Global Energy Interconnection最新文献

Adaptive VSG control of flywheel energy storage array for frequency support in microgrids 用于微电网频率支持的飞轮储能阵列自适应 VSG 控制

IF 1.9 Q4 ENERGY & FUELS

Global Energy Interconnection

Pub Date : 2024-10-01 DOI: 10.1016/j.gloei.2024.10.002

Penghui Ren , Jingwen Zheng , Liang Qin , Ruyin Sun , Shiqi Yang , Jiangjun Ruan , Kaipei Liu

The application of virtual synchronous generator (VSG) control in flywheel energy storage systems (FESS) is an effective solution for addressing the challenges related to reduced inertia and inadequate power supply in microgrids. Considering the significant variations among individual units within a flywheel array and the poor frequency regulation performance under conventional control approaches, this paper proposes an adaptive VSG control strategy for a flywheel energy storage array (FESA). First, by leveraging the FESA model, a variable acceleration factor is integrated into the speed-balance control strategy to effectively achieve better state of charge (SOC) equalization across units. Furthermore, energy control with a dead zone is introduced to prevent SOC of the FESA from exceeding the limit. The dead zone parameter is designed based on the SOC warning intervals of the flywheel array to mitigate its impact on regular operation. In addition, VSG technology is applied for the grid-connected control of the FESA, and the damping characteristic of the VSG is decoupled from the primary frequency regulation through power differential feedback. This ensures optimal dynamic performance while reducing the need for frequent involvement in frequency regulation. Subsequently, a parameter design method is developed through a small-signal stability analysis. Consequently, considering the SOC of the FESA, an adaptive control strategy for the inertia damping and the P/ω droop coefficient of the VSG control is proposed to optimize the grid support services of the FESA. Finally, the effectiveness of the proposed control methods is demonstrated through electromagnetic transient simulations using MATLAB/Simulink.

在飞轮储能系统（FESS）中应用虚拟同步发电机（VSG）控制是解决与微电网中惯性减小和供电不足有关的挑战的有效方案。考虑到飞轮阵列中各个单元之间的显著差异，以及传统控制方法下较差的频率调节性能，本文提出了飞轮储能阵列（FESA）的自适应 VSG 控制策略。首先，利用飞轮储能阵列模型，在速度平衡控制策略中集成了可变加速因子，以有效实现各单元之间更好的电荷状态（SOC）均衡。此外，还引入了带死区的能量控制，以防止 FESA 的 SOC 超过极限。死区参数是根据飞轮阵列的 SOC 警告间隔设计的，以减轻其对正常运行的影响。此外，还将 VSG 技术应用于 FESA 的并网控制，并通过功率差反馈将 VSG 的阻尼特性与主频率调节解耦。这样既能确保最佳的动态性能，又能减少频繁参与频率调节的需要。随后，通过小信号稳定性分析开发了一种参数设计方法。因此，考虑到 FESA 的 SOC，提出了 VSG 控制的惯性阻尼和 P/ω 下降系数的自适应控制策略，以优化 FESA 的电网支持服务。最后，通过使用 MATLAB/Simulink 进行电磁瞬态仿真，证明了所提控制方法的有效性。

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引用次数: 0

An overview of grid-forming technology and its application in new-type power system 电网形成技术及其在新型电力系统中的应用概述

IF 1.9 Q4 ENERGY & FUELS

Global Energy Interconnection

Pub Date : 2024-10-01 DOI: 10.1016/j.gloei.2024.10.003

Zehong Liu , Yu Sun , Chao Ma

To address the global climate crisis, achieving energy transitions is imperative. Establishing a new-type power system is a key measure to achieve CO₂ emissions peaking and carbon neutrality. The core goal is to transform renewable energy resources into primary power sources. The large-scale integration of high proportions of renewable energy sources and power electronic devices will dramatically change the operational mechanisms and control strategies of power systems. Existing wind and solar converters mostly adopt the grid-following control mode, which leads to significant challenges in system security and stability as it is insufficient to support the frequency and voltage of the grid. On the other hand, grid- forming control technology (GFM) can provide voltage and frequency support for the system, and thus becomes an effective measure to improve the inertia and damping characteristics of power systems. This paper illustrates the principles, control strategies, equipment types, application scenarios, and project implementation of grid-forming technology. The simulation and analysis based on a renewable-dominated real new-type power system show that GFM can significantly enhance the frequency and voltage support capacity of the power system, improve renewable energy accommodation capacity and grid transmission capacity under weak grid conditions, and play an important role in enhancing the stability and power supply reliability of renewable-dominated new-type power systems.

为应对全球气候危机，实现能源转型势在必行。建立新型电力系统是实现二氧化碳排放调峰和碳中和的关键措施。其核心目标是将可再生能源转化为一次能源。大规模集成高比例的可再生能源和电力电子设备，将极大地改变电力系统的运行机制和控制策略。现有的风能和太阳能变流器大多采用电网跟随控制模式，这种模式不足以支持电网的频率和电压，从而给系统的安全性和稳定性带来巨大挑战。另一方面，电网形成控制技术（GFM）可为系统提供电压和频率支持，从而成为改善电力系统惯性和阻尼特性的有效措施。本文阐述了电网成形技术的原理、控制策略、设备类型、应用场景和项目实施。基于以可再生能源为主的实际新型电力系统的仿真分析表明，GFM 可显著增强电力系统的频率和电压支持能力，提高弱电网条件下的可再生能源接纳能力和电网输送能力，对提高以可再生能源为主的新型电力系统的稳定性和供电可靠性具有重要作用。

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引用次数: 0

Optimization dispatching strategy for an energy storage system considering its unused capacity sharing 考虑未使用容量共享的储能系统优化调度策略

IF 1.9 Q4 ENERGY & FUELS

Global Energy Interconnection

Pub Date : 2024-10-01 DOI: 10.1016/j.gloei.2024.10.008

Hejun Yang , Zhaochen Yang , Siyang Liu , Dabo Zhang , Yun Yu

In renewable energy systems, energy storage systems can reduce the power fluctuation of renewable energy sources and compensate for the prediction deviation. However, if the renewable energy prediction deviation is small, the energy storage system may work in an underutilized state. To efficiently utilize a renewable-energy-sided energy storage system (RES), this study proposed an optimization dispatching strategy for an energy storage system considering its unused capacity sharing. First, this study proposed an unused capacity-sharing strategy for the RES to fully utilize the storage’s unused capacity and elevate the storage’s service efficiency. Second, RES was divided into “deviation-compensating energy storage (DES)” and “sharing energy storage (SES)” to clarify the function of RES in the operation process. Third, this study established an optimized dispatching model to achieve the lowest system operating cost wherein the unused capacity- sharing strategy could be integrated. Finally, a case study was investigated, and the results indicated that the proposed model and algorithm effectively improved the utilization of renewable-energy-side energy storage systems, thereby reducing the total operation cost and pressure on peak shaving.

在可再生能源系统中，储能系统可以减少可再生能源的功率波动，补偿预测偏差。然而，如果可再生能源预测偏差较小，储能系统可能会处于未充分利用状态。为了有效利用可再生能源侧储能系统（RES），本研究提出了一种考虑未使用容量共享的储能系统优化调度策略。首先，本研究提出了可再生能源储能系统的闲置容量共享策略，以充分利用储能系统的闲置容量，提高储能系统的服务效率。其次，将可再生能源分为 "偏差补偿储能（DES）"和 "共享储能（SES）"，以明确可再生能源在运行过程中的作用。第三，本研究建立了一个优化的调度模型，以实现最低的系统运行成本，其中可将闲置容量共享策略纳入其中。最后，进行了案例研究，结果表明所提出的模型和算法有效提高了可再生能源侧储能系统的利用率，从而降低了总运行成本和削峰压力。

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引用次数: 0

Economic analysis of hydrogen production from electrolyzed water technology by provinces in China 中国各省电解水制氢技术的经济分析

IF 1.9 Q4 ENERGY & FUELS

Global Energy Interconnection

Pub Date : 2024-10-01 DOI: 10.1016/j.gloei.2024.10.004

Xiao Han , Jiangpeng Feng , Yunhao Zhao , Wenlei Bai

A novel model for measuring the economics of hydrogen generation via electrolytic water projects was constructed. The model overcomes the current problem of incomplete and inaccurate assessments of the price of producing hydrogen via water, which are caused by ignoring the indirect carbon costs of different power generation sources in the process of determining the cost of producing hydrogen via water. The model was used to analyze the price of producing hydrogen via water electrolysis and its sensitivity to the electricity costs of hydrogen production and carbon prices in various provinces of China. With the continuing increase in the penetration of novel energy in China’s power system and the gradual decline in electricity prices, the price of producing hydrogen via electrolytic water is expected to be close to or even lower than that of producing hydrogen via coal in the future. Geographical differences also have a significant impact on the price of producing hydrogen, which is typically higher in the southeastern coastal region than in the western region, because of the local price of electricity and the composition of the energy sources. Provinces that have been effective in developing novel energy sources, such as Qinghai, Sichuan, and others, have been effective in the hydrogen energy industry. Sichuan and other provinces with significant new energy development have a clear advantage in the hydrogen industry. Because provinces with low hydrogen production costs can transport hydrogen to provinces with high hydrogen production costs through pipelines, hydrogen pipelines are planned from Shaanxi to Henan and from Xinjiang to Nei Mongol. These study results reveal the relative economic advantages of producing hydrogen via water electrolysis under various energy and electricity price policies and provide new perspectives on China’s energy strategy and the growth of the hydrogen energy sector.

我们建立了一个衡量电解水制氢项目经济性的新模型。该模型克服了目前由于在确定电解水制氢成本的过程中忽略了不同发电来源的间接碳成本而导致的对电解水制氢价格评估不全面和不准确的问题。该模型用于分析中国各省电解水制氢的价格及其对制氢电力成本和碳价格的敏感性。随着新型能源在中国电力系统中渗透率的不断提高以及电价的逐步下降，预计未来电解水制氢的价格将接近甚至低于煤炭制氢的价格。地域差异对制氢价格的影响也很大，由于当地的电价和能源构成，东南沿海地区的制氢价格通常高于西部地区。青海、四川等在开发新型能源方面卓有成效的省份，在氢能产业方面也卓有成效。四川等新能源发展成效显著的省份在氢能产业方面优势明显。由于制氢成本低的省份可以通过管道将氢气输送到制氢成本高的省份，因此规划了从陕西到河南、从新疆到内蒙古的氢气管道。这些研究结果揭示了在不同的能源和电价政策下，通过电解水制氢的相对经济优势，为中国的能源战略和氢能产业的发展提供了新的视角。

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引用次数: 0

Adaptive linear active disturbance-rejection control strategy reduces the impulse current of compressed air energy storage connected to the grid 自适应线性有源干扰抑制控制策略可降低并网压缩空气储能的脉冲电流

IF 1.9 Q4 ENERGY & FUELS

Global Energy Interconnection

Pub Date : 2024-10-01 DOI: 10.1016/j.gloei.2024.10.001

Jianhui Meng , Yaxin Sun , Zili Zhang

The merits of compressed air energy storage (CAES) include large power generation capacity, long service life, and environmental safety. When a CAES plant is switched to the grid-connected mode and participates in grid regulation, using the traditional control mode with low accuracy can result in excess grid-connected impulse current and junction voltage. This occurs because the CAES output voltage does not match the frequency, amplitude, and phase of the power grid voltage. Therefore, an adaptive linear active disturbance-rejection control (A-LADRC) strategy was proposed. Based on the LADRC strategy, which is more accurate than the traditional proportional integral controller, the proposed controller is enhanced to allow adaptive adjustment of bandwidth parameters, resulting in improved accuracy and response speed. The problem of large impulse current when CAES is switched to the grid-connected mode is addressed, and the frequency fluctuation is reduced. Finally, the effectiveness of the proposed strategy in reducing the impact of CAES on the grid connection was verified using a hardware-in-the-loop simulation platform. The influence of the k value in the adaptive- adjustment formula on the A-LADRC was analyzed through simulation. The anti-interference performance of the control was verified by increasing and decreasing the load during the presynchronization process.

压缩空气储能（CAES）具有发电量大、使用寿命长、环保安全等优点。当 CAES 发电站切换到并网模式并参与电网调节时，使用精度较低的传统控制模式可能会导致并网脉冲电流和结点电压过高。出现这种情况的原因是 CAES 输出电压与电网电压的频率、幅值和相位不匹配。因此，有人提出了一种自适应线性有源干扰抑制控制（A-LADRC）策略。与传统的比例积分控制器相比，线性有源干扰抑制控制策略的精度更高，在此基础上，对控制器进行了改进，允许对带宽参数进行自适应调节，从而提高了精度和响应速度。解决了 CAES 切换到并网模式时的大脉冲电流问题，并降低了频率波动。最后，利用硬件在环仿真平台验证了所提策略在减少 CAES 对并网影响方面的有效性。通过仿真分析了自适应调整公式中 k 值对 A-LADRC 的影响。通过在预同步过程中增加和减少负载，验证了控制的抗干扰性能。

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引用次数: 0

Optimal scheduling of zero-carbon park considering variational characteristics of hydrogen energy storage systems 考虑氢储能系统变异特性的零碳园区优化调度

IF 1.9 Q4 ENERGY & FUELS

Global Energy Interconnection

Pub Date : 2024-10-01 DOI: 10.1016/j.gloei.2024.10.007

Jun Yin , Heping Jia , Laijun Chen , Dunnan Liu , Shengwei Mei , Sheng Wang

Zero-carbon parks have broad prospects in carbon neutralization. As an energy hub, hydrogen energy storage plays an important role in zero-carbon parks. However, the nonlinear characteristics of hydrogen energy storage systems (HESSs) have a significant impact on the system economy. Therefore, considering the variable working condition characteristics of HESSs, a hybrid operation method is proposed for HESS, to support the efficient and economic operation of zero-carbon parks, by analyzing the operating principle of a zero-carbon park with HESS, the system structure framework and variable condition linearization model of the equipment in HESS are established. Moreover, considering the energy output characteristics of hydrogen energy storage equipment under variable working conditions, a multimodule hybrid operation strategy is proposed for electrolytic and fuel cells, effectively meeting the thermoelectric load demand of zero- carbon parks in different scenarios. Finally, the economy of the proposed hybrid operation strategy was verified in typical scenarios, using a zero-carbon park embedded with a HESS.

零碳园区在碳中和方面前景广阔。作为能源枢纽，氢储能在零碳园区中发挥着重要作用。然而，氢储能系统（HESS）的非线性特性对系统的经济性有很大影响。因此，考虑到氢储能系统的变工况特性，提出了氢储能系统的混合运行方法，通过分析零碳园区氢储能系统的运行原理，建立了氢储能系统的系统结构框架和设备的变工况线性化模型，为零碳园区的高效经济运行提供支持。此外，考虑到氢储能设备在变工况下的能量输出特性，提出了电解槽与燃料电池的多模块混合运行策略，有效满足了零碳园区在不同场景下的热电负荷需求。最后，利用一个嵌入了氢能储存设备的零碳园区，在典型场景下验证了所提出的混合运行策略的经济性。

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引用次数: 0

Optimal hydrogen-battery energy storage system operation in microgrid with zero-carbon emission 零碳排放微电网中氢电池储能系统的优化运行

IF 1.9 Q4 ENERGY & FUELS

Global Energy Interconnection

Pub Date : 2024-10-01 DOI: 10.1016/j.gloei.2024.10.006

Huayi Wu , Zhao Xu , Youwei Jia

To meet the greenhouse gas reduction targets and address the uncertainty introduced by the surging penetration of stochastic renewable energy sources, energy storage systems are being deployed in microgrids. Relying solely on short-term uncertainty forecasts can result in substantial costs when making dispatch decisions for a storage system over an entire day. To mitigate this challenge, an adaptive robust optimization approach tailored for a hybrid hydrogen battery energy storage system (HBESS) operating within a microgrid is proposed, with a focus on efficient state-of-charge (SoC) planning to minimize microgrid expenses. The SoC ranges of the battery energy storage (BES) are determined in the day- ahead stage. Concurrently, the power generated by fuel cells and consumed by electrolysis device are optimized. This is followed by the intraday stage, where BES dispatch decisions are made within a predetermined SoC range to accommodate the uncertainties realized. To address this uncertainty and solve the adaptive optimization problem with integer recourse variables in the intraday stage, we proposed an outer-inner column-and-constraint generation algorithm (outer-inner-CCG). Numerical analyses underscored the high effectiveness and efficiency of the proposed adaptive robust operation model in making decisions for HBESS dispatch.

为了实现减少温室气体排放的目标，并解决随机可再生能源激增所带来的不确定性，人们正在微电网中部署储能系统。在对储能系统进行全天调度决策时，仅依靠短期不确定性预测可能会导致大量成本。为了缓解这一挑战，我们提出了一种为在微电网中运行的混合氢电池储能系统（HBESS）量身定制的自适应稳健优化方法，重点关注高效的充电状态（SoC）规划，以最大限度地降低微电网成本。电池储能（BES）的 SoC 范围在日前阶段确定。同时，对燃料电池产生的电能和电解装置消耗的电能进行优化。随后是日内阶段，在这一阶段，BES 调度决策将在预定的 SoC 范围内做出，以适应已实现的不确定性。为了解决这种不确定性，并在日内阶段解决带有整数追索变量的自适应优化问题，我们提出了一种外-内列和约束生成算法（outer-inner-CCG）。数值分析表明，所提出的自适应稳健运行模型在 HBESS 调度决策中具有很高的有效性和效率。

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引用次数: 0

Enhancing photovoltaic power prediction using a CNN-LSTM-attention hybrid model with Bayesian hyperparameter optimization 利用贝叶斯超参数优化 CNN-LSTM-attention 混合模型加强光伏发电功率预测

IF 1.9 Q4 ENERGY & FUELS

Global Energy Interconnection

Pub Date : 2024-10-01 DOI: 10.1016/j.gloei.2024.10.005

Ning Zhou , Bowen Shang , Mingming Xu , Lei Peng , Guang Feng

Improving the accuracy of solar power forecasting is crucial to ensure grid stability, optimize solar power plant operations, and enhance grid dispatch efficiency. Although hybrid neural network models can effectively address the complexities of environmental data and power prediction uncertainties, challenges such as labor-intensive parameter adjustments and complex optimization processes persist. Thus, this study proposed a novel approach for solar power prediction using a hybrid model (CNN-LSTM-attention) that combines a convolutional neural network (CNN), long short- term memory (LSTM), and attention mechanisms. The model incorporates Bayesian optimization to refine the parameters and enhance the prediction accuracy. To prepare high-quality training data, the solar power data were first preprocessed, including feature selection, data cleaning, imputation, and smoothing. The processed data were then used to train a hybrid model based on the CNN-LSTM-attention architecture, followed by hyperparameter optimization employing Bayesian methods. The experimental results indicated that within acceptable model training times, the CNN-LSTM-attention model outperformed the LSTM, GRU, CNN-LSTM, CNN-LSTM with autoencoders, and parallel CNN-LSTM attention models. Furthermore, following Bayesian optimization, the optimized model demonstrated significantly reduced prediction errors during periods of data volatility compared to the original model, as evidenced by MRE evaluations. This highlights the clear advantage of the optimized model in forecasting fluctuating data.

提高太阳能发电预测的准确性对于确保电网稳定、优化太阳能发电厂运营和提高电网调度效率至关重要。虽然混合神经网络模型能有效解决环境数据和功率预测不确定性的复杂性，但仍面临着参数调整耗费大量人力和优化过程复杂等挑战。因此，本研究提出了一种利用混合模型（CNN-LSTM-注意力）进行太阳能发电预测的新方法，该模型结合了卷积神经网络（CNN）、长短期记忆（LSTM）和注意力机制。该模型采用贝叶斯优化方法来完善参数并提高预测精度。为了准备高质量的训练数据，首先对太阳能数据进行了预处理，包括特征选择、数据清理、估算和平滑。然后，利用处理后的数据训练基于 CNN-LSTM-attention 架构的混合模型，并采用贝叶斯方法进行超参数优化。实验结果表明，在可接受的模型训练时间内，CNN-LSTM-注意力模型优于 LSTM、GRU、CNN-LSTM、带自动编码器的 CNN-LSTM 和并行 CNN-LSTM 注意力模型。此外，经过贝叶斯优化后，与原始模型相比，优化模型在数据波动期的预测误差明显减少，这一点在 MRE 评估中得到了证明。这凸显了优化模型在预测波动数据方面的明显优势。

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引用次数: 0

Simulation and application analysis of a hybrid energy storage station in a new power system 新型电力系统中混合储能站的仿真与应用分析

IF 1.9 Q4 ENERGY & FUELS

Global Energy Interconnection

Pub Date : 2024-10-01 DOI: 10.1016/j.gloei.2024.10.012

Tianyu Zhang , Xiangjun Li , Hanning Li , hangyu Sun , Weisen Zhao

As the proportion of renewable energy infiltrating the power grid increases, suppressing its randomness and volatility, reducing its impact on the safe operation of the power grid, and improving the level of new energy consumption are increasingly important. For these purposes, energy storage stations (ESS) are receiving increasing attention. This article discusses the structure, working principle, and control methods of grid-following and grid-forming energy-storage converters, which are currently commonly used. A simulation analysis was conducted to investigate their dynamic response characteristics. The advantages and disadvantages of two types of energy storage power stations are discussed, and a configuration strategy for hybrid ESS is proposed. This paper presents research on and a simulation analysis of grid- forming and grid-following hybrid energy storage systems considering two types of energy storage according to different capacity scenarios. Finally, a comparative analysis between the systems is presented. A simulation model was established using PSD-BPA (Power System Department-Bonneville Power Administration) to analyze the impact of the capacity ratio of grid-following and grid-forming ESS on their dynamic response characteristics in a hybrid ESS. In addition, a development direction for future ESSs is indicated.

随着可再生能源渗入电网比例的增加，抑制其随机性和波动性、减少其对电网安全运行的影响以及提高新能源消费水平变得越来越重要。为此，储能站（ESS）受到越来越多的关注。本文讨论了目前常用的电网跟随型和电网形成型储能变流器的结构、工作原理和控制方法。并对其动态响应特性进行了仿真分析。讨论了两种储能电站的优缺点，并提出了混合型 ESS 的配置策略。本文介绍了电网形成和电网跟随混合储能系统的研究和仿真分析，根据不同的容量方案考虑了两种类型的储能。最后，还对这两种系统进行了比较分析。利用 PSD-BPA（电力系统部-邦纳维尔电力管理局）建立了一个仿真模型，以分析混合储能系统中电网跟随型和电网形成型储能系统的容量比对其动态响应特性的影响。此外，还指出了未来 ESS 的发展方向。

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引用次数: 0

Research on entropy weight variation evaluation method for wind power clusters based on dynamic layered sorting 基于动态分层排序的风电集群熵权变化评价方法研究

IF 1.9 Q4 ENERGY & FUELS

Global Energy Interconnection

Pub Date : 2024-10-01 DOI: 10.1016/j.gloei.2024.10.010

Yansong Gao , A. Lifu , Chenxu Zhao , Xiaodong Qin , Ri Na , An Wang , Shangshang Wei

This paper presents an evaluation method for the entropy-weighting of wind power clusters that comprehensively evaluates the allocation problems of wind power clusters by considering the correlation between indicators and the dynamic performance of weight changes. A dynamic layered sorting allocation method is also proposed. The proposed evaluation method considers the power-limiting degree of the last cycle, the adjustment margin, and volatility. It uses the theory of weight variation to update the entropy weight coefficients of each indicator in real time, and then performs a fuzzy evaluation based on the membership function to obtain intuitive comprehensive evaluation results. A case study of a large-scale wind power base in Northwest China was conducted. The proposed evaluation method is compared with fixed-weight entropy and principal component analysis methods. The results show that the three scoring trends are the same, and that the proposed evaluation method is closer to the average level of the latter two, demonstrating higher accuracy. The proposed allocation method can reduce the number of adjustments made to wind farms, which is significant for the allocation and evaluation of wind power clusters.

本文提出了一种风电簇熵权的评价方法，通过考虑指标间的相关性和权重变化的动态表现，综合评价风电簇的分配问题。同时还提出了一种动态分层排序分配方法。所提出的评价方法考虑了上一周期的限电度、调整裕度和波动性。它利用权重变化理论实时更新各指标的熵权系数，然后根据成员函数进行模糊评价，得到直观的综合评价结果。对中国西北某大型风电基地进行了案例研究。将所提出的评价方法与定权熵法和主成分分析法进行了比较。结果表明，三种方法的评分趋势相同，所提出的评价方法更接近后两种方法的平均水平，表现出更高的准确性。建议的分配方法可以减少对风电场的调整次数，这对风电集群的分配和评估意义重大。

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引用次数: 0