提供了新的见解，潜在的影响因素，公众接受潮汐能在沿海社区的居民中，沿英国的一个主要入口，具有很高的潮汐能开发潜力。采用很大程度上定性的经验方法，来自三个沿海城镇的19名参与者参加了照片启发访谈，利用自拍照来推动围绕当地环境（海洋和沿海）属性的重要性以及这些属性如何影响参与者对潮汐能的态度的讨论。从以前的相关能源调查中选择的数据提供了一个混合方法的镜头，以加强参与者提出的具体问题。参与者对潮汐能的看法的主要发现包括对这项技术的总体积极态度，以及对其对可持续能源的重要性的认识。在个人重要问题和潮汐能的广泛意义之间的一系列权衡也很明显。对与会者认为最重要的发展对环境属性的影响进行了专题分析，揭示了对当地环境影响和对野生动物影响的特别关注。作为影响参与者对潮汐能开发看法的关键问题，这些新的定性数据提高了我们对可能导致接受或拒绝提案的问题的理解，因此与包括决策者、顾问和开发商在内的一系列用户相关。

{"title":"How do environmental values and attributes influence coastal community acceptance of tidal energy? Evidence from the Bristol Channel, UK","authors":"Andrew Edwards-Jones , Caroline Hattam , Tara Hooper , Nicola J. Beaumont","doi":"10.1016/j.ref.2025.100748","DOIUrl":"10.1016/j.ref.2025.100748","url":null,"abstract":"<div><div>Early consideration of potential societal issues, including public acceptance, is important for the effective implementation of energy policies and technologies. Conversely, lack of public acceptance can act as a barrier to their uptake, and deployment of renewable technologies has frequently been marked by public opposition at the local level. Levels of support for renewable energy are currently high, although expressions of public support do not always translate into approval for local developments, and there is significant variability in acceptance depending on a wide range of attributes. This paper provides novel insights into potential contributing factors to public acceptance of tidal energy amongst residents of coastal communities along a major inlet in the UK with high potential for tidal energy development. Adopting a largely qualitative empirical approach, nineteen participants from three coastal towns took part in photo-elicitation interviews that utilised self-taken photographs to drive discussions around local environmental (marine and coastal) attributes of importance and how these might influence participants’ attitudes toward tidal energy. Selected data from a previous related energy survey provided a mixed-methods lens to reinforce specific issues raised by participants. Key findings on participants’ perceptions of tidal energy included overall general positivity toward this technology, as well as recognition of its significance for sustainable energy. A range of trade-offs between issues of personal importance and the wider significance of tidal energy were also apparent. The perceived impacts of developments on environmental attributes of greatest importance to participants were thematically analysed revealing particular concerns regarding local environmental impacts and impacts on wildlife. Presented as key influencing issues on participant’s perceptions of tidal energy developments, this new qualitative data improves our understanding of the issues that can lead to acceptance or rejection of proposals and are thus of relevance to a range of users, including decision-makers, consultants and developers.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"56 ","pages":"Article 100748"},"PeriodicalIF":5.9,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144997455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0