Global Energy Interconnection最新文献_第3页

Identifying time zones of power fluctuations method for photovoltaic power ramp rate optimization 光伏发电匝道费率优化的电力波动时区识别方法

IF 2.6 Q4 ENERGY & FUELS

Global Energy Interconnection

Pub Date : 2025-10-01 DOI: 10.1016/j.gloei.2025.05.007

You Chen , Xingshuo Li , Xiaoyang Chen , Shuye Ding , Yizhi Chen , Wei Wang

Photovoltaic (PV) systems are being increasingly implemented in the grid, and their intermittent output fluctuations threaten the stability of the grid, thereby requiring effective power ramp control (PRRC) strategies. In this study, we proposed a power fluctuation identification method to optimize the PRRC strategy. The K-means++ cluster based on DTW used in this method, which clusters the historical PV power generation data into power curves corresponding to a specific weather type (sunny, cloudy, and rainy) in a time zone. Subsequently, wavelet decomposition is applied to discretize the power curves with extreme RR overrun to accurately identify the extreme fluctuation time zones. We conducted an analysis using minute-level data from a 100 kW PV plant in Arizona, which demonstrates that the proposed method can effectively identify high-risk periods. Weather patterns within the time zones were quantitatively identified using a weather probability model. A hardware-in-the-loop experimental platform was employed to validate two days of actual power data in Arizona, demonstrating the weather zoning accuracy of the method and the reasonableness of the control. The proposed methodology contributes significantly to PRRC strategy selection and parameter optimization (e.g., ESS capacity storage allocation and APC power reserve ΔP) in different time zones and weather conditions.

光伏发电系统越来越多地应用于电网，其间歇性输出波动威胁着电网的稳定，因此需要有效的功率斜坡控制策略。在本研究中，我们提出了一种功率波动识别方法来优化PRRC策略。该方法采用基于DTW的k -means++聚类，将历史光伏发电数据聚类成一个时区特定天气类型（晴、阴、雨）对应的功率曲线。随后，利用小波分解对极端RR超限功率曲线进行离散化，准确识别极端波动时区。我们使用亚利桑那州一个100千瓦光伏电站的分钟级数据进行了分析，结果表明，所提出的方法可以有效地识别高风险时期。使用天气概率模型定量地确定了时区内的天气模式。利用硬件在环实验平台对亚利桑那州两天的实际电力数据进行了验证，验证了该方法的天气分区准确性和控制的合理性。所提出的方法对不同时区和天气条件下的PRRC策略选择和参数优化（如ESS容量存储分配和APC电力储备ΔP）具有重要意义。

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引用次数: 0

Research on adaptive smooth switching control strategy for strong and weak power grids in multi-machine parallel PV energy storage VSG system 多机并联光伏储能VSG系统强弱电网自适应平滑切换控制策略研究

IF 2.6 Q4 ENERGY & FUELS

Global Energy Interconnection

Pub Date : 2025-10-01 DOI: 10.1016/j.gloei.2025.03.005

Zuobin Zhu , Shumin Sun , Yueming Ding

To enable distributed PV to adapt to variations in power grid strength and achieve stable grid connection while enhancing operational flexibility, it is essential to configure grid-connected inverters with an integrated grid-following control mode, allowing smooth switching between GFL and GFM modes. First, impedance models of GFL and GFM PV energy storage VSG systems were established, and grid stability was analyzed. Second, an online impedance identification method based on voltage fluctuation data screening was proposed to enhance the accuracy of impedance identification. Additionally, a PV energy storage GFM/GFL VSG smooth switching method based on current inner loop compensation was introduced to achieve stable grid-connected operation of distributed photovoltaics under changes in strong and weak power grids. Finally, a grid stability analysis was conducted on the multi-machine parallel PV ESS, and a simulation model of a multi-machine parallel PV ESS based on current inner loop compensation was established for testing. Results showed that, compared to using a single GFM or single GFL control for the PV VSG system, the smooth switching method of multi-machine parallel PV ESS effectively suppresses system resonance under variations in power grid strength, enabling adaptive and stable grid-connected operations of distributed PV.

为了使分布式光伏能够适应电网强度的变化，在提高运行灵活性的同时实现稳定的并网，必须为并网逆变器配置集成的电网跟随控制模式，实现GFL和GFM模式之间的平滑切换。首先，建立了GFL和GFM光伏储能VSG系统的阻抗模型，并对电网稳定性进行了分析。其次，提出了一种基于电压波动数据筛选的阻抗在线识别方法，提高了阻抗识别的准确性。此外，提出了一种基于电流内环补偿的光伏储能GFM/GFL VSG平滑切换方法，以实现分布式光伏在强弱电网变化下的稳定并网运行。最后，对多机并联光伏发电系统进行了电网稳定性分析，并建立了基于电流内环补偿的多机并联光伏发电系统仿真模型进行测试。结果表明，与单一GFM或单一GFL控制相比，多机并联光伏ESS平滑切换方式能有效抑制电网强度变化下的系统共振，实现分布式光伏自适应稳定并网运行。

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引用次数: 0

A photovoltaic array DC arc fault location method integrating MKDANN and SPA 结合MKDANN和SPA的光伏阵列直流电弧故障定位方法

IF 2.6 Q4 ENERGY & FUELS

Global Energy Interconnection

Pub Date : 2025-10-01 DOI: 10.1016/j.gloei.2025.07.004

Chenye Huang , Wei Gao , Chenhao Huang , Liangshi Lin

This paper proposes a fingerprint matching method integrating transfer learning and online learning to tackle the challenges of environmental adaptability and dynamic interference resistance in photovoltaic (PV) array DC arc fault location methods based on electromagnetic radiation (EMR) signals. Initially, a comprehensive analysis of the time–frequency characteristics of series arc EMR signals is carried out to pinpoint effective data sources that reflect fault features. Subsequently, a multi- kernel domain-adversarial neural network (MKDANN) is introduced to extract domain-invariant features, and a feature extractor designed specifically for fingerprint matching is devised. To reduce inter-domain distribution differences, a multi-kernel maximum mean discrepancy (MK-MMD) is integrated into the adaptation layer. Moreover, to deal with dynamic environmental changes in real-world situations, the support-class passive aggressive (SPA) algorithm is utilized to adjust model parameters in real time. Finally, MKDANN and SPA technologies are smoothly combined to build a fully operational fault location model. Experimental results indicate that the proposed method attains an overall fault location accuracy of at least 95%, showing strong adaptability to environmental changes and robust interference resistance while maintaining excellent online learning capabilities during model migration.

针对基于电磁辐射（EMR）信号的光伏阵列直流电弧故障定位方法中存在的环境适应性和动态抗干扰问题，提出了一种融合迁移学习和在线学习的指纹匹配方法。首先，对串联电弧EMR信号的时频特性进行综合分析，找出反映故障特征的有效数据源。随后，引入多核区域对抗神经网络（MKDANN）提取区域不变特征，并设计了专门用于指纹匹配的特征提取器。为了减少域间分布差异，在自适应层中引入了多核最大平均差异（MK-MMD）。此外，为了应对现实环境的动态变化，采用支持类被动攻击（SPA）算法实时调整模型参数。最后，将MKDANN技术与SPA技术顺利结合，构建全操作故障定位模型。实验结果表明，该方法总体故障定位精度达到95%以上，对环境变化具有较强的适应性和较强的抗干扰能力，同时在模型迁移过程中保持了良好的在线学习能力。

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引用次数: 0

Total inertia evaluation of multiple PV power stations with virtual inertia control using a small number of measurements 基于少量测量的虚拟惯性控制的多个光伏电站总惯性评估

IF 2.6 Q4 ENERGY & FUELS

Global Energy Interconnection

Pub Date : 2025-10-01 DOI: 10.1016/j.gloei.2025.05.010

Yujia Gu , Jinpeng Guo , Hongqiang Li , Lei Zhou , Yuanchen Dong , Xin Ma , Xueping Pan

The increasing penetration of PV power generation inevitably leads to the decline of system inertia, posing challenges to frequency stability. To this end, virtual inertia control has been proposed; however, it causes more fluctuations of system inertia. To address this issue, a novel equivalent inertia evaluation method for multiple PV power generation under virtual inertia control is proposed. The total system inertia is first estimated based on historical or injected disturbance. Then, the total inertia of multiple PV power generation is directly calculated by subtracting the inertia of synchronous generators from the estimated system inertia. To improve practicality, a partition-based strategy is introduced, which divides the system into regions characterized by homogeneous frequency response behaviors. After partitioning, only the synchronous generator data within the region and inter-area transmission line power are required for evaluation, reducing the demand for PMU data compared to traditional methods requiring measurements at each PV connection point. Comprehensive simulation results in a 10-machine 39-bus system penetrated with multiple PV power generation validated the effectiveness of the proposed method.

光伏发电普及率的提高必然导致系统惯性的下降，对频率稳定性提出了挑战。为此，提出了虚拟惯性控制；但是，它会引起系统惯性的较大波动。针对这一问题，提出了一种虚拟惯性控制下的多台光伏发电等效惯性评估方法。首先根据历史或注入的扰动估计系统的总惯性。然后，用估计的系统惯量减去同步发电机的惯量，直接计算出多台光伏发电的总惯量。为了提高实用性，引入了一种基于分区的策略，该策略将系统划分为具有均匀频率响应行为的区域。划分后，只需要评估区域内的同步发电机数据和区域间的传输线功率，与传统方法需要在每个光伏连接点进行测量相比，减少了对PMU数据的需求。综合仿真结果验证了该方法在10机39总线多光伏发电系统中的有效性。

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引用次数: 0

Performance assessment of meta-heuristic MPPT strategies for solar panels under complex partial shading conditions and load variation 复杂部分遮阳条件和负荷变化下太阳能电池板元启发式MPPT策略的性能评估

IF 2.6 Q4 ENERGY & FUELS

Global Energy Interconnection

Pub Date : 2025-08-01 DOI: 10.1016/j.gloei.2025.03.004

Abdulbari Talib Naser , Nur Fadilah Ab Aziz , Karam Khairullah Mohammed , Karmila binti Kamil , Saad Mekhilef

Weather variations present a major challenge for photovoltaic (PV) systems in obtaining the optimal output during maximum power point tracking (MPPT), particularly under partial shadowing conditions (PSCs). Bypass diodes are typically installed across the series-connected PV modules to avoid the occurrence of the hotspots. Consequently, the power curve exhibits several local peaks (LPs) and one global peak (GP). The conventional MPPTs typically become stuck in one of these LPs, presenting a significant decrease in both the power output and overall efficiency of the PV system. A major constraint of several optimization techniques is their inability to differentiate between the irradiance fluctuations and load alterations. In this study, we analyze seven different methods for MPPT. These include: the team game algorithm (TGA), social ki driver algorithm (SSD), differential evolution (DE), grey wolf optimization (GWO), particle swarm optimization (PSO), cuckoo search (CS), and the perturb and observe (P&O) method. These algorithms were applied in practice, and their effectiveness was experimentally demonstrated under different amounts of solar irradiation while maintaining a constant temperature. The results indicate that the CS and TGA approaches can accurately track the MPPT across various positions on the P-V curve. These methods achieve average efficiencies of 99.59% and 99.54%, respectively. Additionally, the TGA achieves superior performance with the shortest average tracking time of 0.92 s, outperforming the existing MPPT algorithms.

天气变化是光伏系统在最大功率点跟踪（MPPT）期间获得最佳输出的主要挑战，特别是在部分阴影条件下（PSCs）。旁路二极管通常安装在串联的光伏模块上，以避免热点的发生。因此，功率曲线呈现出几个局部峰值（lp）和一个全局峰值（GP）。传统的mppt通常会卡在其中一个lp中，导致光伏系统的输出功率和整体效率显著下降。几种优化技术的一个主要限制是它们无法区分辐照度波动和负载变化。在本研究中，我们分析了七种不同的MPPT方法。这些算法包括：团队游戏算法（TGA）、社交ki驱动算法（SSD）、差分进化（DE）、灰狼优化（GWO）、粒子群优化（PSO）、布谷鸟搜索（CS）和扰动与观察（P&；O）方法。这些算法在实际应用中得到了验证，并在温度保持不变的情况下，在不同太阳辐照量下验证了算法的有效性。结果表明，CS和TGA方法可以准确地跟踪P-V曲线上不同位置的MPPT。这两种方法的平均效率分别为99.59%和99.54%。此外，TGA的平均跟踪时间最短，为0.92 s，优于现有的MPPT算法。

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引用次数: 0

Assessing the technical and economic potential of rooftop solar panels in Nador, Morocco, using advanced GIS methodology and remote sensing data 利用先进的地理信息系统方法和遥感数据，评估摩洛哥纳多尔屋顶太阳能板的技术和经济潜力

IF 2.6 Q4 ENERGY & FUELS

Global Energy Interconnection

Pub Date : 2025-08-01 DOI: 10.1016/j.gloei.2025.01.010

Rachid Lambarki , Elmostafa Achbab , Mehdi Maanan , Hassan Rhinane

The utilization of unused rooftops is a promising solution to meet the growing energy needs of urban areas. This study identifies the strategic locations for installing photovoltaic (PV) systems and assesses the energy production in Nador, Morocco, comparing various PV modules based on sunlight, while also integrating an economic analysis. A key innovation of this study lies in the novel application of LiDAR (Light Detection and Ranging) point clouds combined with photogrammetric restitution, enabling the construction of a 3D model of buildings. A Boolean multicriteria analysis was implemented to determine the effective surface area of each roof, considering parameters, such as slope, orientation, shadow, and accessibility, while excluding unsuitable buildings. A substantial area of 336 ha suitable for solar systems was identified, representing 61% of the total area of existing structures, with an average annual irradiation of 1,413.71 kWh/m². The CIS (copper/indium/selenium) PV module stands out as an attractive option, offering an energy capacity of 168.56 MWp and significant energy production of 311.35 GWh. Their moderate initial cost of 376.95 million USD makes them financially appealing with a feasible return on investment within 10 years. Environmentally, the CIS module contributes notably to reduced CO₂ emissions, thereby mitigating its environmental impact. By implementing the CIS module, solar energy production is expected to significantly exceed the estimated demand of the urban population. The data were integrated into a Geographic Information System to target roofs suitable for solar panels, forming the basis of an accurate solar cadastre. This study actively contributes to shaping a sustainable energy landscape by promoting environment-friendly solutions, thereby playing a role in transitioning to a more sustainable energy future in Nador.

利用未使用的屋顶是一个很有前途的解决方案，可以满足城市地区日益增长的能源需求。本研究确定了安装光伏（PV）系统的战略位置，并评估了摩洛哥纳多尔的能源生产，比较了基于阳光的各种光伏模块，同时也整合了经济分析。本研究的一个关键创新在于将LiDAR（光探测和测距）点云与摄影测量恢复相结合的新应用，使建筑三维模型的构建成为可能。采用布尔多标准分析来确定每个屋顶的有效表面积，同时考虑坡度、朝向、阴影和可达性等参数，同时排除不合适的建筑物。确定了适合太阳能系统的大量面积336公顷，占现有结构总面积的61%，年平均辐照量为1,413.71千瓦时/平方米。CIS（铜/铟/硒）光伏组件作为一种有吸引力的选择脱颖而出，提供168.56 MWp的能量容量和311.35 GWh的显著发电量。它们的初始成本为3.7695亿美元，适中，在10年内投资回报可行，具有经济吸引力。在环境方面，CIS模块有助于减少二氧化碳排放，从而减轻其对环境的影响。通过实施CIS模块，预计太阳能产量将大大超过城市人口的估计需求。这些数据被整合到地理信息系统中，以确定适合安装太阳能电池板的屋顶，形成准确的太阳地籍基础。这项研究通过推广环境友好型解决方案，积极促进塑造可持续能源景观，从而在向更可持续的能源未来过渡中发挥作用。

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引用次数: 0

Optimized control of grid-connected photovoltaic systems: Robust PI controller based on sparrow search algorithm for smart microgrid application 并网光伏系统优化控制：基于麻雀搜索算法的智能微电网鲁棒PI控制器

IF 2.6 Q4 ENERGY & FUELS

Global Energy Interconnection

Pub Date : 2025-08-01 DOI: 10.1016/j.gloei.2025.05.004

Youssef Akarne , Ahmed Essadki , Tamou Nasser , Maha Annoukoubi , Ssadik Charadi

The integration of renewable energy sources into modern power systems necessitates efficient and robust control strategies to address challenges such as power quality, stability, and dynamic environmental variations. This paper presents a novel sparrow search algorithm (SSA)-tuned proportional-integral (PI) controller for grid-connected photovoltaic (PV) systems, designed to optimize dynamic performance, energy extraction, and power quality. Key contributions include the development of a systematic SSA-based optimization framework for real-time PI parameter tuning, ensuring precise voltage and current regulation, improved maximum power point tracking (MPPT) efficiency, and minimized total harmonic distortion (THD). The proposed approach is evaluated against conventional PSO-based and P&O controllers through comprehensive simulations, demonstrating its superior performance across key metrics: a 39.47% faster response time compared to PSO, a 12.06% increase in peak active power relative to P&O, and a 52.38% reduction in THD, ensuring compliance with IEEE grid standards. Moreover, the SSA-tuned PI controller exhibits enhanced adaptability to dynamic irradiance fluctuations, rapid response time, and robust grid integration under varying conditions, making it highly suitable for real-time smart grid applications. This work establishes the SSA-tuned PI controller as a reliable and efficient solution for improving PV system performance in grid-connected scenarios, while also setting the foundation for future research into multi-objective optimization, experimental validation, and hybrid renewable energy systems.

将可再生能源整合到现代电力系统中，需要有效和稳健的控制策略来应对诸如电能质量、稳定性和动态环境变化等挑战。本文提出了一种新的麻雀搜索算法（SSA）调谐比例积分（PI）控制器，用于并网光伏（PV）系统，旨在优化动态性能，能量提取和电能质量。主要贡献包括开发了基于ssa的系统优化框架，用于实时PI参数调谐，确保精确的电压和电流调节，提高最大功率点跟踪（MPPT）效率，并最小化总谐波失真（THD）。通过综合仿真，将该方法与传统的基于PSO和P&；O控制器进行了对比，结果表明，该方法在关键指标上具有卓越的性能：响应时间比PSO快39.47%，峰值有功功率比P&；O提高12.06%，THD降低52.38%，确保符合IEEE电网标准。此外，ssa调谐PI控制器对动态辐照度波动的适应性增强，响应时间快，在不同条件下具有鲁棒的电网集成能力，非常适合实时智能电网应用。本研究确立了ssa调谐PI控制器作为提高并网场景下光伏系统性能的可靠、高效的解决方案，同时也为未来多目标优化、实验验证和混合可再生能源系统的研究奠定了基础。

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引用次数: 0

Signal processing and machine learning techniques in DC microgrids: a review 直流微电网中的信号处理和机器学习技术综述

IF 2.6 Q4 ENERGY & FUELS

Global Energy Interconnection

Pub Date : 2025-08-01 DOI: 10.1016/j.gloei.2025.05.002

Kanche Anjaiah , Jonnalagadda Divya , Eluri N.V.D.V. Prasad , Renu Sharma

Low-voltage direct current (DC) microgrids have recently emerged as a promising and viable alternative to traditional alternating current (AC) microgrids, offering numerous advantages. Consequently, researchers are exploring the potential of DC microgrids across various configurations. However, despite the sustainability and accuracy offered by DC microgrids, they pose various challenges when integrated into modern power distribution systems. Among these challenges, fault diagnosis holds significant importance. Rapid fault detection in DC microgrids is essential to maintain stability and ensure an uninterrupted power supply to critical loads. A primary challenge is the lack of standards and guidelines for the protection and safety of DC microgrids, including fault detection, location, and clearing procedures for both grid-connected and islanded modes. In response, this study presents a brief overview of various approaches for protecting DC microgrids.

低压直流（DC）微电网最近成为传统交流（AC）微电网的一种有前途和可行的替代方案，具有许多优点。因此，研究人员正在探索各种配置的直流微电网的潜力。然而，尽管直流微电网提供了可持续性和准确性，但当集成到现代配电系统中时，它们会带来各种挑战。在这些挑战中，故障诊断具有重要意义。直流微电网的快速故障检测对于维持稳定和确保关键负载的不间断供电至关重要。主要挑战是缺乏直流微电网保护和安全的标准和指南，包括并网和孤岛模式的故障检测、定位和清除程序。作为回应，本研究简要概述了保护直流微电网的各种方法。

引用次数: 0

Study on the investment and construction models and value assessment of shared energy storage in the context of the new power system 新型电力系统背景下共享储能投资建设模式及价值评估研究

IF 2.6 Q4 ENERGY & FUELS

Global Energy Interconnection

Pub Date : 2025-08-01 DOI: 10.1016/j.gloei.2025.07.002

Yuanying Chi, Zihang Jin, Xufeng Zhang, Yanzhao Zhang, Yuxi Wu, Junqi Wang

New energy-storage systems play a pivotal role in the development of the new power system for advancing the energy transition in China. In the “14th Five-Year Plan” for the New Energy-Storage Development, it is proposed to expand investment and construction models by promoting the deployment of energy-storage facilities through the ways of self-construction, leasing, and purchasing, and to encourage the development of the shared energy-storage. However, the current scarcity in the model of the shared energy-storage investment and construction substantially restricts its development, particularly due to unclear mechanisms for cost and benefit allocation, which also discourages potential investors. To address the issue, this paper proposes investment and construction models for shared energy-storage that aligns with the present stage of energy storage development. In specific, three main models are introduced: (1) Centralized Self-built Shared Energy-Storage model (CSSES), (2) Third-party Investment Shared Energy-Storage model (TISES), and (3) Distributed Self-built Shared Energy Storage (DSSES) model. The cost–benefit analysis is conducted for each model. The results indicate that the CSSES model achieves the highest internal rate of return (11.5%) and the shortest payback period, while the DSSES model performs acceptable with an IRR of 9.4%. In contrast, the TISES model shows the lowest IRR (6.7%) and requires higher electricity price for being feasible. Furthermore, the study employs the entropy weight method and the analytic hierarchy process (AHP) for indicator evaluation, and integrates the technique for order preference by the similarity to an ideal solution (TOPSIS) for scheme optimization. The results show that both the CSSES model and the DSSES model achieve the highest proximity scores. Under environmental regulations, these models demonstrate superior economic benefits by optimizing energy storage utilization, reducing user costs, and enhancing overall profitability.

新型储能系统在推进中国能源转型的新电力系统建设中起着举足轻重的作用。《新型储能发展“十四五”规划》提出，通过自建、租赁、购买等方式推动储能设施部署，拓展投资建设模式，鼓励共享储能发展。然而，目前共享储能投资建设模式的稀缺性极大地限制了其发展，特别是成本和收益分配机制不明确，这也使潜在投资者望而却步。针对这一问题，本文提出了与现阶段储能发展相适应的共享储能投资建设模式。具体介绍了三种主要模型：(1)集中式自建共享储能模型（cses）；(2)第三方投资共享储能模型（TISES）；(3)分布式自建共享储能模型（dses）。对每个模型进行成本效益分析。结果表明，cses模型的内部收益率最高（11.5%），投资回收期最短，而dses模型的内部收益率为9.4%，表现尚可。相比之下，TISES模型显示出最低的内部收益率（6.7%），并且需要更高的电价才能实现。在此基础上，采用熵权法和层次分析法进行指标评价，并结合与理想解相似度排序偏好技术进行方案优化。结果表明，cses模型和dses模型的接近性得分最高。在环保法规下，这些模式通过优化储能利用率，降低用户成本，提高整体盈利能力，显示出卓越的经济效益。

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引用次数: 0

Demand Response in power off-grid microgrids in Nigeria: a game theory approach 尼日利亚离网微电网的需求响应：博弈论方法

IF 2.6 Q4 ENERGY & FUELS

Global Energy Interconnection

Pub Date : 2025-08-01 DOI: 10.1016/j.gloei.2025.06.003

Racine Diatta, Rodica Loisel, Lionel Richefort

Most developing countries continue to face challenges in accessing sustainable energy. This study investigates a solar panel and battery-powered system for an urban off-grid microgrid in Nigeria, where demand-side flexibility and strategic interactions between households and utilities can optimize system sizing. A nonlinear programming model is built using bilevel problem formulation that incorporates both the households’ willingness to reduce their energy consumption and the utility’s agreement to provide price rebates. The results show that, for an energy community of 10 households with annual energy demand of 7.8 MWh, an oversized solar-storage system is required (12 kWp of photovoltaic solar panels and 26 kWh of battery storage). The calculated average cost of 0.31 €/kWh is three times higher than the current tariff, making it unaffordable for most Nigerian households. To address this, the utility company could implement Demand Response programs with direct load control that delay the use of certain appliances, such as fans, irons and air conditioners. If these measures reduce total demand by 5%, both the required system size and overall costs could decrease significantly, by approximately one-third. This adjustment leads to a reduced tariff of 0.20 €/kWh. When Demand Response is implemented through negotiation between the utility and households, the amount of load-shaving achieved is lower. This is because households experience discomfort from curtailment and are generally less willing to provide flexibility. However, negotiation allows for greater flexibility than direct control, due to dynamic interactions and more active consumer participation in the energy transition. Nonetheless, tariffs remain higher than current market prices. Off-grid contracts could become competitive if financial support is provided, such as low-interest loans and capital grants covering up to 75% of the upfront cost.

大多数发展中国家在获取可持续能源方面继续面临挑战。本研究调查了尼日利亚城市离网微电网的太阳能电池板和电池供电系统，其中家庭和公用事业之间的需求侧灵活性和战略互动可以优化系统规模。一个非线性规划模型是用双层问题公式建立的，其中包含了家庭减少能源消耗的意愿和公用事业公司提供价格回扣的协议。结果表明，对于一个由10户家庭组成的能源社区，年能源需求为7.8兆瓦时，需要一个超大的太阳能存储系统（12千瓦时的光伏太阳能电池板和26千瓦时的电池存储）。计算出的平均成本为0.31欧元/千瓦时，比目前的电价高出三倍，使大多数尼日利亚家庭无法负担。为了解决这个问题，公用事业公司可以实施需求响应计划，直接控制负荷，延迟使用某些电器，如风扇、熨斗和空调。如果这些措施将总需求减少5%，那么所需的系统大小和总成本都将显著减少，大约减少三分之一。这一调整导致电价降低0.20欧元/千瓦时。当需求响应通过公用事业和家庭之间的谈判来实施时，实现的减载量较低。这是因为家庭对限电感到不舒服，通常不太愿意提供灵活性。然而，由于动态互动和更积极的消费者参与能源转型，谈判比直接控制具有更大的灵活性。尽管如此，关税仍高于目前的市场价格。如果提供财政支持，如低息贷款和高达75%的前期成本的资本补助，离网合同将具有竞争力。

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引用次数: 0