Renewable Energy Focus最新文献_第4页

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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引用次数: 0

A data-driven framework for microgrid design integrating machine learning model with economic-energy-environmental parameters 集成机器学习模型与经济-能源-环境参数的微电网设计数据驱动框架

IF 5.9 Q2 ENERGY & FUELS

Renewable Energy Focus

Pub Date : 2025-11-04 DOI: 10.1016/j.ref.2025.100785

Abba Lawan Bukar , Mahmoud Kassas , Mohammad A. Abido , Ahmed S. Menesy , Babangida Modu , Mukhtar Fatihu Hamza , Djamal Hissein Didane

This study proposes a data-driven framework for designing community microgrids that integrate photovoltaic systems, wind turbines, diesel generators, and battery storage. The framework optimizes microgrid configurations based on economic, energy, and environmental (3E) sustainability performance indicators (3E-SPI). To achieve these objectives, we developed a data-driven model that combines Homer-Pro with a custom Python tool integrating extreme gradient boosting (XGBoost) machine learning algorithm and thirteen 3E-SPI calculations for community microgrid systems. Subsequently, a multi-objective optimization model with a two-layer multi-criteria decision-making (MCDM) approach was employed to evaluate microgrid configurations based on thirteen 3E-SPI to support stakeholders in the decision-making process. In the first layer, Best Worst Method (BWM) determines the weights of the 3E-SPI, whereas in the second layer, Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and VIˇsekriterijumsko Kompromisno Rangiranje (VIKOR) methods are used to rank microgrid alternatives. The predictive performance of XGBoost was compared with that of random forest (RF), support vector regression (SVR), and deep neural network (DNN). The analysis revealed that XGBoost outperformed other models, achieving superior predictive performance, with a coefficient of determination (R²) exceeding 0.95. The MCDM results indicate that hybrid photovoltaic/wind/battery/diesel microgrid is the optimal solution for the studied community, yielding a total net present cost of approximately $1.3 million, a levelized cost of energy of $0.29/kWh, and annual CO₂ emissions of 169.11 kg. Overall, the proposed framework provides a practical tool for policymakers and energy planners to design cost-effective, reliable, and sustainable microgrids.

这项研究提出了一个数据驱动的框架，用于设计集成光伏系统、风力涡轮机、柴油发电机和电池存储的社区微电网。该框架基于经济、能源和环境（3E）可持续性绩效指标（3E- spi）优化微电网配置。为了实现这些目标，我们开发了一个数据驱动模型，该模型结合了Homer-Pro和一个定制的Python工具，该工具集成了极端梯度增强（XGBoost）机器学习算法和13个用于社区微电网系统的3E-SPI计算。随后，基于13条3E-SPI，采用两层多准则决策（MCDM）方法的多目标优化模型对微电网配置进行评估，为利益相关者决策提供支持。在第一层，最佳最差方法（BWM）确定3E-SPI的权重，而在第二层，使用与理想解决方案相似的顺序偏好技术（TOPSIS）和VI - sekriterijumsko Kompromisno Rangiranje （VIKOR）方法对微电网备选方案进行排名。将XGBoost的预测性能与随机森林（RF）、支持向量回归（SVR）和深度神经网络（DNN）的预测性能进行比较。分析表明，XGBoost的预测性能优于其他模型，其决定系数（R2）超过0.95。MCDM结果表明，光伏/风能/电池/柴油混合微电网是研究社区的最佳解决方案，总净现值成本约为130万美元，能源平准化成本为0.29美元/千瓦时，年二氧化碳排放量为169.11公斤。总体而言，所提出的框架为政策制定者和能源规划者设计具有成本效益、可靠和可持续的微电网提供了实用工具。

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引用次数: 0

Increasing grid access capacity for renewable integration through a grid-forming E-STATCOM under Spanish regulation 根据西班牙法规，通过电网形成的E-STATCOM增加可再生能源整合的电网接入能力

IF 5.9 Q2 ENERGY & FUELS

Renewable Energy Focus

Pub Date : 2025-11-04 DOI: 10.1016/j.ref.2025.100786

Carolina M. Martín, Santiago Arnaltes, Francisco Arredondo, Jaime Alonso-Martínez, José Luis Rodríguez-Amenedo

The increasing penetration of non-synchronous renewable generation poses significant challenges for grid stability and access capacity, particularly under regulatory frameworks with strict technical requirements. In Spain, rotating synchronous condensers (RSCs) have recently been proposed to strengthen the grid and facilitate renewable integration; however, their deployment is currently restricted by the Transmission System Operator (TSO) due to concerns such as exceeding the permissible short-circuit current levels and the risk of subsynchronous torsional interactions (SSTI). This paper proposes an energy storage static synchronous compensator (E-STATCOM) model with grid forming (GFM) control as an effective alternative to RSCs for increasing grid access capacity for renewable integration. A control strategy based on the emulation of the synchronous machine swing equation, combined with a power system stabilizer (PSS), is proposed to ensure system stability. The PSS addresses the oscillatory response that arises when emulating the behavior of an RSC in the converter. The concept is validated through simulation studies in PSCAD, using the equivalent electrical network of the Peninsular Electricity System and the Interconnected European System, as specified by current Spanish regulations. Results demonstrate the ability of the proposed E-STATCOM to replicate the key functionalities of RSCs, including inertial response and dynamic voltage support in weak grids, while also meeting fault ride-through (FRT) requirements and ensuring power oscillation damping. It is shown that the proposed solution based on an E-STATCOM with GFM control can be valid for increasing renewable hosting capacity while mitigating the technical and economic drawbacks associated with RSCs.

非同步可再生能源发电的日益普及对电网稳定性和接入能力构成了重大挑战，特别是在具有严格技术要求的监管框架下。在西班牙，最近提出了旋转同步冷凝器（RSCs）来加强电网并促进可再生能源的整合；然而，由于担心超过允许的短路电流水平和次同步扭转相互作用（SSTI）的风险，它们的部署目前受到输电系统运营商（TSO）的限制。本文提出了一种具有网格形成（GFM）控制的储能静态同步补偿器（E-STATCOM）模型，作为rsc的有效替代方案，以增加可再生能源整合的电网接入容量。提出了一种基于同步电机摆动方程仿真的控制策略，并结合电力系统稳定器（PSS）来保证系统的稳定性。PSS解决了在模拟转换器中RSC的行为时产生的振荡响应。该概念通过PSCAD的模拟研究得到验证，该研究使用了西班牙现行法规规定的半岛电力系统和互联欧洲系统的等效电力网络。结果表明，所提出的E-STATCOM能够复制rsc的关键功能，包括弱电网中的惯性响应和动态电压支持，同时还能满足故障穿越（FRT）要求并确保功率振荡阻尼。结果表明，基于GFM控制的E-STATCOM解决方案可以有效地增加可再生主机容量，同时减轻与rsc相关的技术和经济缺陷。

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引用次数: 0

Enhancing the flexibility of decentralized energy resources through bi-level optimization in intra-day regional markets 通过日内区域市场的双层优化，增强分散能源的灵活性

IF 5.9 Q2 ENERGY & FUELS

Renewable Energy Focus

Pub Date : 2025-11-01 DOI: 10.1016/j.ref.2025.100778

Arya Abdollahi , Selma Cheshmeh Khavar

This paper presents an innovative approach to an intra-day, intra-hourly Regional Flexibility Market (RFM) that enhances the utilization of Distributed Generation (DG) flexibility, including energy storage systems, electric vehicles, and photovoltaics. The market is managed by an Advanced Virtual Power Plant (AVPP), which acts as an intermediary and efficiently integrates DG flexibility into power system operations by coordinating transactions among DG aggregators. Beyond facilitating RFM trades, the AVPP also contributes to the Wholesale Flexibility Market (WFM) and helps mitigate short-term fluctuations within the Distribution Network (DN). To achieve an optimal market balance, a hierarchical market clearing mechanism is introduced, ensuring that DG flexibility is efficiently allocated while all participating entities gain economic benefits. The framework is modeled as a bilevel optimization problem with multiple lower-level decision processes, capturing the interactions between the AVPP and aggregators. While the AVPP at the upper level seeks to maximize its own profit, each lower-level problem represents an aggregator’s strategic decision-making process. To enhance computational efficiency, the bilevel formulation is transformed into a single-level mixed-integer linear programming model and tested on a 119-bus DN. The results confirm that the framework effectively utilizes DG flexibility, increasing AVPP profit by 28% and reducing intra-hourly net-load deviations by 35%, thereby improving both economic efficiency and operational stability.

本文提出了一种创新的方法，以提高分布式发电（DG）灵活性的利用率，包括储能系统、电动汽车和光伏发电。该市场由先进虚拟电厂（AVPP）管理，AVPP作为中介，通过协调DG集成商之间的交易，有效地将DG灵活性整合到电力系统运行中。除了促进RFM交易外，AVPP还有助于批发灵活性市场（WFM），并有助于减轻分销网络（DN）的短期波动。为了实现最优的市场平衡，引入了分层的市场出清机制，确保DG灵活性得到有效分配，同时所有参与主体都获得经济利益。该框架被建模为具有多个低级决策过程的双层优化问题，捕获AVPP和聚合器之间的交互。当AVPP在上层寻求最大化自己的利润时，每个低层问题代表了聚合器的战略决策过程。为了提高计算效率，将双层公式转换为单层混合整数线性规划模型，并在119总线DN上进行了测试。结果证实，该框架有效地利用了DG灵活性，AVPP利润提高了28%，小时内净负荷偏差减少了35%，从而提高了经济效率和运行稳定性。

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引用次数: 0

Optimization configuration of energy storage system considering deep peak regulation and source-load-storage interaction 考虑深调峰和源-荷-蓄相互作用的储能系统优化配置

IF 5.9 Q2 ENERGY & FUELS

Renewable Energy Focus

Pub Date : 2025-11-01 DOI: 10.1016/j.ref.2025.100780

Wenzhuang Liu , Rui Yan , Liangxu Liu , Di Zhang

To address the pressure on peak shaving of the power system resulting from the widespread integration of renewable energy to generate electricity with the “dual-carbon” objectives, an optimized configuration regulation method for energy storage systems (ESS) is proposed in this paper. This method considers deep peak shaving and the interaction between sources, loads, and storage. It integrates an operational model that utilizes deep peaking of thermal power units (TPUs) alongside coordinated scheduling of demand-side response (DSR). To account for the uncertainty of renewable energy and the dynamic changes in load demand, the source-load-storage interaction is developed to enhance the responsiveness of ESSs to fluctuations in renewable energy supply and variations in load demand. Simulation results based on four scheduling scenarios demonstrate the effectiveness of the proposed method. Compared with conventional strategies, it reduces total operating cost by 11.35%, unit operating cost by 98.89%, and renewable energy input cost by 69.08%. Simulation results validate the effectiveness of the proposed method in reducing operation costs and increasing the utilization rate of renewable energy. Additionally, it also significantly enhances the flexibility and economic efficiency of the power system while effectively smoothing load fluctuations.

针对可再生能源与“双碳”目标并网发电所带来的电力系统调峰压力，提出了一种储能系统优化配置调节方法。该方法考虑了深度削峰和源、负载和存储之间的相互作用。它集成了一个利用火电机组（tpu）深度调峰和需求侧响应（DSR）协调调度的运行模型。考虑到可再生能源的不确定性和负荷需求的动态变化，本文提出了源-负荷-蓄交互作用，以提高ess对可再生能源供应波动和负荷需求变化的响应能力。基于四种调度场景的仿真结果验证了该方法的有效性。与常规策略相比，总运行成本降低11.35%，单位运行成本降低98.89%，可再生能源投入成本降低69.08%。仿真结果验证了该方法在降低运行成本和提高可再生能源利用率方面的有效性。此外，它还显著提高了电力系统的灵活性和经济性，同时有效地平滑了负荷波动。

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引用次数: 0

Optimal design and energy management of a hybrid PV-Wind system with hydrogen and gravity energy storage: An off-grid sustainable alternative for coal power in Morocco 具有氢气和重力储能的混合光伏-风能系统的优化设计和能源管理：摩洛哥离网可持续替代煤电

IF 5.9 Q2 ENERGY & FUELS

Renewable Energy Focus

Pub Date : 2025-10-30 DOI: 10.1016/j.ref.2025.100775

Mohammed Sahab , Anisa Emrani , Mohammad J. Sanjari , Jamil Abdelmajid , Asmae Berrada

Energy storage integration is vital for reliable power supply as reliance on renewables grows. This study investigates the co-optimization and control of an off-grid hybrid system—comprising photovoltaics (PV), wind turbines (WT), hydrogen storage, and gravity energy storage (GES)—as a sustainable alternative to a 624 MW ultra-supercritical coal unit in Morocco. Unlike prior work, this paper explicitly quantifies the distinct roles of GES and hydrogen in coal plant replacement scenarios. A unified framework is proposed to size all system components while performing 8760-hour dispatch simulations to ensure uninterrupted power supply, achieving a 0% loss of power supply probability (LPSP). At this reliability level, the optimal configuration includes ∼1000 PV modules, 594 wind turbines, a GES unit (5 m diameter, 714 m height), and substantial hydrogen infrastructure: a 790 MW electrolyzer, 650 MW fuel cell (FC), and 260 t storage tank. The resulting levelized cost of electricity (LCOE) is 0.23 €/kWh. The system reliably meets demand by leveraging PV, WT, FC, and GES. Intermittency in PV and wind is mitigated through the complementary roles of hydrogen and GES. Hydrogen production aligns with renewable generation, while GES exhibits frequent deep-cycling, highlighting its key balancing function. This analysis demonstrates that a well-sized and controlled PV–WT–Hydrogen–GES system can serve as a credible, clean alternative to coal-based generation. It underscores the potential of hybrid energy storage systems in enabling sustainable, off-grid power solutions, particularly in regions with abundant renewable energy resources.

随着对可再生能源的依赖日益增加，能源存储集成对于可靠的电力供应至关重要。本研究探讨了离网混合系统的协同优化和控制，该系统包括光伏（PV）、风力涡轮机（WT）、储氢和重力储能（GES），作为摩洛哥624兆瓦超超临界燃煤机组的可持续替代方案。与之前的工作不同，本文明确量化了GES和氢气在燃煤电厂替代方案中的不同作用。在进行8760小时调度仿真的同时，提出了一个统一的框架来对所有系统组件进行尺寸调整，以确保不间断供电，实现0%的供电损失概率（LPSP）。在这种可靠性水平下，最佳配置包括约1000个光伏模块、594个风力涡轮机、一个GES单元（直径5米，高度714米）和大量的氢基础设施：790兆瓦的电解槽、650兆瓦的燃料电池（FC）和260吨的储罐。由此产生的平均电力成本（LCOE）为0.23欧元/千瓦时。系统通过PV、WT、FC、GES等多种方式可靠地满足需求。通过氢和GES的互补作用，光伏和风能的间歇性得到缓解。氢气生产与可再生能源发电一致，而GES表现出频繁的深度循环，突出了其关键的平衡功能。这一分析表明，一个规模良好、可控的PV-WT-Hydrogen-GES系统可以作为燃煤发电的可靠、清洁的替代品。它强调了混合储能系统在实现可持续的离网电力解决方案方面的潜力，特别是在可再生能源资源丰富的地区。

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