International Journal of Electrical Power & Energy Systems最新文献_第2页

Technical assessment of solar energy storage investments with recommender system-enhanced quantum picture fuzzy rough sets 利用推荐系统增强的量子图模糊粗糙集对太阳能储存投资进行技术评估

IF 5 2区工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

International Journal of Electrical Power & Energy Systems

Pub Date : 2024-11-10 DOI: 10.1016/j.ijepes.2024.110361

Gang Kou , Hasan Dinçer , Serhat Yüksel , Serkan Eti , Merve Acar

The performance of solar energy storage projects should be improved by taking appropriate actions. However, there are very different criteria that affect the performance of these investments. Therefore, businesses need to focus on more important criteria to use the budget effectively and efficiently. This situation increases the need for a priority analysis for performance indicators of solar energy storage investments. Accordingly, the purpose of this study is to make evaluation for the technical assessment of solar energy storage investments. In this scope, a new four-stage model is introduced by considering different decision-making techniques and fuzzy sets. The first stage is related to the prioritizing the experts with artificial intelligence (AI)-based decision-making method. Secondly, the missing evaluations of solar energy storage investments are estimated with expert recommender system. In the following part, the criteria for the technical assessment of solar energy storage investments are weighted by quantum picture fuzzy rough sets (QPFRS) adopted M−SWARA. The final stage consists of ranking the solar energy storage alternatives with QPFR-VIKOR. The main contribution of this study is the generation of the decision matrix by the help of AI. This situation gives an opportunity to calculate the significance weights of the experts. Therefore, the analysis results can be more reliable and coherent. It is concluded that battery capacity is the most critical factor for the technical assessment of solar energy storage investments. On the other hand, pumped hydro for mechanic energy is found as the most significant solar energy storage alternative. Governments should provide the necessary incentives for the development of high-capacity battery technologies. In this context, tax reductions can be provided to companies that invest in production technologies. This contributes to the cost efficiency of businesses.

应通过采取适当行动提高太阳能储存项目的性能。然而，影响这些投资绩效的标准大不相同。因此，企业需要关注更重要的标准，以便有效和高效地使用预算。在这种情况下，更有必要对太阳能储能投资的绩效指标进行优先分析。因此，本研究的目的是对太阳能储能投资的技术评估进行评价。在此范围内，通过考虑不同的决策技术和模糊集，引入了一个新的四阶段模型。第一阶段是利用基于人工智能（AI）的决策方法对专家进行优先排序。其次，利用专家推荐系统估算太阳能储能投资的缺失评价。接下来，采用 M-SWARA 的量子图模糊粗糙集（QPFRS）对太阳能储能投资的技术评估标准进行加权。最后，利用 QPFR-VIKOR 对太阳能储能备选方案进行排序。本研究的主要贡献在于借助人工智能生成了决策矩阵。这种情况为计算专家的重要性权重提供了机会。因此，分析结果可以更加可靠和一致。结论是，电池容量是太阳能储能投资技术评估的最关键因素。另一方面，用于机械能的抽水蓄能被认为是最重要的太阳能储能替代方案。各国政府应为开发高容量电池技术提供必要的激励措施。在这方面，可以为投资生产技术的公司提供税收减免。这有助于提高企业的成本效益。

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引用次数: 0

Interruption characteristic of self-triggering low voltage hybrid DC circuit breaker with non-polarized bidirectional breaking 非极化双向分断的自触发低压混合直流断路器的分断特性

IF 5 2区工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

International Journal of Electrical Power & Energy Systems

Pub Date : 2024-11-09 DOI: 10.1016/j.ijepes.2024.110348

Jianning Yin, Xiaojian Lang, Yongyong Zhao, Jiandong Duan

The global new photovoltaic installed capacity reached 345.5GW in 2023. As the installed capacity of photovoltaic power generation systems increases worldwide, there is a growing demand for circuit breakers to withstand higher voltages on the DC side of these systems. A self-triggering hybrid circuit breaker with non-polarized bidirectional breaking is proposed. The distinguishing feature of this structure is conduction of the IGBT is determined by arc voltage. In addition, the non-polarized bidirectional arc-breaking is realized by the new transfer branch structure. To closely replicate the actual interruption process, a semi-physical simulation is used to validate the breaking performance. The breaking of 15kA fault current under DC1500V can be realized. Compared with the mechanical circuit breaker for PV system, the peak current of the breaking fault decreased, and shorten the interruption time by the self-triggering hybrid DC circuit breaker, which effectively improves the service life. And the factors affecting interruption characteristics are also analyzed. According to the MOPSO algorithm, the stray inductance of transfer branch getting little and the reference voltage of MOV is set to 3.7 kV is the best. The self-triggering hybrid DC circuit has applications in higher voltage level systems, which leads to new concepts for circuit breaker schemes using hybrid structures in future PV systems.

2023 年，全球新增光伏发电装机容量将达到 345.5GW。随着全球光伏发电系统装机容量的增加，对能承受这些系统直流侧更高电压的断路器的需求也在不断增长。本文提出了一种非极化双向分断的自触发混合断路器。这种结构的显著特点是 IGBT 的导通由电弧电压决定。此外，非极化双向断弧是通过新的转移支路结构实现的。为了接近实际的断路过程，我们采用了半物理仿真来验证断路性能。在 DC1500V 电压下，可实现 15kA 故障电流的分断。与光伏系统机械断路器相比，自触发混合直流断路器分断故障峰值电流降低，分断时间缩短，有效提高了使用寿命。同时还分析了影响分断特性的因素。根据 MOPSO 算法，传递支路的杂散电感变小，MOV 的参考电压设为 3.7 kV 为最佳。自触发混合直流电路可应用于更高电压等级的系统，这为未来光伏系统中使用混合结构的断路器方案提供了新的概念。

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引用次数: 0

Analysis of the applicability and results of swarm intelligence tools for the positioning of Energy Storage Systems 分析蜂群智能工具对储能系统定位的适用性和结果

IF 5 2区工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

International Journal of Electrical Power & Energy Systems

Pub Date : 2024-11-09 DOI: 10.1016/j.ijepes.2024.110343

Asier Divasson-J , Itxaso Aranzabal Santamaria , Miren T. Bedialauneta Landaribar , Paula Castillo Aguirre

The integration of renewable energy is transforming traditional energy systems, blurring the distinction between producers and consumers and shifting towards a distributed grid network. This change demands innovative approaches to optimize Energy Storage Systems (ESS) and manage grid incidents efficiently, all without significant infrastructural changes. While optimization algorithms like Swarm Intelligence are gaining traction, critical aspects, such as worst-case scenario analysis in distribution networks, remain underexplored. This study addresses this gap by applying stochastic optimization techniques to determine the optimal placement and capacity of ESS in a medium voltage radial distribution system, using the IEEE 33-bus model. The findings highlight the importance of considering worst-case scenarios, offering a balanced evaluation of current methodologies. This research provides valuable insights for improving system flexibility and resilience, contributing to more effective and practical energy optimization strategies in real-world applications.

可再生能源的整合正在改变传统的能源系统，模糊了生产者和消费者之间的区别，并向分布式电网网络转变。这种变化要求采用创新方法来优化储能系统（ESS）并有效管理电网事故，而所有这一切都无需对基础设施进行重大改造。虽然像蜂群智能这样的优化算法正受到越来越多的关注，但配电网络中的最坏情况分析等关键方面仍未得到充分探索。本研究针对这一空白，采用随机优化技术，利用 IEEE 33 总线模型，确定中压径向配电系统中 ESS 的最佳位置和容量。研究结果强调了考虑最坏情况的重要性，并对当前方法进行了平衡评估。这项研究为提高系统灵活性和恢复能力提供了宝贵的见解，有助于在实际应用中制定更有效、更实用的能源优化策略。

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引用次数: 0

Learning-based flexible load aggregation for secondary frequency regulation in co-simulated transmission and distribution networks 基于学习的灵活负载聚合，用于共同模拟输配电网络中的二次频率调节

IF 5 2区工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

International Journal of Electrical Power & Energy Systems

Pub Date : 2024-11-08 DOI: 10.1016/j.ijepes.2024.110339

Mengtong Chen , Qinran Hu , Tao Qian , Xinyi Chen , Rushuai Han , Yongxu Zhu

Aggregated flexible loads offer a promising solution for secondary frequency regulation (SFR) in power systems with increasing intermittent renewable energy sources. However, uncertainties in users’ behaviors may create a mismatch between the aggregated power of flexible loads and the control target of SFR. Furthermore, as these loads are dispersed across distribution networks, distribution network’s topology and its interplay with the transmission network may affect the performance of aggregated flexible loads in SFR. Therefore, this paper proposes an adaptive combinatorial multi-armed bandit (CMAB) flexible load aggregation strategy to enhance SFR performance in co-simulated transmission and distribution (T&D) networks. First, a dynamic T&D co-simulation framework is proposed based on the HELICS platform. Then, the combinatorial upper confidence bound-average (CUCB-Avg)-based CMAB algorithm is employed to manage users’ uncertain responses. Case studies on the IEEE 14-bus system with five IEEE 8,500-node feeders demonstrate the effectiveness of the proposed framework and method. The SFR performance of the proposed strategy based on CUCB-Avg algorithm outperforms the average and CUCB strategies in terms of accuracy, rapidity, robustness, and the number of affected users.

在间歇性可再生能源日益增多的电力系统中，聚合灵活负载为二次频率调节（SFR）提供了一种前景广阔的解决方案。然而，用户行为的不确定性可能会导致柔性负载的聚合功率与 SFR 的控制目标不匹配。此外，由于这些负载分散在配电网络中，配电网络的拓扑结构及其与输电网络的相互作用可能会影响 SFR 中聚合灵活负载的性能。因此，本文提出了一种自适应组合多臂匪式（CMAB）柔性负载聚合策略，以提高共同模拟输电和配电（T&D）网络中的 SFR 性能。首先，基于 HELICS 平台提出了动态 T&D 协同仿真框架。然后，采用基于组合置信上限-平均值（CUCB-Avg）的 CMAB 算法来管理用户的不确定响应。对带有五个 IEEE 8,500 节点馈线的 IEEE 14 总线系统进行的案例研究证明了所提框架和方法的有效性。基于 CUCB-Avg 算法的拟议策略的 SFR 性能在准确性、快速性、鲁棒性和受影响用户数量方面均优于平均策略和 CUCB 策略。

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引用次数: 0

A distributed MILP framework to coordinate restoration of transmission and distribution systems under imperfect communication 在通信不完善的情况下协调恢复输配电系统的分布式 MILP 框架

IF 5 2区工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

International Journal of Electrical Power & Energy Systems

Pub Date : 2024-11-08 DOI: 10.1016/j.ijepes.2024.110342

Lizhou Jiang , Binye Ni , Xinlei Cai , Jinzhou Zhu , Longteng Wu , Tianyang Zhao , Gengfeng Li

This paper proposes a novel distributed framework to restore transmission and distribution systems (T&DS) under imperfect communication. First of all, nodal reserve is introduced into the power exchange constraint, thereby making the coordination between transmission systems (TS) and distribution systems (DS) more efficiently to achieve. However, the above formulation undermines the convexity of the model since constraints regarding reserve response involve bi-linear terms. In this regard, a novel linearization method, with guaranteed accuracy and limited complexity, is proposed to reformulate the coordinated model into a mixed-integer linear programming problem. To solve this problem, a primal decomposition-based distributed framework is developed. Then, this paper takes imperfect communication into consideration and adopts data prediction methods to encounter this kind of issue. We theoretically prove that the distributed framework is guaranteed to converge under imperfect communication with the proposed strategy. Finally, the effectiveness and scalability of the proposed framework are verified by numerical experiments.

本文提出了一种新颖的分布式框架，用于在通信不完善的情况下恢复输配电系统（T&DS）。首先，在电力交换约束中引入节点储备，从而更有效地实现输电系统（TS）和配电系统（DS）之间的协调。然而，由于有关储备响应的约束涉及双线性项，上述表述破坏了模型的凸性。为此，我们提出了一种新颖的线性化方法，在保证精度和有限复杂度的前提下，将协调模型重新表述为混合整数线性规划问题。为了解决这个问题，本文开发了一个基于基元分解的分布式框架。然后，本文考虑了通信不完善的问题，并采用数据预测方法来解决这类问题。我们从理论上证明，采用所提出的策略，分布式框架能保证在不完全通信条件下收敛。最后，我们通过数值实验验证了所提框架的有效性和可扩展性。

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引用次数: 0

Day-ahead strategic bidding of multi-energy microgrids participating in electricity, thermal energy, and hydrogen markets: A stochastic bi-level approach 参与电力、热能和氢气市场的多能源微电网的日前战略竞标：双层随机方法

IF 5 2区工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

International Journal of Electrical Power & Energy Systems

Pub Date : 2024-11-07 DOI: 10.1016/j.ijepes.2024.110319

Jiahua Wang , Zhentong Shao , Jiang Wu , Lei Wu

This paper proposes a stochastic strategic bidding approach for a multi-energy microgrid (MEMG) to optimize its participation across electricity, thermal energy, and hydrogen markets. A MEMG powered entirely by renewable energy and integrating these three energy forms is designed using advanced energy conversion and storage technologies. A bi-level model is developed: in the upper level, the MEMG’s bidding strategies are optimized to maximize profits under operational constraints and market demands; in the lower level, detailed pricing mechanisms for each energy market are modeled, incorporating physical constraints and market competition. To address uncertainties in renewable energy generation, a chance-constrained approach is employed to mitigate potential market penalties. Moreover, a novel cost estimation method enables the MEMG to effectively price energy during trading. The bi-level problem is transformed into a tractable mixed-integer linear programming (MILP) problem using the Karush–Kuhn–Tucker conditions and linearization techniques. Numerical results show that the MEMG efficiently participates in multiple energy markets, reducing renewable energy curtailment and adjusting its trading strategies based on market conditions, thereby improving overall economic benefits.

本文为多能源微电网（MEMG）提出了一种随机战略竞标方法，以优化其在电力、热能和氢气市场的参与。本文采用先进的能源转换和存储技术，设计了一个完全由可再生能源驱动并集成这三种能源形式的 MEMG。我们开发了一个双层模型：在上层，优化 MEMG 的投标策略，以便在运营约束和市场需求下实现利润最大化；在下层，结合物理约束和市场竞争，为每个能源市场的详细定价机制建模。针对可再生能源发电的不确定性，采用了机会约束方法来减轻潜在的市场惩罚。此外，一种新颖的成本估算方法使 MEMG 能够在交易过程中有效地为能源定价。利用卡鲁什-库恩-塔克条件和线性化技术，将双层问题转化为一个简单易行的混合整数线性规划（MILP）问题。数值结果表明，MEMG 有效地参与了多个能源市场，减少了可再生能源缩减，并根据市场情况调整了交易策略，从而提高了整体经济效益。

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引用次数: 0

Coordinated planning for offshore wind and electricity–hydrogen system based on SDDP: A case study of coastal provinces in China 基于 SDDP 的海上风电-氢能系统协调规划：中国沿海省份案例研究

IF 5 2区工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

International Journal of Electrical Power & Energy Systems

Pub Date : 2024-11-07 DOI: 10.1016/j.ijepes.2024.110341

Tao Qian , Qiyu Wu , Qinran Hu , Zishan Guo , Zaijun Wu

The coordinated development of offshore wind and electricity–hydrogen systems (OW-EHS) has the potential to enhance the utilization of renewable energy sources and achieve carbon neutrality. This article presents a case study of nine coastal provinces in China and designs four scenarios to analyze the economic benefits and potential hydrogen production capacity of OW-EHS. A multi-stage stochastic dual dynamic programming based approach is proposed for integrating OW-EHS, exploring offshore wind energy as both a primary electricity source for coastal regions and a clean, sustainable energy source for electrolyzers. It accounts for variations in hydrogen demand, wind uncertainty, load profiles, and electricity price dynamics, offering a holistic perspective on the feasibility and benefits of collaborative offshore wind and electricity–hydrogen systems. A comparative analysis highlights the effectiveness of the proposed planning approach, demonstrating its capacity to maximize the overall system benefits, encompassing both the optimal levelized cost of energy and hydrogen production. The new discoveries elucidate the unique attributes and advantages of each coastal province in OW-EHS. This research provides a tailored blueprint for coastal provinces in China to harness their offshore wind potential and accelerate progress towards carbon neutrality.

海上风电氢系统（OW-EHS）的协调发展具有提高可再生能源利用率和实现碳中和的潜力。本文以中国沿海九省为案例，设计了四种情景，分析了海上风电制氢系统的经济效益和潜在制氢能力。文章提出了一种基于多阶段随机二元动态编程的方法来整合 OW-EHS，探索海上风能作为沿海地区主要电力来源和电解槽清洁、可持续能源的可能性。该方法考虑了氢气需求、风力不确定性、负荷曲线和电价动态等方面的变化，为海上风电-氢气协作系统的可行性和效益提供了一个全面的视角。对比分析凸显了所提规划方法的有效性，证明其有能力最大化整个系统的效益，包括最优化的平准化能源成本和制氢成本。新发现阐明了沿海省份在 OW-EHS 中的独特属性和优势。这项研究为中国沿海省份利用其海上风电潜力和加快实现碳中和提供了量身定制的蓝图。

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引用次数: 0

Variable droop gain frequency supporting control with maximum rotor kinetic energy utilization for wind-storage system 为风力存储系统提供可变垂降增益频率支持控制，实现转子动能最大化利用

IF 5 2区工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

International Journal of Electrical Power & Energy Systems

Pub Date : 2024-11-06 DOI: 10.1016/j.ijepes.2024.110289

Wenbo Li , Yujun Li , Jiapeng Li , Yang Zhang , Xiqiang Chang , Zhongqing Sun

To address the emerging frequency stability issue brought by the large replacement of synchronous generators with renewable generations, wind turbine generators are required to possess frequency-supporting capability. However, existing frequency-supporting control strategies lack the assessment of the frequency support capability of wind turbine generators, leading to degraded control performance under various situations. Aiming to solve this problem, this paper proposes a variable-droop-gain control for wind turbine generators with maximum rotor kinetic energy utilization. Firstly, an analytical relationship was established between droop gain, disturbance scale, and rotor speed. Subsequently, the released energy of the wind turbine generator is evaluated, which equals the difference in the rotor kinetic energy under the initial and the post-disturbance steady-state rotor speed. It was proved that the released kinetic energy cannot exceed a certain proportion of total rotor kinetic energy. Accordingly, a variable initial gain scheme is proposed, which determines the initial droop gain as per the disturbance scale for maximizing the kinetic energy release of wind turbines. Moreover, an additional real-time droop gain adjustment rule is added to prevent the over-deceleration of wind turbines. The simulation results show that the proposed scheme may provide the maximum KE release and effectively improve the system frequency nadir while ensuring the safe operation of wind turbine generators.

为解决可再生能源大量替代同步发电机带来的频率稳定问题，要求风力涡轮发电机具备频率支持能力。然而，现有的频率支持控制策略缺乏对风力发电机频率支持能力的评估，导致在各种情况下控制性能下降。为了解决这一问题，本文提出了转子动能利用最大化的风力涡轮发电机变垂增益控制。首先，建立了下垂增益、干扰尺度和转子速度之间的分析关系。随后，对风力发电机的释放能量进行了评估，释放能量等于初始和扰动后稳态转子速度下转子动能的差值。实践证明，释放动能不能超过转子总动能的一定比例。因此，提出了一种可变初始增益方案，根据扰动尺度确定初始垂降增益，以最大限度地释放风力发电机的动能。此外，还增加了一个额外的实时下垂增益调整规则，以防止风机过度减速。仿真结果表明，所提出的方案可提供最大的动能释放，并在确保风力发电机安全运行的同时有效改善系统频率低点。

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引用次数: 0

Size optimization of standalone wind-photovoltaics-diesel-battery systems by Harris hawks optimization (HHO): Case study of a wharf located in Bushehr, Iran 利用 Harris Hawks 优化法（HHO）优化独立风力-光伏-柴油-电池系统的规模：伊朗布什尔一个码头的案例研究

IF 5 2区工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

International Journal of Electrical Power & Energy Systems

Pub Date : 2024-11-06 DOI: 10.1016/j.ijepes.2024.110353

Kamyar Fakhfour, Fathollah Pourfayaz

The global increase in energy demand has led to a growing focus on renewable energy sources as a potential solution. This study examines the annual total cost of optimized off-grid hybrid multi-resource systems, considering various configurations of Wind Turbines (WT), Photovoltaics (PV), Diesel Generators (DG), and Batteries (Bat). The research focuses on an oil dock in Bushehr, Iran, as a case study. The optimization process employs the Harris Hawk Optimization (HHO) algorithm – which is used for the first time for hybrid configuration and optimal sizing in this paper-, a nature-inspired, population-based optimization technique. This algorithm’s performance is compared to conventional optimization methods to assess its efficiency. The study’s methodology involves: (1) Explaining the economic relationships for each energy source, (2) Formulating a cost function, (3) Using the HHO algorithm to minimize the total cost of the renewable energy-based hybrid systems. The HHO algorithm is inspired by the hunting behavior of Harris hawks, specifically their “wonder attack” strategy. This novel approach to optimization aims to find the most cost-effective configuration of energy sources for the given scenario. Key findings of the study include the HHO algorithm demonstrated superior efficiency compared to Particle Swarm Optimization (PSO) and Gray Wolf Optimizer (GWO) across all configurations tested. The most cost-effective configuration was found to be a combination of photovoltaics, batteries, and diesel generators. This setup had the lowest total annual cost among all configurations examined. The optimal system consisted of 450 photovoltaic units, 9 battery units, and 2 diesel generator units, with a minimum annual cost of approximately $355,525. These results highlight the potential of the HHO algorithm in optimizing renewable energy systems and demonstrate the complex trade-offs between cost and environmental impact in hybrid energy configurations. The study contributes valuable insights to the field of renewable energy system design and optimization, particularly for off-grid applications in industrial settings.

随着全球能源需求的增长，可再生能源作为一种潜在的解决方案日益受到关注。本研究考虑了风力涡轮机 (WT)、光伏 (PV)、柴油发电机 (DG) 和电池 (Bat) 的各种配置，考察了优化离网混合多资源系统的年度总成本。研究以伊朗布歇赫尔的一个石油码头为案例。优化过程采用 Harris Hawk Optimization (HHO) 算法，这是一种受自然启发、基于群体的优化技术，在本文中首次用于混合配置和优化尺寸。该算法的性能与传统优化方法进行了比较，以评估其效率。研究方法包括：（1）解释每种能源的经济关系；（2）制定成本函数；（3）使用 HHO 算法最小化基于可再生能源的混合系统的总成本。HHO 算法的灵感来自哈里斯鹰的狩猎行为，特别是它们的 "奇袭 "策略。这种新颖的优化方法旨在为给定场景找到最具成本效益的能源配置。研究的主要发现包括：与粒子群优化（PSO）和灰狼优化器（GWO）相比，HHO 算法在所有测试配置中都表现出更高的效率。最具成本效益的配置是光伏、电池和柴油发电机的组合。在所有测试的配置中，该配置的年总成本最低。最佳系统由 450 个光伏单元、9 个电池单元和 2 个柴油发电机单元组成，最低年成本约为 355525 美元。这些结果凸显了 HHO 算法在优化可再生能源系统方面的潜力，并证明了混合能源配置中成本与环境影响之间的复杂权衡。这项研究为可再生能源系统设计和优化领域，特别是工业环境中的离网应用，提供了宝贵的见解。

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引用次数: 0

Robust contingency-constrained load restoration method for transmission systems considering modified SOCP formulation of power flow 考虑修改后的电力流 SOCP 公式的输电系统鲁棒性突发事件约束负荷恢复方法

IF 5 2区工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

International Journal of Electrical Power & Energy Systems

Pub Date : 2024-11-06 DOI: 10.1016/j.ijepes.2024.110345

Lei Sun , Weikang Fang , Youwang Wei , Zhenzhi Lin , Xudong Jin

A proper load restoration method can speed up the load restoration phase and reduce the outage losses of power systems after natural disasters. Existing research assumes that transmission lines would not trip again in the load restoration phase, which is not always acceptable, especially in the outage scenario due to natural disasters. Besides, the feasibility of the load restoration scheme relies on an exact mathematical model of the load restoration problem, while the existing second-order cone programming (SOCP) based model is not suitable for transmission power systems due to the lack of voltage angle related arctangent constraints. To address these two main drawbacks in existing research on load restoration, a robust contingency-constrained load restoration model (CCLRM) for transmission systems considering the modified SOCP formulation of power flow is proposed with the objective of reducing the outage losses taking the worst contingency into account. To identify the worst contingency for the CCLRM, a bi-level worst contingency identification model (WOCIM) is proposed and reformulated into a single-level model by employing the duality theory to make the WOCIM solvable. The non-linear voltage angle related arctangent constraints in the modified SOCP based power flow expression in both models are studied and reformulated into the convex ones based on the convex envelope theory, thereby enhancing the accuracy of the presented models. Case studies on the IEEE 30-bus power system and IEEE 118-bus power system are conducted to illustrate the effectiveness of the proposed method.

适当的负荷恢复方法可以加快负荷恢复阶段的速度，减少自然灾害后电力系统的停电损失。现有研究假设输电线路在负荷恢复阶段不会再次跳闸，但这并不总是可以接受的，尤其是在自然灾害造成停电的情况下。此外，负载恢复方案的可行性依赖于负载恢复问题的精确数学模型，而现有的基于二阶锥编程（SOCP）的模型由于缺乏与电压角相关的反正切约束，并不适合输电系统。针对现有负荷恢复研究中存在的这两大弊端，我们提出了一种适用于输电系统的鲁棒性突发事件约束负荷恢复模型（CCLRM），该模型考虑了修改后的电力流 SOCP 公式，目的是在考虑最坏突发事件的情况下减少停电损失。为识别 CCLRM 的最坏意外情况，提出了一个双级最坏意外情况识别模型（WOCIM），并通过使用对偶理论使 WOCIM 可求解，将其重新表述为一个单级模型。研究了这两种模型中基于 SOCP 的修改功率流表达式中与电压角相关的非线性正切约束，并根据凸包络理论将其重新表述为凸约束，从而提高了所提出模型的精度。对 IEEE 30 总线电力系统和 IEEE 118 总线电力系统进行了案例研究，以说明所提方法的有效性。

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引用次数: 0