Renewable Energy Focus最新文献_第10页

A sustainable power management solution integrated with fuel cell based hybrid energy storage system in variable climate conditions 在可变气候条件下，与基于燃料电池的混合能源存储系统集成的可持续电源管理解决方案

IF 5.9 Q2 ENERGY & FUELS

Renewable Energy Focus

Pub Date : 2025-12-02 DOI: 10.1016/j.ref.2025.100797

Debabrata Mazumdar , Josep M. Guerrero , Nishant Thakkar , Anand R. , Chiranjit Sain , Taha Selim Ustun

The current age has seen a growing reliance on HSES including fuel cells, solar, and wind with the goal of lowering global warming, the greenhouse effect, and reliance on fossil fuels. An efficient management technique that incorporates a hybrid energy storage alternative is presented here to develop a self-sufficient and sustainable energy system. The suggested system incorporates all four-energy storage and generating techniques: batteries, fuel cells, photovoltaic, and super-capacitors. This study suggests an EMS with an ANFIS controller, a Zeta converter, and a ZOA-based MPPT for fuel cell regulation in a micro grid that consists of photovoltaic, fuel cells, batteries, and super-capacitors. Effective power sharing, enhanced DC-bus voltage stability, and quick dynamic response under varying load and ambient conditions are all guaranteed by the suggested architecture. In comparison to FSSO, MPA and GWO algorithms, simulation findings show that ZOA-based MPPT achieves 30–45 % faster convergence and 8–10 % higher energy extraction, with steady-state oscillations below 1.8 %. In addition to ensuring seamless coordination with the battery and super-capacitor, the ANFIS controller keeps the fuel-cell voltage at 300 ± 2 V. Compared to traditional boost converter topologies, the integrated control system stabilizes the DC-bus voltage within ±2 % and minimizes ripple content by about 30 %. A damping ratio of 0.83 and a settling time of less than 0.25 seconds are confirmed by stability analysis, demonstrating robustness and strong dynamic stability against changes in the parameters. These results demonstrate the system’s capacity to operate dependably and efficiently in both independent and grid-connected hybrid energy applications.

当今时代，人们越来越依赖燃料电池、太阳能和风能等HSES，其目标是降低全球变暖、温室效应和对化石燃料的依赖。本文提出了一种结合混合储能替代方案的高效管理技术，以开发自给自足和可持续的能源系统。建议的系统结合了所有四种能量存储和发电技术：电池、燃料电池、光伏和超级电容器。本研究提出了一种具有ANFIS控制器、Zeta转换器和基于zoa的MPPT的EMS，用于由光伏、燃料电池、电池和超级电容器组成的微电网中的燃料电池调节。该架构保证了有效的功率共享、增强的直流母线电压稳定性以及在不同负载和环境条件下的快速动态响应。仿真结果表明，与FSSO、MPA和GWO算法相比，基于zoa的MPPT算法收敛速度提高30 - 45%，能量提取速度提高8 - 10%，稳态振荡低于1.8%。除了确保与电池和超级电容器的无缝协调外，ANFIS控制器还将燃料电池电压保持在300±2 V。与传统升压转换器拓扑结构相比，集成控制系统将直流母线电压稳定在±2%以内，并将纹波含量减少约30%。稳定性分析证实阻尼比为0.83，沉降时间小于0.25秒，对参数变化具有鲁棒性和较强的动稳定性。这些结果证明了该系统在独立和并网混合能源应用中可靠高效运行的能力。

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引用次数: 0

Hybrid stochastic-robust optimization for smart parking lot trading with local electricity markets under a decentralized framework with renewable energy integration 分布式可再生能源集成框架下智能停车场与本地电力市场交易的混合随机-鲁棒优化

IF 5.9 Q2 ENERGY & FUELS

Renewable Energy Focus

Pub Date : 2025-11-28 DOI: 10.1016/j.ref.2025.100794

Asma Nasiri , Nima Nasiri , Behnam Mohammadi-Ivatloo , Mehdi Abapour , Sajad Najafi Ravadanegh

This paper presents a hybrid stochastic-robust optimization approach for trading smart parking lots (SPL) with the local electricity market (LEM) within a decentralized scheduling framework and considering the renewable energy sources (RES) participation. In the proposed structure, the smart parking operator aims to minimize operating costs by submitting offers/bids to the LEM. Additionally, the impact of implementing smart charging strategies in the trading process of SPLs with the LEM is discussed. Dischargin profle of SPLs have been modeled using the k-means clustering method and considering the uncertain behavior of electric vehicle (EV) owners. The aim of the LEM operator is to clear the electricity market while considering the physical constraints of the electricity distribution network (EDN), fluctuations in wholesale electricity market (WEM) prices, and the uncertain behavior of RES. In this study, the uncertain behavior of WEM price and RES is modeled by robust optimization (RO) and stochastic programming (SP), respectively. To implement energy trade between SPLs and the LEM, alternating direction method of multipliers (ADMM) algorithm has been used in the framework of decentralized optimization. The proposed problem is formulated as a second-order conic programming (SOCP) model, leveraging the benefits of convex optimization and efficiently solved using the MOSEK solver. Solving the proposed hybrid optimization problem using the ADMM algorithm leads to a robust solution, which enables trade between SPLs and the LEM while respecting privacy. The results show that implementing a smart electric vehicle charging strategy leads to a 59.18%, 8.56%, and 11.23% reduction in the first to third parking lots. In addition, implementing the smart charging strategy also reduces the operating costs of LEM by 0.3%.

在分散调度框架下，考虑可再生能源的参与，提出了智能停车场（SPL）与本地电力市场（LEM）交易的一种混合随机-鲁棒优化方法。在拟议的结构中，智能停车运营商的目标是通过向LEM提交报价/投标来最大限度地降低运营成本。此外，还讨论了在与LEM交易过程中实施智能充电策略的影响。采用k-均值聚类方法，考虑电动汽车车主行为的不确定性，建立了电动汽车排放曲线模型。LEM运营商的目标是在考虑配电网（EDN）的物理约束、批发电力市场（WEM）价格波动和RES的不确定性行为的情况下清理电力市场。在本研究中，WEM价格和RES的不确定性行为分别采用鲁棒优化（RO）和随机规划（SP）建模。为了实现SPLs与LEM之间的能量交易，在分散优化框架下采用了乘法器的交替方向法（ADMM）算法。该问题被表述为二阶二次规划（SOCP）模型，利用凸优化的优点，并使用MOSEK求解器有效地求解。使用ADMM算法解决所提出的混合优化问题可以得到一个鲁棒的解决方案，该解决方案可以在尊重隐私的情况下实现SPLs和LEM之间的交易。结果表明，实施智能充电策略后，第一到第三停车场分别减少59.18%、8.56%和11.23%。此外，实施智能充电策略也使LEM的运营成本降低了0.3%。

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引用次数: 0

Reliability-oriented AC/DC hybrid distribution network planning: A risk-constrained approach 面向可靠性的交直流混合配电网规划：一种风险约束方法

IF 5.9 Q2 ENERGY & FUELS

Renewable Energy Focus

Pub Date : 2025-11-22 DOI: 10.1016/j.ref.2025.100790

Zahra Esmaeilzadeh, Hamid Falaghi, Maryam Ramezani

The rising share of direct current (DC) loads and DC-based distributed generations (DGs) challenges the efficiency of alternating current (AC) distribution networks, thereby making hybrid AC/DC distribution networks a more flexible and economical solution. However, uncertainties in AC and DC load demands and renewable DG outputs can lead to violations in bus voltage and line loading limits, which introduces significant risks. The proposed plan includes modeling the security constraints of the problem as a combination of hard and soft constraints. Hard constraints represent strict technical requirements that must be satisfied, whereas soft constraints allow limited violations and are modeled as penalty costs associated with bus voltage deviation and line overload. These penalties are included in the objective function to internalize the cost of risk. The conditional value at risk (CVaR) criterion is employed to quantify and control risk under uncertainty. Ensuring network reliability is a critical aspect of distribution network planning, as it directly influence service continuity and overall operational resilience. Network reliability is modeled through the inclusion of outage-related costs. The overall objective function consists of investment costs, operation costs, and risk. Both risk-averse and risk-seeking strategies are examined by adjusting the weight of the CVaR component. The effectiveness of the proposed methodology is demonstrated using a test distribution network, and a sensitivity analysis is conducted on the planning problem considering both risk and reliability simultaneously under factors such as confidence level, load interruption cost, equipment cost, converter efficiency, and equipment failure rates.

随着直流（DC）负载和基于直流的分布式发电（dg）份额的不断增加，对交流（AC）配电网的效率提出了挑战，从而使交直流混合配电网成为一种更加灵活和经济的解决方案。然而，交流和直流负载需求以及可再生DG输出的不确定性可能导致违反母线电压和线路负载限制，从而引入重大风险。建议的计划包括将问题的安全约束建模为硬约束和软约束的组合。硬约束表示必须满足的严格技术要求，而软约束允许有限的违规，并建模为与母线电压偏差和线路过载相关的惩罚成本。这些惩罚包含在目标函数中，以内部化风险成本。采用条件风险值（CVaR）准则对不确定条件下的风险进行量化和控制。确保配电网的可靠性是配电网规划的一个关键方面，因为它直接影响到服务的连续性和整体运行的弹性。网络可靠性是通过包含与中断相关的成本来建模的。总体目标函数包括投资成本、运营成本和风险。通过调整CVaR分量的权重来检验风险规避和风险寻求策略。通过一个配电网试验验证了该方法的有效性，并在置信度、负荷中断成本、设备成本、变流器效率和设备故障率等因素的影响下，对同时考虑风险和可靠性的配电网规划问题进行了敏感性分析。

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引用次数: 0

Techno-economic feasibility of hybrid renewable energy systems for continuous demand coverage at the provincial level in South Korea 韩国混合可再生能源系统持续覆盖省级需求的技术经济可行性

IF 5.9 Q2 ENERGY & FUELS

Renewable Energy Focus

Pub Date : 2025-11-19 DOI: 10.1016/j.ref.2025.100788

Abdulfatai Olatunji Yakub , Noel Ngando Same , Deepak Chaulagain , Abdullahi Yahaya , Abdulhameed Babatunde Owolabi , Anthony Fon Tangoh , Dongjun Suh , Jong Wook Roh , Jeong Ok Lim , Jeung-Soo Huh

This study concerns the need to provide alternatives to the current regime of fossil-fuel energy toward achieving net zero CO2 emissions and limiting the rise in global average temperatures. Here, we focus on the development of hybrid renewable energy systems (HRESs), which combine wind energy, photovoltaic systems, and energy storage to meet the growing demand for renewable energy in South Korea. In this study, the Multi-Objective Particle Swarm Optimization algorithm is utilized with an HRES to determine the optimal HRES configuration, evaluated by measuring the net present cost while ensuring that energy demand can be reliably met. We find that solar photovoltaic will yield grid parity in nearly 94.4 % of the regions examined throughout South Korea by 2030, indicating its cost-effectiveness over wind power. However, the most optimal HRES configuration over most of South Korea is the WT-PV-ESS configuration, which combines wind turbines, photovoltaic systems, and universal energy storage, providing the most cost-effective solution. We believe that this study will lay the foundation for further investigation into the analysis and optimization of renewable energy sources in South Korea, paving the way toward reaching our energy goals.

这项研究关注的是，为实现二氧化碳净零排放和限制全球平均气温上升，需要提供替代目前化石燃料能源体制的能源。在这里，我们重点关注混合可再生能源系统（HRESs）的发展，它结合了风能、光伏系统和能源存储，以满足韩国对可再生能源日益增长的需求。在本研究中，利用多目标粒子群优化算法和HRES来确定最优的HRES配置，通过测量净当前成本来评估，同时确保能够可靠地满足能源需求。我们发现，到2030年，太阳能光伏发电将在韩国近94.4%的地区实现电网平价，这表明它比风能更具成本效益。然而，在韩国大部分地区，最理想的HRES配置是WT-PV-ESS配置，它结合了风力涡轮机、光伏系统和通用储能系统，提供了最具成本效益的解决方案。我们相信，这项研究将为进一步调查分析和优化韩国可再生能源奠定基础，为实现我们的能源目标铺平道路。

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引用次数: 0

A Soft Systems Methodology for Renewable Energy Research in the Built Environment: A Case Study of Coloured Solar Photovoltaics in Luxembourg 建筑环境中可再生能源研究的软系统方法论：卢森堡彩色太阳能光伏案例研究

IF 5.9 Q2 ENERGY & FUELS

Renewable Energy Focus

Pub Date : 2025-11-18 DOI: 10.1016/j.ref.2025.100789

Alexander Skinner, Catherine Jones

Integrating photovoltaics into the built environment requires navigating technical, aesthetic, and social complexities, particularly in dense urban contexts. Coloured photovoltaics offer potential to improve visual integration, but their adoption is influenced by performance trade-offs, policy frameworks, and local urban conditions. This paper presents an Integrated Assessment Process (IAP) developed to evaluate coloured photovoltaics within these complex settings.

The IAP was structured through the application of Soft Systems Methodology (SSM), providing a way to capture and connect the diverse factors shaping deployment. Using Luxembourg as a case study, the process combines technical assessment of coloured photovoltaic prototypes, spatial analysis of urban morphology, policy and regulatory review, and insights from stakeholders. The results highlight key tensions between visual quality and energy output, as well as the influence of heritage protection rules, fragmented ownership, and built form constraints on implementation potential.

By aligning technological evaluation with urban planning considerations and social perspectives, the IAP offers a holistic framework to guide the integration of coloured photovoltaics in the built environment. The Luxembourg case study illustrates how this approach can reveal context-specific pathways to overcome barriers and support wider adoption. The findings contribute to ongoing efforts to balance technical feasibility, public acceptance, and urban realities in renewable energy transitions.

将光伏集成到建筑环境中需要在技术、美学和社会复杂性方面进行导航，特别是在密集的城市环境中。彩色光伏提供了改善视觉整合的潜力，但其采用受到性能权衡、政策框架和当地城市条件的影响。本文提出了一种综合评估过程（IAP），用于评估这些复杂设置中的彩色光伏。IAP是通过软系统方法论（SSM）的应用来构建的，提供了一种捕获和连接影响部署的各种因素的方法。以卢森堡为例，该过程结合了彩色光伏原型的技术评估、城市形态的空间分析、政策和监管审查以及利益相关者的见解。结果强调了视觉质量和能量输出之间的关键紧张关系，以及遗产保护规则、分散所有权和建筑形式对实施潜力的限制的影响。通过将技术评估与城市规划考虑和社会观点结合起来，IAP提供了一个整体框架来指导彩色光伏在建筑环境中的整合。卢森堡的案例研究说明了这种方法如何能够揭示出克服障碍和支持更广泛采用的具体途径。研究结果有助于在可再生能源转型中平衡技术可行性、公众接受度和城市现实。

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引用次数: 0

Renewable-Based Hybrid Charging Infrastructure for Isolated Microgrids: Enhancing Power Quality and Supporting EV Integration 孤立微电网的可再生混合充电基础设施：提高电能质量和支持电动汽车一体化

IF 5.9 Q2 ENERGY & FUELS

Renewable Energy Focus

Pub Date : 2025-11-10 DOI: 10.1016/j.ref.2025.100783

Sombir Kundu , Ashutosh K. Giri , Sunil Kadiyan , Surender Singh , Sudhanshu Mittal

This article presents a three-phase, three-wire (3P-3W) renewable-based hybrid charging infrastructure that includes a photovoltaic (PV) system, wind-powered self-excited induction generator (SEIG), storage battery, sources to provide power to small consumer loads as well as incorporating AC & DC charging stations. The generated PV power is employed locally to increase the self-consumption rate, whereas the power generated from the wind is utilized to feed AC loads and electric vehicles (EVs) connected at the point of common injection (PCI). The harmonics introduced by the charging stations are suppressed using a modified filtering generalized integrator (MFGI) based control technique. The system is equipped with ancillary services, such as maintaining the power quality (PQ) of the isolated system frequent switching of EV loads and small consumer loads, undisrupted power to loads, and reactive power compensation. Validation of the proposed hybrid system is presented through a performance evaluation of the presented technique with an enhanced phase-locked loop (EPLL) and Notch filter technique. The results are plotted using MATLAB/Simulink and verified with license hybrid optimization of multiple energy resources (HOMER) version 1.2.7 under different operating circumstances. Despite the elevated total harmonic distortion (THD) of 24.49% in the load current, the MFGI control effectively mitigates the supply current THD to 4.0%, which effectively complies with the IEEE-519 standard.

本文介绍了一种三相三线制（3P-3W）可再生混合充电基础设施，该基础设施包括光伏（PV）系统、风力自励感应发电机（SEIG）、蓄电池、为小型消费负荷提供电力的电源，以及结合交流和直流充电站。产生的光伏发电在当地使用，以提高自耗率，而风力发电则用于馈送在公共注入点（PCI）连接的交流负载和电动汽车（ev）。采用基于改进滤波广义积分器（MFGI）的控制技术抑制充电站引入的谐波。该系统具有隔离系统电能质量（PQ）的维持、电动汽车负载与小消费负载的频繁切换、负载不间断供电、无功补偿等辅助功能。通过使用增强锁相环（EPLL）和陷波滤波技术对所提出的混合系统进行性能评估，验证了所提出的混合系统。使用MATLAB/Simulink绘制结果，并在不同运行环境下使用多能源混合优化（HOMER） 1.2.7版本许可证进行验证。在负载电流总谐波失真（THD）高达24.49%的情况下，MFGI控制有效地将电源电流总谐波失真（THD）降低到4.0%，有效地符合IEEE-519标准。

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引用次数: 0

Optimizing investment strategies for biogas-solar photovoltaic microgeneration: a multi-objective approach 沼气-太阳能光伏微发电投资策略优化：多目标方法

IF 5.9 Q2 ENERGY & FUELS

Renewable Energy Focus

Pub Date : 2025-11-07 DOI: 10.1016/j.ref.2025.100787

Pedro Alberto Chaib de Sousa Bernardes , Giancarlo Aquila , Edson de Oliveira Pamplona , Paulo Rotella Junior , Luiz Célio Souza Rocha , Karel Janda

Brazil has encouraged distributed generation (DG) through net-metering, state tax exemptions, and subsidized financing. While some renewable energy sources (RES) show complementarities, the biogas and solar PV integration remains little explored, especially under varying geographic and regulatory conditions. This study proposes an optimization model to support economic planning of hybrid biogas-PV DG systems using swine waste in three Brazilian cities. The model considered installed capacity as input variables and the mean and standard deviation of Net Present Value (NPV) as outputs. Design of experiments, combined with the Normal Boundary Intersection (NBI) method, defined objective functions and constructed the Pareto frontier. Pareto-optimal solutions were then identified through the entropy/Mahalanobis distance indicator. The results showed mean NPVs of 577,976.44 in Uberlândia-MG, 537,898.31 in Agudos-SP, and 328,786.67 in Toledo-PR, with return-risk ratios of 12.49, 11.35, and 8.74, respectively. Confidence ellipses indicated overlap, and the MANOVA test revealed no significant differences among cities. The study provides a replicable and flexible framework highlighting complementarities between biogas and solar PV, supporting investors and regulators in decision-making and advancing hybrid DG planning in Brazil.

巴西通过净计量、国家免税和补贴融资鼓励分布式发电（DG）。虽然一些可再生能源（RES）显示互补性，但沼气和太阳能光伏的整合仍然很少探索，特别是在不同的地理和监管条件下。本研究提出了一个优化模型，以支持巴西三个城市使用猪粪的混合沼气-光伏DG系统的经济规划。模型以装机容量为输入变量，净现值（NPV）均值和标准差为输出变量。在实验设计中，结合法向边界相交（NBI）方法，定义目标函数，构造Pareto边界。然后通过熵/马氏距离指标确定帕累托最优解。结果显示，uberlind - mg的平均npv为577,976.44，Agudos-SP的平均npv为537,898.31，Toledo-PR的平均npv为328,786.67，收益风险比分别为12.49,11.35和8.74。置信椭圆表示重叠，MANOVA检验显示城市之间没有显著差异。该研究提供了一个可复制和灵活的框架，突出了沼气和太阳能光伏之间的互补性，支持投资者和监管机构的决策，并推进巴西的混合DG规划。

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引用次数: 0

Grid code requirements for the integration of renewable energy sources in Indonesia—a review 印尼可再生能源并网电网规范要求综述

IF 5.9 Q2 ENERGY & FUELS

Renewable Energy Focus

Pub Date : 2025-11-05 DOI: 10.1016/j.ref.2025.100782

Majid Ali , Yajuan Guan , Juan C. Vasquez , Josep M. Guerrero , Fransisco Danang Wijaya , Adam Priyo Perdana

The large-scale integration of renewable energy sources into electric grids proposes significant challenges for any power grid management and planning. To address these challenges, system operators have developed GCs so that the grid operates safely, reliably, and economically. These codes establish technical, operational, and procedural standards for the connection and operation of renewable energy systems to the utility grid. This article investigates the current state of GCs in Indonesia as a case study, highlighting the growing need for updated and robust regulations to allocate renewable energy integration. The article focuses on the integration requirements for microgrid technologies, which are vital for decentralized energy systems and the proliferation of renewable resources, especially in remote and off-grid areas, especially Indonesia, and targets Indonesia to adopt renewable energy. Insights from Denmark’s advanced energy framework are utilized to propose recommendations for enhancing Indonesia’s GCs. A comparative analysis between the standard of IEEE 1547-2003 and IEEE 1547-2018 to compliance in terms of voltage regulation, fault ride-through capabilities, and Distributed Energy Resources (DERs) interoperability is carried out.

可再生能源大规模并网给电网管理和规划提出了重大挑战。为了应对这些挑战，系统运营商开发了GCs，使电网安全、可靠、经济地运行。这些规范为可再生能源系统与公用电网的连接和运行建立了技术、操作和程序标准。本文以印度尼西亚为例，调查了GCs的现状，强调了对更新和强有力的法规来分配可再生能源整合的日益增长的需求。本文重点关注微电网技术的整合要求，这对分散式能源系统和可再生资源的扩散至关重要，特别是在偏远和离网地区，特别是印度尼西亚，并以印度尼西亚采用可再生能源为目标。从丹麦先进的能源框架中获得的见解被用来为加强印度尼西亚的全球气候变化提出建议。对IEEE 1547-2003和IEEE 1547-2018标准在电压调节、故障穿越能力和分布式能源（DERs）互操作性方面的合规性进行了比较分析。

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引用次数: 0

Privacy-Preserving and Stochastic Energy Management of Multi-Microgrid Systems with Bidirectional Electric Vehicle Integration 双向电动车集成多微网系统的隐私保护与随机能量管理

IF 5.9 Q2 ENERGY & FUELS

Renewable Energy Focus

Pub Date : 2025-11-05 DOI: 10.1016/j.ref.2025.100784

Anas Quteishat , Mahmoud A. Younis , Seyed Reza Seyednouri , Amin Safari

This paper investigates distributed stochastic optimal energy management of an active distribution network with multi-microgrids in which both the distribution system operator (DSO) and microgrids (MGs) strive to minimize operational costs. The primary obstacles include the preservation of privacy and the management of uncertainties in a decentralized environment. Renewable energy sources, a demand response program, and a parking lot for electric vehicles (EVs) are all features that are associated with MGs. EVs can offer flexibility by adjusting the charging and discharging power according to the needs and advantages of the MGs, using the grid-to-vehicle and vehicle-to-grid mechanism. Scenarios were generated using probability density function which were reduced by mixed integer linear programming-based scenario reduction approach to overcome the computation complexity. The alternating direction method of multipliers is utilized to manage the DSO and MG optimization problems in a distributed manner that ensures privacy and scalability. The model is tested on a modified IEEE 33-bus system with four microgrids. Based on the findings, it is evident that the bidirectional charging of EVs plays a crucial role in enabling MGs to shift their energy consumption from peak hours to off-peak hours and the proposed approach improves flexibility and enables more realistic scheduling under uncertainty.

本文研究了具有多微电网的有源配电网的分布式随机最优能量管理，其中配电系统运营商（DSO）和微电网（mg）都努力使运营成本最小化。主要障碍包括在分散的环境中保护隐私和管理不确定性。可再生能源、需求响应计划和电动汽车停车场都是与mg相关的功能。电动汽车可以根据mg的需求和优势，采用电网对车辆和车辆对电网的机制，灵活调整充放电功率。利用概率密度函数生成场景，并采用基于混合整数线性规划的场景约简方法进行约简，克服了计算复杂性。利用乘法器的交替方向方法以分布式方式管理DSO和MG优化问题，保证了隐私性和可扩展性。该模型在一个改进的IEEE 33总线系统和四个微电网上进行了测试。综上所述，电动汽车双向充电对于实现汽车在高峰时段向非高峰时段的能源消耗转移起着至关重要的作用，该方法提高了灵活性，使不确定性下的调度更加现实。

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引用次数: 0

Artificial Intelligence in Deep Geothermal Energy: Trends, Insights, and Future Perspectives 深层地热能中的人工智能：趋势、见解和未来展望

IF 5.9 Q2 ENERGY & FUELS

Renewable Energy Focus

Pub Date : 2025-11-04 DOI: 10.1016/j.ref.2025.100781

Danial Sheini Dashtgoli , Michela Giustiniani , Martina Busetti , Claudia Cherubini , Giulia Alessandrini , Guillermo A. Narsilio

Deep geothermal energy, known for its stable base load power and resilience to environmental fluctuations, is increasingly recognized as an important renewable energy source. Yet, its development is constrained by subsurface variability, high exploration costs, and operational inefficiencies. Artificial intelligence (AI) can analyze complex data, reveal patterns, and support predictive modeling to lower costs, shorten timelines, and improve efficiency. This review aims to evaluate how AI can address these barriers by systematically synthesizing its applications in deep geothermal research. A structured Web of Science search and multi-stage screening yielded 183 peer-reviewed journal papers, classified across eight research areas: reservoir characterization, exploration and resource identification, system optimization, seismic monitoring and risk assessment, drilling optimization, hybrid energy systems, environmental impact and sustainability, and techno-economic analysis. Our analysis shows that since 2020, AI applications in geothermal energy have expanded exponentially, surpassing overall AI growth rates. China and the United States dominate research output, followed by Germany, Turkey, Canada, and India. Advanced algorithms are increasingly preferred: convolutional neural networks for spatial modeling and image interpretation, recurrent neural networks for time-series forecasting, physics-informed AI, Bayesian frameworks, and autoencoders advance uncertainty quantification and data reconstruction. The novelty of this review lies in its comprehensive cross-domain synthesis of AI applications in deep geothermal energy, using a unified algorithm–input–output–performance lens. This structured mapping enables comparisons not possible in earlier overviews, reveals methodological strengths, identifies effective approaches for different geothermal tasks, and uncovers underexplored areas such as environmental assessment and techno-economic analysis.

深层地热能以其稳定的基荷功率和对环境波动的弹性，越来越被认为是一种重要的可再生能源。然而，它的发展受到地下变化、高勘探成本和低操作效率的限制。人工智能（AI）可以分析复杂的数据，揭示模式，并支持预测建模，以降低成本，缩短时间，提高效率。本文旨在评估人工智能如何通过系统地综合其在深部地热研究中的应用来解决这些障碍。结构化的科学网络搜索和多阶段筛选产生了183篇同行评议的期刊论文，分为八个研究领域：油藏表征、勘探和资源识别、系统优化、地震监测和风险评估、钻井优化、混合能源系统、环境影响和可持续性以及技术经济分析。我们的分析表明，自2020年以来，人工智能在地热能方面的应用呈指数级增长，超过了人工智能的整体增长率。中国和美国主导了研究产出，其次是德国、土耳其、加拿大和印度。先进的算法越来越受欢迎：用于空间建模和图像解释的卷积神经网络，用于时间序列预测的循环神经网络，物理信息人工智能，贝叶斯框架和推进不确定性量化和数据重建的自编码器。这篇综述的新颖之处在于它使用统一的算法-输入-输出-性能镜头，对人工智能在深层地热能中的应用进行了全面的跨领域综合。这种结构化的绘图可以进行早期概述中无法进行的比较，揭示方法优势，确定不同地热任务的有效方法，并揭示未开发的领域，如环境评估和技术经济分析。

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