International Journal of Electrical Power & Energy Systems最新文献_第10页

Research on impact of synchronous condenser excitation strategy based on PIDA controller and feedforward voltage control on transient voltage of grid 基于 PIDA 控制器和前馈电压控制的同步电容器励磁策略对电网暂态电压影响的研究

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

International Journal of Electrical Power & Energy Systems

Pub Date : 2024-10-02 DOI: 10.1016/j.ijepes.2024.110262

Xiaoling Yuan , Hanqing Ma , Can Cui , Mingyang Liu , Ze Gao

As grid-connected renewable energy and HVDC transmission grow in China, maintaining stable power grid operation is essential to avert system collapse caused by insufficient reserves of dynamic reactive power. Network topology and dynamic reactive power compensation device settings influence the transient voltage stability. Synchronous condenser (SC) serves as a dynamic reactive power source in modern energy AC/DC grids. However, the traditional SC excitation control strategy causes significant voltage overshoot during the voltage recovery process of the grid. This paper proposes a proportion-integral–differential-acceleration (PIDA) excitation controller which considers grid voltage feedforward for SC to improve FV type excitation control strategy to suppress transient voltage fluctuations, and the fruit fly optimization algorithm (FOA) is employed to tune the PIDA parameters. To verify the control effect, an improved IEEE14-node AC/DC hybrid system is proposed by using the PSCAD/EMTDC simulation platform, and variations in SC excitation voltage, DC transmission active power, reactive power output of SC (

Q_{sc}

), and AC bus voltage on the inverter side are compared and analyzed in three different excitation control strategies under three fault conditions. Simulation results show that the improved SC excitation control strategy proposed can not only suppress system bus voltage drop effectively and reduce the risk of DC commutation failure, but also reduce voltage overshoot by 6 % and voltage drop by 10 % compared with those of traditional excitation control strategies of SC, and make the system recover faster and effectively improve the power system voltage level and voltage stability.

随着中国可再生能源并网和高压直流输电的发展，保持电网稳定运行对于避免动态无功功率储备不足导致的系统崩溃至关重要。电网拓扑结构和动态无功补偿装置的设置会影响暂态电压稳定性。同步电容器（SC）是现代能源交直流电网中的动态无功功率源。然而，传统的 SC 励磁控制策略会在电网电压恢复过程中造成明显的电压过冲。本文提出了一种比例-积分-微分-加速（PIDA）励磁控制器，考虑了 SC 的电网电压前馈，以改进 FV 型励磁控制策略，从而抑制瞬态电压波动，并采用果蝇优化算法（FOA）来调整 PIDA 参数。为了验证控制效果，利用 PSCAD/EMTDC 仿真平台提出了一种改进的 IEEE14 节点交直流混合系统，并比较分析了三种故障条件下三种不同励磁控制策略对 SC 励磁电压、直流输电有功功率、SC 输出无功功率（Qsc）和逆变器侧交流母线电压的影响。仿真结果表明，所提出的改进型 SC 励磁控制策略不仅能有效抑制系统母线电压跌落，降低直流换向故障风险，而且与传统 SC 励磁控制策略相比，电压过冲降低了 6%，电压跌落降低了 10%，使系统恢复更快，有效改善了电力系统的电压水平和电压稳定性。

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引用次数: 0

High-impedance faulty feeder detection for cross-country faults in distribution networks based on zero-sequence active power regulation 基于零序有功功率调节的配电网跨国故障高阻抗馈线检测

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

International Journal of Electrical Power & Energy Systems

Pub Date : 2024-10-02 DOI: 10.1016/j.ijepes.2024.110264

Yuting Lan , Kun Yu , Xiangjun Zeng , Rong Cai , Qingbo Deng , Chenyu Wu , Shigeng He , Shijie Xu , Youcheng Jia

The weak characteristics of high-impedance faults and the complex attributes of cross-country faults make faulty feeder detection of cross-country high-impedance faults difficult in medium-voltage networks. This paper deduces the zero-sequence equivalent circuit of cross-country faults through a three-sequence two-port network, analyzes the influence of grounding resistance on cross-country faults, and then explores the limitations of the traditional passive feeder detection methods. Moreover, this paper proposes a novel faulty feeder detection method for cross-country high-impedance faults based on zero-sequence active power regulation. First, based on the zero-sequence current varying characteristics under the regulation of zero-sequence voltage, construct a continuous adjustment region of zero-sequence voltage within the feeder insulation tolerance range. Next, based on the zero-sequence active power varying characteristics in each feeder, propose a discriminant formula for the zero-sequence active power fluctuation coefficient. Finally, adjusting zero-sequence voltage can actively amplify the differences in zero-sequence active power fluctuations between healthy feeders and faulty feeders and accurately select faulty feeders of cross-country high-impedance faults in medium-voltage networks. Various fault conditions are simulated in the PSCAD/EMTDC simulation and field test to verify the effectiveness of the proposed method. The proposed method can accurately identify all faulty feeders of cross-country high-impedance faults in the medium-voltage distribution network.

高阻抗故障的微弱特性和跨国故障的复杂属性使得中压网络中跨国高阻抗故障的馈线检测变得困难。本文通过三序两端口网络推导出跨国故障的零序等效电路，分析了接地电阻对跨国故障的影响，进而探讨了传统无源馈线检测方法的局限性。此外，本文还提出了一种基于零序有功功率调节的新型跨国高阻抗故障馈线检测方法。首先，基于零序电压调节下的零序电流变化特性，在馈线绝缘容差范围内构建零序电压连续调节区域。其次，根据各馈线的零序有功功率变化特性，提出零序有功功率波动系数的判别式。最后，调整零序电压可以主动放大健康馈线与故障馈线之间的零序有功功率波动差异，准确选择中压电网跨国高阻抗故障的故障馈线。在 PSCAD/EMTDC 仿真中模拟了各种故障条件，并进行了现场测试，以验证所提方法的有效性。所提出的方法能准确识别中压配电网中跨国高阻抗故障的所有故障馈线。

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引用次数: 0

Multi-objective two-stage robust optimization of wind/PV/thermal power system based on meta multi-agent reinforcement learning 基于元多代理强化学习的风力/光伏/火力发电系统多目标两阶段鲁棒优化

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

International Journal of Electrical Power & Energy Systems

Pub Date : 2024-10-01 DOI: 10.1016/j.ijepes.2024.110273

Dengao Li , Zhuokai Zhang , Ding Feng , Yu Zhou , Xiaodong Bai , Jumin Zhao

The integration of renewable energy into the power grid poses significant challenges for optimization and scheduling of the power system. In recent years, methods based on deep reinforcement learning have surpassed traditional methods on the high complexity and long-term decision-making of power system optimization and scheduling. However, faced with the inherent uncertainty of renewable energy generation and the different optimization objectives in power system, the deep reinforcement learning methods are unable to effectively address them. This paper proposes a method that combines meta reinforcement learning with multi-agent reinforcement learning to solve the multi-objective two-stage robust optimization of wind/PV/thermal power system. We conducts optimization and scheduling experiments on the IEEE39 bus system. The results indicate that our method not only enhances the robustness of the scheduling strategy, but also outperforms baseline methods in terms of convergence, diversity, and uniformity of the Pareto frontier.

可再生能源并入电网给电力系统的优化和调度带来了巨大挑战。近年来，基于深度强化学习的方法在电力系统优化和调度的高复杂性和长期决策方面超越了传统方法。然而，面对可再生能源发电固有的不确定性和电力系统不同的优化目标，深度强化学习方法无法有效应对。本文提出了一种元强化学习与多代理强化学习相结合的方法，以解决风电/光伏/火电系统的多目标两阶段鲁棒优化问题。我们在 IEEE39 总线系统上进行了优化和调度实验。结果表明，我们的方法不仅增强了调度策略的鲁棒性，而且在收敛性、多样性和帕累托前沿均匀性方面优于基线方法。

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引用次数: 0

Distributed robust Lasso-MPC based on Nash optimization for smart grid: Guaranteed robustness and stability 基于纳什优化的分布式鲁棒 Lasso-MPC 适用于智能电网：保证鲁棒性和稳定性

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

International Journal of Electrical Power & Energy Systems

Pub Date : 2024-10-01 DOI: 10.1016/j.ijepes.2024.110248

Hossein Ahmadian, Heidar Ali Talebi, Iman Sharifi

The integration of variable renewable energy supplies into smart grid energy management poses several obstacles to system operation. An efficient solution for resource management is essential to ensuring reliable operation. This research presents distributed robust

L

asso-model predictive control (

D − RLMPC

) as a way to handle energy problems in a multi-layer and multi-time frame optimization method. The

D − RLMPC

is a hierarchical system that integrates a centralized supervisory management (

SM

) layer for long-term optimization with a distributed coordination management (

CM

) layer for short-term adaptation to high power fluctuations. The higher layer, known as the

SM

, is responsible for providing the grid operator with specific operating plans and offering guidance to the bottom layer, known as the

CM

. The

CM

is responsible for coordinating the interaction between the centralized optimization goals and the physical power system layer. Furthermore, a distributed extended Kalman filter (

DEKF

) is used to ascertain the inter-dependencies among subsystems. Next, an iterative approach based on

N

ash optimization is proposed to get the globally optimum solution of the whole system in a partly distributed manner. The simulation results demonstrate the effectiveness of the proposed control approach, which combines the advantages of centralized and distributed control to provide a comprehensive solution for the grid operating issue. To verify and assess the effectiveness of the suggested approach, the acquired outcomes are compared to those of the centralized robust, distributed robust, and distributed

MPC

approaches. The simulation findings confirm the practicality of using the suggested system to manage future smart grid assets.

将可变可再生能源供应纳入智能电网能源管理给系统运行带来了一些障碍。高效的资源管理解决方案对确保可靠运行至关重要。本研究提出了分布式鲁棒拉索模型预测控制（D - RLMPC），作为一种多层多时间框架优化方法来处理能源问题。D - RLMPC 是一个分层系统，集成了用于长期优化的集中式监督管理层（SM）和用于短期适应高功率波动的分布式协调管理层（CM）。上层（即 SM）负责向电网运营商提供具体的运行计划，并向下层（即 CM）提供指导。CM 负责协调集中优化目标与物理电力系统层之间的互动。此外，分布式扩展卡尔曼滤波器（DEKF）用于确定子系统之间的相互依赖关系。接着，提出了一种基于纳什优化的迭代方法，以部分分布式的方式获得整个系统的全局最优解。仿真结果证明了所提控制方法的有效性，该方法结合了集中控制和分布式控制的优势，为电网运行问题提供了全面的解决方案。为了验证和评估所建议方法的有效性，将所获得的结果与集中鲁棒、分布式鲁棒和分布式 MPC 方法的结果进行了比较。模拟结果证实了使用建议系统管理未来智能电网资产的实用性。

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引用次数: 0

Pilot protection for flexible HVDC transmission lines based on transient voltage ratio characteristics 基于暂态电压比特性的柔性高压直流输电线路先导保护

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

International Journal of Electrical Power & Energy Systems

Pub Date : 2024-09-29 DOI: 10.1016/j.ijepes.2024.110263

Zhijie Wang, Haifeng Li, Haotian Jin, Hainan Liu, Yuansheng Liang, Gang Wang

To address the problems of poor speed performance and the large influence of the distributed capacitance of traditional pilot differential protection, a pilot protection scheme based on the characteristics of the transient voltage waveform is proposed. First, the expression of the relationship between the fault voltage of the current-limiting reactor and the measuring point is derived. From the theoretical derivation, it can be inferred that for internal faults, the voltage ratio of the current-limiting reactor to the measuring point on both sides of the HVDC line is constant over a short period. For external faults, the voltage ratio of the current-limiting reactor to the measuring point varies exponentially on the fault side, while on the other side, it remains constant. Based on the above characteristics, the waveform characteristics of the voltage ratio of the current-limiting reactor to the measuring point are used to establish a protection criterion. A pilot protection scheme based on the standard deviation coefficient is proposed. The simulation results show that this method can reliably identify internal and external faults and has high sensitivity and selectivity. Moreover, this method is reliable for different types of faults and fault resistances. In addition, the proposed protection scheme can identify the type of fault in a short time window, requires a low sampling frequency, and does not require data synchronization.

针对传统先导差动保护速度性能差、分布电容影响大等问题，提出了一种基于瞬态电压波形特征的先导保护方案。首先，推导出限流电抗器故障电压与测量点之间的关系表达式。从理论推导中可以推断出，对于内部故障，高压直流线路两侧限流电抗器与测量点的电压比在短时间内是恒定的。对于外部故障，故障侧限流电抗器与测量点的电压比呈指数变化，而另一侧则保持不变。根据上述特征，限流电抗器与测量点电压比的波形特征可用于建立保护判据。提出了一种基于标准偏差系数的先导保护方案。仿真结果表明，这种方法可以可靠地识别内部和外部故障，并具有较高的灵敏度和选择性。此外，这种方法对于不同类型的故障和故障电阻都是可靠的。此外，所提出的保护方案能在很短的时间窗口内识别故障类型，采样频率要求低，且不需要数据同步。

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引用次数: 0

A novel short-term wind power scenario generation method combining multiple algorithms for data-missing wind farm Considering spatial-temporal correlativity 针对数据缺失风电场的多种算法相结合的新型短期风电场景生成方法考虑时空相关性

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

International Journal of Electrical Power & Energy Systems

Pub Date : 2024-09-27 DOI: 10.1016/j.ijepes.2024.110227

Yuhua Tan , Qian Zhang , Lei Shi , Nuo Yu , Zhe Qian

For newly-built or expanded wind farms with missing, insufficient or invalid wind power data, the existing methods often have limitations in describing their wind power characteristics and generating wind power scenarios. To this end, a novel effective short-term wind power scenario generation method is put forward in this paper, where similar data domain matching, transfer learning, conditional deep convolutions generative adversarial network (C-DCGAN) and parameter optimization are improved and combined in a unified framework with full consideration of the spatial–temporal correlativity among multiple adjacent wind farms. Specifically, a similar data domain matching process is firstly presented to quickly filter and purify the sufficient wind power data of adjacent wind farms, so as to extract their useful similar wind power characteristics. On this basis, an accurate wind power scenario generation model of data-missing wind farm can be constructed through transfer learning and C-DCGAN training. Then a constrained optimization model is proposed to control the noise parameter in order to obtain the short-term wind power scenarios for a specific day. After expounding the general principle and mathematical formulations of the proposed method, simulation studies and comparative analysis are conducted based on the WIND public dataset to verify the accuracy, effectiveness and superiority of the proposed method.

对于风电数据缺失、不足或无效的新建或扩建风电场，现有方法在描述其风电特性和生成风电场景方面往往存在局限性。为此，本文提出了一种新颖有效的短期风电场景生成方法，将相似数据域匹配、迁移学习、条件深度卷积生成式对抗网络（C-DCGAN）和参数优化进行改进，并在统一的框架下进行组合，充分考虑了多个相邻风电场之间的时空相关性。具体来说，首先提出了一种相似数据域匹配过程，以快速过滤和净化相邻风电场的充足风电数据，从而提取其有用的相似风电特征。在此基础上，通过迁移学习和 C-DCGAN 训练，构建缺失数据风电场的精确风电场景生成模型。然后提出一个约束优化模型来控制噪声参数，从而获得特定日期的短期风力发电情景。在阐述了所提方法的一般原理和数学公式后，基于 WIND 公共数据集进行了仿真研究和对比分析，以验证所提方法的准确性、有效性和优越性。

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引用次数: 0

Leveraging blockchain technology to enhance transparency and efficiency in carbon trading markets 利用区块链技术提高碳交易市场的透明度和效率

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

International Journal of Electrical Power & Energy Systems

Pub Date : 2024-09-25 DOI: 10.1016/j.ijepes.2024.110225

Ameni Boumaiza, Kenza Maher

The global energy sector is undergoing a significant transformation, driven by the emergence of ‘prosumers’ - individuals who generate and consume energy. This shift is redefining traditional roles and is propelled by a growing demand for sustainable and renewable energy. Prosumers utilize decentralized energy sources, such as solar panels and wind turbines, enhancing energy independence by producing their own energy and selling any surplus back to the grid. However, this decentralized landscape presents challenges in accurately tracking carbon emissions and establishing equitable pricing mechanisms. In response to these challenges, we propose an innovative blockchain-based peer-to-peer (P2P) trading platform for carbon allowances. This novel approach gives prosumers a decisive influence over energy pricing, ensuring a more equitable distribution of energy resources. The blockchain framework benefits from decentralization, promoting transparency, security, and an immutable record of energy transactions and carbon emissions. To evaluate the platform’s effectiveness, we will initiate a real-world pilot project within the Education City Community Housing (ECCH) to gather empirical data over one year. The pilot will involve various participants—including prosumers and traditional consumers—and will meticulously monitor energy production, consumption, and trading activities. By comparing this decentralized system with traditional energy models, we aim to assess its impact on carbon emissions, user satisfaction, and overall economic viability, paving the way for a sustainable energy future.

在 "专业消费者"--即生产和消费能源的个人--出现的推动下，全球能源行业正在经历一场重大变革。这种转变正在重新定义传统角色，并受到对可持续和可再生能源日益增长的需求的推动。Prosumers 利用太阳能电池板和风力涡轮机等分散能源，通过生产自己的能源并将剩余能源卖回电网，增强了能源的独立性。然而，这种分散式的格局给准确跟踪碳排放和建立公平的定价机制带来了挑战。为了应对这些挑战，我们提出了一个基于区块链的创新型点对点（P2P）碳配额交易平台。这种新颖的方法赋予了消费者对能源定价的决定性影响，确保了能源资源的更公平分配。区块链框架得益于去中心化，提高了能源交易和碳排放的透明度、安全性和不可更改的记录。为了评估该平台的有效性，我们将在教育城社区住房（ECCH）内启动一个实际试点项目，收集一年的经验数据。试点项目将有不同的参与者参与，包括专业消费者和传统消费者，并将对能源生产、消费和交易活动进行细致监控。通过将这种分散式系统与传统能源模式进行比较，我们旨在评估其对碳排放、用户满意度和整体经济可行性的影响，为可持续能源的未来铺平道路。

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引用次数: 0

Multifactor evaluation method of smart meter 智能电表的多因素评估方法

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

International Journal of Electrical Power & Energy Systems

Pub Date : 2024-09-25 DOI: 10.1016/j.ijepes.2024.110261

Tao Hu , Jian Ma , Xuewei Guo , Lixing Yang , Lintao Zhou , Junlei Huang , Chong Li

As an important terminal of smart grid, smart meter has the functions of equipment health monitoring and power metering. However, it is difficult to quantify the impact of factors such as ex-factory parameters, historical failure rates, electromagnetic interference when conducting an operational condition assessment. Therefore, in view of the large number of influencing factors and the difficulty in quantifying the degree of influence, an improved multifactor evaluation model for the operating status of smart meters is constructed. Firstly, a multifactor index system for evaluating the operating state of smart meters is constructed by analyzing the working mechanism and operating characteristics of smart meters. Then, an improved combinatorial weighting method is proposed by combining the subjective weight and the objective weight. The combinatorial weighting method is used to estimate the weight of factors in the health status evaluation of smart meters, and the improved multifactor evaluation method is presented to evaluate the health status of smart meters. Finally, an example is given to verify and analyze the proposed method. Compared with the other three methods, this method can provide effective evaluation results, and help guide targeted maintenance or replacement to improve the efficiency of smart meter detection.

作为智能电网的重要终端，智能电表具有设备健康监测和电能计量的功能。然而，在进行运行状态评估时，很难量化出厂参数、历史故障率、电磁干扰等因素的影响。因此，针对影响因素多、影响程度难以量化的问题，构建了一种改进的智能电表运行状态多因子评估模型。首先，通过分析智能电表的工作机理和运行特点，构建了智能电表运行状态的多因子评价指标体系。然后，结合主观权重和客观权重，提出了一种改进的组合权重法。利用组合加权法估算智能电表健康状况评价中各因素的权重，并提出改进的多因素评价方法来评价智能电表的健康状况。最后，举例验证和分析了所提出的方法。与其他三种方法相比，该方法能提供有效的评价结果，有助于指导有针对性的维护或更换，提高智能电表的检测效率。

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引用次数: 0

Enhancing MPPT efficiency in PV systems under partial shading: A hybrid POA&PO approach for rapid and accurate energy harvesting 提高部分遮阳下光伏系统的 MPPT 效率：快速准确能量采集的 POA&PO 混合方法

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

International Journal of Electrical Power & Energy Systems

Pub Date : 2024-09-25 DOI: 10.1016/j.ijepes.2024.110260

Hao Wang , Lin Li , Haoshen Ye , Weiwei Zhao

Partial shading in operational environments introduces multiple peaks in the output characteristics of photovoltaic (PV) systems, presenting significant challenges to energy harvesting. This study introduces a novel meta-heuristic algorithm, termed POA&PO, which aims to address the maximum power point tracking (MPPT) issues in PV systems. The algorithm capitalizes on the global search capability of the POA method to quickly pinpoint the range with the maximum power, followed by the fast convergence of the PO method to ensure both rapidity and accuracy of the solution. Extensive simulation tests, conducted in MATLAB/SIMULINK, have demonstrated the efficacy of the POA&PO algorithm, achieving an average tracking efficiency of 99.97 % with a convergence time of 0.3 s in step response tests; under the EN50530 test standard, the algorithm also showed sustained and stable tracking of ramp signals. Moreover, practical testing utilizing a new, low-cost indoor PV simulator confirmed the algorithm’s high performance under controlled conditions, yielding an average tracking efficiency of 97.03 % and a convergence time of 0.18 s. This paper highlights the capacity of the developed algorithm to reliably, accurately, and swiftly achieve high energy transfer efficiency. Additionally, the innovative and economical experimental testing methods employed are emphasized, contributing to the practical applicability and cost-effectiveness of the proposed solution.

运行环境中的部分遮挡会给光伏（PV）系统的输出特性带来多个峰值，从而给能量收集带来重大挑战。本研究介绍了一种新型元启发式算法，称为 POA&PO，旨在解决光伏系统中的最大功率点跟踪（MPPT）问题。该算法利用 POA 方法的全局搜索能力快速确定功率最大的范围，然后利用 PO 方法的快速收敛能力确保解决方案的快速性和准确性。在 MATLAB/SIMULINK 中进行的大量仿真测试证明了 POA&PO 算法的有效性，在阶跃响应测试中，该算法的平均跟踪效率达到 99.97%，收敛时间为 0.3 秒；在 EN50530 测试标准下，该算法还显示出对斜坡信号的持续稳定跟踪。此外，利用新型低成本室内光伏模拟器进行的实际测试证实了该算法在受控条件下的高性能，其平均跟踪效率为 97.03%，收敛时间为 0.18 秒。此外，本文还强调了所采用的创新而经济的实验测试方法，这有助于提高所提解决方案的实际适用性和成本效益。

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引用次数: 0

A decision-making model for joint energy and reserve scheduling of wind power producers with local intraday demand response exchange market 具有本地日内需求响应交换市场的风电生产商联合能源和储备调度决策模型

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

International Journal of Electrical Power & Energy Systems

Pub Date : 2024-09-24 DOI: 10.1016/j.ijepes.2024.110234

Ehsan Nokandi , Mostafa Vahedipour-Dahraie , Saeed Reza Goldani , Pierluigi Siano

In this paper, a three-stage stochastic bi-level optimization framework is presented for optimal participation of wind power producers (WPPs) in day-ahead (DA), intraday, and balancing markets. In this framework, to leverage demand response (DR) services, a peer-to-peer (P2P) energy trading platform is implemented that allows local load aggregators (LAs) to contribute to the intraday markets improving both LAs’ and WPP’s benefits. Participating in the intraday DR exchange (IDRX) market enables WPP to purchase DR services from LAs, to reduce the penalty cost on the deviation between the day-head bidding and the real-time dispatch. A Stackelberg game for the bi-level decision-making model captures the conflict of interests between the WPP and LAs, in which, the upper level seeks to maximize WPP profit, while the lower level aims to maximize LAs’ economic surplus. The bi-level model is converted into its equivalent single-level mixed-integer quadratic problem (MIQP) employing the Karush-Kuhn-Tucker (KKT) conditions and strong duality theorem. Simulation results show that participation of the WPP in the IDRX market and employing spinning reserve and DR services for compensating the uncertainties are greatly dependent on its risk preferences and increase its expected profit in all conditions, significantly.

本文提出了一个三阶段随机双级优化框架，用于优化风力发电商（WPP）在日前（DA）、当日和平衡市场中的参与。在该框架中，为了充分利用需求响应（DR）服务，实施了一个点对点（P2P）能源交易平台，允许本地负荷聚合器（LA）为日内市场做出贡献，从而提高 LA 和 WPP 的收益。参与日内 DR 交易（IDRX）市场使 WPP 能够从 LAs 处购买 DR 服务，以减少日内投标与实时调度之间偏差的惩罚成本。双层决策模型的 Stackelberg 博弈捕捉了 WPP 和 LA 之间的利益冲突，其中，上层寻求 WPP 利润最大化，而下层寻求 LA 经济盈余最大化。利用卡鲁什-库恩-塔克（KKT）条件和强对偶定理，将双层模型转换为等效的单层混合整数二次问题（MIQP）。仿真结果表明，水电厂参与 IDRX 市场以及使用旋转储备和 DR 服务来补偿不确定性在很大程度上取决于其风险偏好，并且在所有条件下都能显著增加其预期利润。

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引用次数: 0