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2021 IEEE/IAS Industrial and Commercial Power System Asia (I&CPS Asia)最新文献

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EV Fleet Charging Management Method Considering the Uncertainty of Passenger Travel Choice 考虑乘客出行选择不确定性的电动汽车车队收费管理方法
Pub Date : 2021-07-18 DOI: 10.1109/ICPSAsia52756.2021.9621499
Jinran Guo, Zhaohao Ding
Given that many countries have issued a series of policies to promote the development of electric vehicles (EVs), the amount of EVs is growing rapidly around the world. The charging behaviour of EVs is related to the transportation system, power grid and passenger travel. Considering the uncertainty of passenger travel choice, we establish a EV fleet charging management method in this paper to optimize the dispatch of EV fleet and minimize the total system cost. On the one hand, we design the EV routing mechanism and charging scheduling strategy based on the traffic condition and the limit of charging stations. On the other hand, the uncertainty of passenger travel choice resulted from the consumer preference is also proposed in this model, which greatly affect the operation condition of EVs. In addition, a numerical case study is utilized to verify the effectiveness of the proposed model.
由于许多国家出台了一系列政策来促进电动汽车的发展,全球电动汽车的数量正在快速增长。电动汽车的充电行为与交通系统、电网和乘客出行有关。考虑到乘客出行选择的不确定性,本文建立了电动汽车车队充电管理方法,以优化电动汽车车队的调度,使系统总成本最小化。一方面,基于交通状况和充电站限制,设计了电动汽车路由机制和充电调度策略;另一方面,该模型还提出了消费者偏好导致的乘客出行选择的不确定性,这将极大地影响电动汽车的运行状况。最后,通过数值算例验证了该模型的有效性。
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引用次数: 0
Distributed Optimal Dispatch of Regional Integrated Energy System Considering Electricity-Gas-Heating 考虑电-气供热的区域综合能源系统分布式优化调度
Pub Date : 2021-07-18 DOI: 10.1109/ICPSAsia52756.2021.9621710
Wenzhao Nie, Jing Wang, Yongkai Zhang, Zhipeng Qiu, Encheng Dong, Jian Chen
Taking account of day-ahead dispatch of electricity-gas-heating regional integrated energy system, the active power flow model of distribution network, heating network transmission equation and natural gas network model with the consideration of dynamic characteristics of natural gas are first established. Then, a day-ahead dispatch model is established aiming at minimizing the system economic cost. Considering the privacy and opacity of information between electricity-gas-heating entities, based on improved alternating direction multiplier method, a distributed optimization scheduling method is proposed. The augmented Lagrange function of the whole system is decomposed into three sub-problems of electricity, natural gas and heating for iterative solution. Finally, case study verified the effectiveness and validity of the proposed model and optimization method.
考虑电-气-热区域综合能源系统日前调度,首先建立了考虑天然气动态特性的配电网有功潮流模型、供热网络传输方程和天然气网络模型。然后,以系统经济成本最小为目标,建立了日前调度模型。考虑到电-气供热主体间信息的私密性和不透明性,基于改进的交变方向乘数法,提出了一种分布式优化调度方法。将整个系统的增广拉格朗日函数分解为电、气、热三个子问题进行迭代求解。最后,通过实例验证了所提模型和优化方法的有效性。
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引用次数: 0
Oscillation Coupling Analysis of MVDC Distribution System Based on Impedance Measurement 基于阻抗测量的MVDC配电系统振荡耦合分析
Pub Date : 2021-07-18 DOI: 10.1109/ICPSAsia52756.2021.9621732
Xueshen Zhao, Lin Zhu, Haolin Lu, Zhanfeng Deng, Jie Song, Li Guo
For medium-voltage DC (MVDC) distribution system, the MVDC bus voltage is prone to instability owing to the dynamic interaction among source, constant power load and cable. Based on the equivalent model of MVDC distribution system, the input and output impedance considering the cable are established in detail. In addition, the voltage closed-loop transfer function of the equivalent model is also established. Then, the instability mechanism of system oscillation caused by cable can be revealed intuitively. To address this oscillation issue, the input filter capacitor of constant power load is further increased, thus the oscillation instability of the system is suppressed effectively. Finally, PLECS based simulation verification have been provided.
在中压直流配电系统中,由于电源、恒负荷和电缆之间的动态相互作用,中压直流母线电压容易出现不稳定。在MVDC配电系统等效模型的基础上,详细建立了考虑电缆的输入、输出阻抗。此外,还建立了等效模型的电压闭环传递函数。从而直观地揭示了索引起系统振荡的失稳机理。为了解决这一振荡问题,进一步增大恒功率负载的输入滤波电容,从而有效地抑制了系统的振荡不稳定性。最后,给出了基于PLECS的仿真验证。
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引用次数: 0
Extension of Power Flow Algorithm in STEPS for AC/DC Hybrid Power Systems with VSC-MTDC 基于VSC-MTDC的交直流混合电力系统潮流算法在STEPS中的扩展
Pub Date : 2021-07-18 DOI: 10.1109/ICPSAsia52756.2021.9621554
Zhenhe Ma, Changgang Li, Hua Ye, Yutian Liu
The open-source simulation toolkit for electrical power systems (STEPS) was released in Github with power flow and dynamic simulation functions. However, voltage source converter based multi-terminal direct current (VSC-MTDC) was not supported in STEPS. In this paper, the steady-state model of VSC-MTDC is introduced with diverse control modes. Then, the AC/DC power flow algorithm with VSC-MTDC is designed with alternating iteration method. The controlled variables exceeding limits with different control modes are handled in the algorithm. Besides, a general data structure of VSC-MTDC is established based on PSS/E and realized in STEPS. Finally, Two cases with VSC-MTDC are tested to verify the feasibility and effectiveness of the designed algorithm.
电力系统的开源仿真工具包(STEPS)在Github上发布,具有功率流和动态仿真功能。然而,在STEPS中不支持基于电压源变换器的多端直流电(vcs - mtdc)。本文介绍了具有多种控制方式的VSC-MTDC稳态模型。然后,采用交替迭代法设计了基于VSC-MTDC的交直流潮流算法。该算法处理了不同控制方式下被控变量超出限制的情况。此外,基于PSS/E建立了VSC-MTDC的通用数据结构,并在STEPS中实现。最后,通过两个VSC-MTDC实例验证了所设计算法的可行性和有效性。
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引用次数: 1
Hybrid Deep Learning Gaussian Process for Deterministic and Probabilistic Load Forecasting 确定性和概率负荷预测的混合深度学习高斯过程
Pub Date : 2021-07-18 DOI: 10.1109/ICPSAsia52756.2021.9621428
Pengfei Zhao, Zhenyuan Zhang, Haoran Chen, Peng Wang
Various hybrid load forecasting models have been proposed in recent years, but they generally assign weights to individual forecasting models for optimal combinations and without taking full advantage of the strengths of each model. In this paper, a hybrid Deep Learning Gaussian Process (HDLGP) model for short-term deterministic and probabilistic load forecasting (DLF and PLF) is proposed. This model merges the predictive power of artificial neural networks (ANN) and the ability to handle uncertainty of Gaussian Process (GP) by a composite kernel. Firstly, we design a multi-layer perception (MLP) neural network to learn high fluctuating load data. Then a GP with a composite kernel is incorporated to capture the residuals based on MLP so that further boost accuracy of DLF, meanwhile performing high-quality probability density estimation. Our model guarantees both reliability and sharpness of the PLF. Verifying our proposed model based on the realistically available data, it indicates that our model outperforms the other list approaches both in DLF and PLF.
近年来提出了各种混合负荷预测模型,但它们一般都是为各个预测模型分配权重以获得最优组合,而没有充分发挥每个模型的优势。本文提出了一种用于短期确定性和概率负荷预测的混合深度学习高斯过程模型(HDLGP)。该模型结合了人工神经网络(ANN)的预测能力和复合核处理高斯过程(GP)不确定性的能力。首先,我们设计了一个多层感知(MLP)神经网络来学习高波动负荷数据。然后在基于MLP的残差捕获中引入带复合核的GP,进一步提高DLF的精度,同时进行高质量的概率密度估计。我们的模型保证了PLF的可靠性和清晰度。基于实际可用的数据验证了我们提出的模型,表明我们的模型在DLF和PLF方面都优于其他列表方法。
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引用次数: 1
Interval Probability Estimation of Wind Farm Cluster Ramp Events Based on Credal Network 基于credential网络的风电场集群坡道事件区间概率估计
Pub Date : 2021-07-18 DOI: 10.1109/ICPSAsia52756.2021.9621615
Wang Xinyi, Han Xueshan, Yang Ming, Yu Yixiao
Large-scale wind power integration makes the impact of wind power ramp events more impossible to ignore. Compared with single station prediction, cluster prediction can reflect the impact of power mutation on the power system more intuitively, and the prediction results are more conducive to the decision-making of dispatchers. Therefore, this paper proposed an imprecise probabilistic prediction method for wind farm cluster. Data dimensionality reduction was carried out through correlation analysis and principal component analysis to avoid problems such as excessive data dimension caused by too many input variables and the influence of calculation speed. The credal network (CN) was established to express the dependent relationship between wind farm cluster ramp events and evidence variables, and the conditional dependent relationship was statistically quantified by using the imprecise Dirichlet model (IDM). Finally, combined with meteorological information, the ramp events were classified and inferred in the form of probability intervals, and the prediction performance was evaluated by using evaluation indexes. In this paper, the validity of the method was verified by using the data of a wind farm cluster in Xinjiang.
大规模的风电并网使得风电坡道事件的影响更加不容忽视。与单站预测相比,集群预测能更直观地反映电力突变对电力系统的影响,预测结果更有利于调度员的决策。为此,本文提出了一种针对风电场集群的不精确概率预测方法。通过相关分析和主成分分析对数据进行降维,避免因输入变量过多导致数据维数过大,影响计算速度等问题。建立了表征风电场集群坡道事件与证据变量依赖关系的可信度网络(CN),并利用不精确Dirichlet模型(IDM)对条件依赖关系进行了统计量化。最后,结合气象信息,以概率区间的形式对斜坡事件进行分类推断,并利用评价指标对斜坡事件的预测效果进行评价。本文以新疆某风电场集群为例,验证了该方法的有效性。
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引用次数: 0
Multi-time Scale Co-optimization Scheduling of Integrated Energy System for Uncertainty Balancing 面向不确定性平衡的集成能源系统多时间尺度协同优化调度
Pub Date : 2021-07-18 DOI: 10.1109/ICPSAsia52756.2021.9621574
Zhenwei Zhang, Chengfu Wang, Ruiqi Wang, Guanghua Guo, Shuai Chen, Yan Wang
Secure and economic operation of the integrated energy system (IES) is challenged by the high level of the uncertainty and fluctuation introduced by wind power sources. In this paper, a multi-time scale co-optimization scheduling scheme of IES is proposed, which considers tracking the wind power uncertainty to achieve accurate power balance and optimal economic operation of the whole system. First, a multi-time scale co-optimization model framework is established, and the electric power system, natural gas system and district heating system are coordinated to achieve more flexibility in each time scale. In the day-ahead stage, the optimal unit commitment is determined, furthermore, the operation scheme is adjusted on a rolling basis to track the random fluctuation of wind power in the intra-day stage. In the real-time stage, model predictive control (MPC) is used to achieve precise control, which takes the intra-day scheme as a reference to minimize operating deviations. Besides, the auto regressive moving average (ARMA) model and scenario method are employed to represent the wind power uncertainty by typical scenarios with corresponding probabilities. Finally, simulation results on an IEEE39-NGS20-DHS21 test system demonstrate the superiority of the proposed method in operational economy and wind power utilization, and also verify the effectiveness of the method to satisfy the uncertainty balancing.
风力发电带来的高度不确定性和波动性对综合能源系统的安全和经济运行提出了挑战。本文提出了一种考虑风电不确定性跟踪的IES多时间尺度协同优化调度方案,以实现整个系统的准确功率平衡和最优经济运行。首先,建立多时间尺度协同优化模型框架,协调电力系统、天然气系统和区域供热系统,实现各时间尺度下更大的灵活性。在日前阶段确定最优机组承诺,滚动调整运行方案,跟踪日内风电的随机波动。在实时阶段,采用模型预测控制(MPC)实现精确控制,以日内方案为参考,使运行偏差最小化。采用自回归移动平均(ARMA)模型和情景法,用具有相应概率的典型情景来表示风电的不确定性。最后,在IEEE39-NGS20-DHS21测试系统上进行了仿真,验证了该方法在运行经济性和风电利用率方面的优越性,并验证了该方法在满足不确定性平衡方面的有效性。
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引用次数: 1
Optimal Operation of Isolated CCHP System Considering Time-Varying Weighting Factors 考虑时变加权因素的孤立式热电联产系统优化运行
Pub Date : 2021-07-18 DOI: 10.1109/ICPSAsia52756.2021.9621385
Kejing Duan, Wei Wang, Wu Wei, Zhenya Ji
Nowadays, comprehensive utilization of multiple forms of energy to improve energy efficiency is popularly concerned. To this end, an isolated combined cooling, heating and power (CCHP) system is deeply explored in this paper. Aiming for further optimization of the system according to characteristics of island operation mode, two integrated energy system (IES) evaluation indexes are taken as the objective function. Furthermore, a time-varying weight factor is proposed to calculate multi-objective function and optimize the system scheduling. Case study results demonstrate that the potential benefits of the proposed optimization strategy in terms of operation economics, energy utilization, as well as the load balancing of isolated system.
目前,综合利用多种形式的能源,提高能源效率受到普遍关注。为此,本文对隔离式冷热电联产系统进行了深入的研究。针对海岛运行模式的特点,以两个综合能源系统评价指标作为目标函数,对系统进行进一步优化。在此基础上,提出了一种时变权重因子来计算多目标函数并优化系统调度。实例分析结果表明,所提出的优化策略在运行经济性、能源利用率和隔离系统负载均衡方面具有潜在的效益。
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引用次数: 1
Research on Cost and Benefit of Demand Response Related Entities Based on System Dynamics 基于系统动力学的需求响应相关实体成本效益研究
Pub Date : 2021-07-18 DOI: 10.1109/ICPSAsia52756.2021.9621561
Jiaxin Zhao, M. Zeng, Xiaorui Qian, Zhipeng Zhong, Yongli Wang
Studying the cost-benefit of demand response is helpful for participants to understand their own input and benefit. The system dynamics method provides a more systematic, dynamic, and clear causal feedback solution for the cost-benefit analysis of demand response. Based on the analysis of the cost-benefit sources of demand response related entities, this paper applies the system dynamics method to the cost-benefit model of demand response, and verifies the rationality and effectiveness of the model through simulation examples, which provides theoretical reference value for the further development of demand response resources.
研究需求响应的成本效益有助于参与者了解自己的投入和收益。系统动力学方法为需求响应的成本效益分析提供了更系统、动态、清晰的因果反馈解决方案。本文在分析需求响应相关实体成本效益来源的基础上,将系统动力学方法应用于需求响应成本效益模型,并通过仿真算例验证了模型的合理性和有效性,为需求响应资源的进一步开发提供了理论参考价值。
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引用次数: 0
Stability Analysis of Single-Phase Full H-bridge DC-AC Converter with Considering Time Delay and Parasitic Inductance Based on Small-Signal Model 基于小信号模型的考虑时延和寄生电感的单相全h桥DC-AC变换器稳定性分析
Pub Date : 2021-07-18 DOI: 10.1109/ICPSAsia52756.2021.9621758
Huayv Ji, Fan Xie, Wenxun Xiao, Bo Zhang
With the development of renewable energy and distributed generation, DC-AC converters are widely used in the power system. For the safety of the power system, the analysis of the stability in the inverter is vital. For this issue, the small-signal model of the inverter is established in this paper. Some non-ideal components are investigated, like response delay time and the parasitic inductance of the resistance. This paper determines that these factors do affect the stability of the DC-AC converter. The slow-scale instability is detected by the small-signal analysis. In the final, the experimental device is carried out to verify the correctness of the investigation.
随着可再生能源和分布式发电的发展,直流-交流变换器在电力系统中得到了广泛的应用。逆变器的稳定性分析对电力系统的安全运行至关重要。针对这一问题,本文建立了逆变器的小信号模型。研究了一些非理想元件,如响应延迟时间和电阻的寄生电感。本文确定了这些因素确实会影响直流-交流变换器的稳定性。通过小信号分析来检测慢尺度不稳定性。最后进行了实验装置的设计,验证了研究的正确性。
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引用次数: 0
期刊
2021 IEEE/IAS Industrial and Commercial Power System Asia (I&CPS Asia)
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