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2021 International Conference on power system Technology, powerCON 2021

作者： Liu, Hanghang You, Daning Cai, Yanbin Zhang, Guoqiang Wang, Hao Zhang, Li State Grid Shandong Electric Power Company Dongying Power Supply Company Dongying China State Grid Shandong Electric Power Company Power Dispatching Control Center Jinan China Shandong University Key Laboratory of Power System Intelligent Dispatch and Control Jinan China

ISBN: (纸本)9781665407373

The continuously increased renewable energy has brought tremendous pressure to the operation of power system. To enhance dispatching flexibility, it is necessary to build peak shaving market and include captive power plants in the transaction. Considering the peculiarity of captive power plants, a mechanism of captive power plants to participate in peak shaving auxiliary services market is proposed, in which the captive power plant must meet the enterprise's own demand for steam and heat when it takes part in market bidding and clearing. The mechanism is established on the basis of the provincial spot market, emphases are focused on declaration and settlement rules. Case studies show that the mechanism can make the captive power plant play its peak shaving role without affecting the production of the enterprise. Thus, the mechanism is practicable and promising in promoting the consumption of renewable energy. © 2021 IEEE.

关键词： Energy utilization

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Bi-Level Joint Planning of Transmission Network and Energy Storage system to Enhance Flexibility

Bi-Level Joint Planning of Transmission Network and Energy S...

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power Energy systems and Applications (ICoPESA), International Conference on

作者： Xiangfei Meng Yi Sun Shihao Zou Yongji Cao Hengxu Zhang Rui Liu Xian Wang Yao Wang Economic and Technological Research Institute of State Grid Shandong Electric Power Company Jinan China Key Laboratory of Power System Intelligent Dispatch and Control of the Ministry of Education Shandong University Jinan China Academy of Intelligent Innovation Shandong University Jinan China

The high proportion of renewable energies make the operation state of the power system more complicated. This paper proposes a bi-level joint planning approach considering the flexibility of the power system, which proposes for the transmission network and energy storage. By building a network flexibility index and adding a flexibility objective function, a bi-level optimization model is established to improve the power system flexibility and reducing investment cost. In addition, the outer model is solved by the snake optimization algorithm. The analysis results show that the joint planning model can effectively improve the flexibility of power system, and has economic advantages compared with the transmission lines expansion.

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Multi-stage power Source and Grid Coordination Planning Method Considering Grid Load Uniformity

Multi-stage Power Source and Grid Coordination Planning Meth...

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2020 IEEE/IAS Industrial and Commercial power system Asia, I and CPS Asia 2020

作者： Li, Zhiqi Han, Xueshan Yang, Ming Ma, Yiran Shandong University Key Laboratory of Power System Intelligent Dispatch and Control Jinan China

ISBN: (数字)9781728143033

ISBN: (纸本)9781728143033

In view of the increasing uncertainty of power supply and load, the concept of power source and grid coordination uniformity planning is proposed, and the standard deviation of transmission line load rate is taken as the uniformity evaluation index of power source and grid planning. A multi-stage and multi-objective optimization model of power source and grid expansion planning is established to minimize the comprehensive cost of the whole planning cycle. The improved PSO-GA hybrid algorithm is used to solve the model, which improves the efficiency of solution. The analysis of a simple IEEE garver-6 node system shows that the model and the solution method are effective and feasible, and are suitable for the coordinated planning of the power source and grid under the diversified development of power supply and load. © 2020 IEEE.

关键词： Multiobjective optimization

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Longitudinal Protection Method for AC/DC Hybrid system Based on Measuring Current Similarity

Longitudinal Protection Method for AC/DC Hybrid System Based...

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IEEE IAS Conference on Industrial and Commercial power system Asia (IEEE I and CPS Asia)

作者： Zhang, Hongzhe Cong, Wei Kong, Hao Chen, Ming Wei, Zhen Shandong Univ Minist Educ Key Lab Power Syst Intelligent Dispatch & Control Jinan Peoples R China State Grid Shandong Elect Power Co Qingdao Power Supply Co Qingdao Peoples R China

ISBN: (纸本)9781665434980

When a fault occurred on the tie line of the AC/DC hybrid system, the change rule of the current on the DC side is different from that of the traditional infinite AC power source. Traditional relay protection methods may meet the problem of low sensitivity and reliability. A longitudinal protection method for AC / DC hybrid system based on measuring current similarity is proposed. The method bases on the conclusion that the waveform characteristics of the measuring current at both sides of the line are different in the case of internal and external faults, determine the fault location through the Bhattacharyya distance method. The simulation results of PSCAD model show that the scheme in this paper can accurately identify the fault of the tie line of the AC/DC hybrid system, and has high reliability and good applicability.

关键词： AC/DC hybrid system longitudinal protection current similarity Bhattacharyya distance

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Optimal dispatch for cross-regional integrated energy system with renewable energy uncertainties: A unified spatial-temporal cooperative framework

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ENERGY 2024年 292卷

作者： Zhang, Zhenwei Wang, Chengfu Wu, Qiuwei Dong, Xiaoming Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Jinan 250061 Shandong Peoples R China Tsinghua Univ Tsinghua Berkeley Shenzhen Inst Tsinghua Shenzhen Int Grad Sch Shenzhen 518055 Peoples R China

Cross -regional energy sharing is a promising way to alleviate the imbalance in energy distribution. However, there is a risk that the uncertain fluctuations of intermittent renewable energy sources (RES) could be transmitted across regional transmissions, resulting in large-scale system economic inefficiency and security concerns. To this end, a unified spatial -temporal cooperative framework for the integrated energy system, which considers the coordination between intra-regional multi -energy coupling and cross -regional multi -agent -system energy sharing, is proposed in this paper. First, in the temporal dimension, a multi -time -scale stochastic decision -making model is established based on stochastic model predictive control (SMPC). Thus, slow -response units are arranged to gain economic goals in day -ahead stage and the closed -loop rolling adjustment is implemented on fastresponse units to achieve accuracy supply -demand balance in real-time stage. Second, in the spatial dimension, a fully distributed dispatch approach is adopted to address the information sharing barriers, which only requires neighboring information and considers consistency of boundary control variables on border lines. Finally, to improve the computational efficiency, the established complex time sequential model is decomposed into a set of time -discrete parallel sub -problems, using the optimal condition decomposition (OCD) technique. Simulation results on a cross -regional test system demonstrate that proposed framework can increase the wind power consumption capacity and reduce operation cost through cross -regional cooperation, while the parallel decomposition can save 67.25 % of the computation time relative to the serial computation.

关键词： Cross-regional energy sharing Multi-energy coupling Integrated energy system Optimal condition decomposition Stochastic model predictive control

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A Voltage Adaptive Dynamic Harmonic Model of Nonlinear Home Appliances

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2020年第5期67卷 3607-3617页

作者： Sun, Yuanyuan Xie, Xiangmin Zhang, Linghan Li, Shurong Shandong Univ Minist Educ Key Lab Power Syst Intelligent Dispatch & Control Sch Elect Engn Jinan 250061 Peoples R China

The widespread application of nonlinear power electronic devices in residential loads has resulted in significant harmonic distortions. Harmonic source modeling is of great importance since it is a prerequisite to estimate the harmonic pollution. In this paper, a dynamic harmonic coupled matrix model (HCMM) is proposed for the nonlinear home appliances. This model is adaptive to the load supply voltage conditions;therefore, the dynamic harmonic generating characteristics of nonlinear home appliances can be demonstrated by the proposed HCMM. Moreover, the HCMM derivation process is based on measurement, independent of the load equivalent circuit, which makes the proposed method most suitable for nonlinear home appliances with unknown circuit topologies. The widely linear complex partial least squares method, which has a fast speed and high robustness, is used to estimate the HCMM. A procedure to establish the HCMM for multistate home appliances is also proposed in this paper. lab experiments were performed to verify the accuracy and validity of the proposed methodology. The aggregate harmonics caused by multiple nonlinear residential loads have been analyzed based on the proposed HCMM.

关键词： Harmonic analysis Home appliances Load modeling power system harmonics Integrated circuit modeling Adaptation models Equivalent circuits Aggregate harmonics dynamic harmonic characteristics harmonic modeling home appliances

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SolarSAM: Building-scale photovoltaic potential assessment based on Segment Anything Model (SAM) and remote sensing for emerging city

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RENEWABLE ENERGY 2024年 237卷

作者： Li, Guanglei Wang, Guohao Luo, Tengqi Hu, Yuxiao Wu, Shouyuan Gong, Guanghui Song, Chenchen Guo, Zhiling Liu, Zhengguang Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Minist Educ Jinan 250061 Peoples R China Northwest A&F Univ Dept Power & Elect Engn Yangling 712100 Peoples R China Hong Kong Polytech Univ Dept Bldg Environm & Energy Engn Hung Hom Kowloon Hong Kong Peoples R China Ningbo Inst Digital Twin & Eastern Inst Technol Ningbo 315200 Peoples R China Beijing Informat Sci & Technol Univ Higher Informat Ind Technol Res Inst Beijing 100192 Peoples R China Univ Manchester Dept Chem Engn Manchester M13 9PL England

Driven by advancements in photovoltaic (PV) technology, solar energy has emerged as a promising renewable energy source due to its ease of integration onto building rooftops, facades, and windows. For emerging cities, the lack of detailed street-level data presents a challenge for effectively assessing the potential of buildingintegrated photovoltaic (BIPV). To address this, this study introduces SolarSAM, a novel BIPV evaluation method that leverages satellite imagery and deep learning techniques, and an emerging city in northern China is utilized to validate the model performance. SolarSAM segmented various building rooftops using text promptguided semantic segmentation during the process. Separate PV models were then developed for Rooftop PV, Facade-integrated PV, and PV windows, using this segmented data and local climate information. The potential for BIPV installation, solar power generation, and city-wide power self-sufficiency were assessed, revealing that the annual BIPV power generation potential surpassed the city's total electricity consumption by a factor of 2.5. Economic and environmental analysis were also conducted for the BIPVs on different buildings;the levelized cost of electricity is 0.18-0.41 CNY/kWh, and the annual total carbon reduction is 7.08 x 107 T CO2. These findings demonstrated the model's performance and revealed the potential for BIPV power generation.

关键词： Potential assessment Building-integrated photovoltaic Semantic segmentation Satellite imagery

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Two-Mode Balancing control Scheme for Modular DC/DC Converter Interfaced Battery Swapping Stations

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IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION 2025年第1期11卷 1640-1651页

作者： Ma, Zhan Gao, Feng Li, Wei Jia, Ming Wasylowski, David Lv, Qi Gao, Xiongying Zhou, Xin Uwe Sauer, Dirk Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Minist Educ Jinan 250061 Peoples R China Rhein Westfal TH Aachen Inst Power Elect & Elect Drives ISEA Chair Electrochem Energy Convers & Storage Syst D-52074 Aachen Germany Shandong Univ Sch Control Sci & Engn Jinan 250061 Peoples R China Southchip Semicond Technol Co Ltd Shanghai 201210 Peoples R China Rhein Westfal TH Aachen Inst Power Elect & Elect Drives ISEA Flexible Elekt Netze FEN GmbH Aachen 52074 Germany Rhein Westfal TH Aachen Inst Power Generat & Storage Syst PGS EON ERC Aachen 52074 Germany Rhein Westfal TH Aachen Inst Power Elect & Elect Drives ISEA Chair Electrochem Energy Convers & Storage Syst Aachen 52074 Germany Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China Yangzhou Huading Elect Co Ltd Yangzhou 225127 Peoples R China

In comparison to the traditional structure, the utilization of the modular dc/dc converter (MDDC) for integrating power battery packs in electric vehicle (EV) battery swapping stations (BSSs) presents notable advancements in cost-effectiveness, conversion efficiency, and stability. This article introduces a two-mode balancing control scheme tailored for the state-of-charge (SoC) differences due to the distinctive plug-and-play operation of BSS. First, the proposed scheme efficiently addresses high swapping demands by expediting the generation of full battery packs using a sorting selection control during the on-grid mode. Subsequently, during the off-grid mode, a flexible energy transfer loop, incorporating the dc inductor, capacitor, and submodules (SMs), enhances balancing capabilities through an internal circulation control. It can effectively address scenarios with low swapping demands where there is a shortage of battery packs that are not fully charged. Moreover, the proposed method ensures equal switching loss distribution and accelerates balancing speed, adding to its appeal. The practical validation of the proposed scheme is achieved through a 1-kW/1-kWh MDDC-BSS prototype equipped with 16 SMs.

关键词： Battery balancing battery swapping modular dc/dc converter (MDDC) state-of-charge (SoC) Battery balancing battery swapping modular dc/dc converter (MDDC) state-of-charge (SoC)

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A hybrid machine learning and meta-heuristic algorithm based service restoration scheme for radial power distribution system

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INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY systemS 2021年第6期31卷 p1-25页

作者： Srivastava, Ishan Bhat, Sunil Thadikemalla, Venkata Sainath Gupta Singh, Arvind R. Visvesvaraya Natl Inst Technol Elect Engn Dept Nagpur Maharashtra India VRSEC Dept Elect & Commun Engn Vijayawada India Shandong Univ Sch Elect Engn Key Lab Power Syst Intelligent Dispatch & Control Minist Educ Jinan Peoples R China

In-service Restoration (SR), the healthy section of the feeder can be re-energized by finding the optimal path for power flow. Through conventional methods which are mainly deterministic in nature, the computational burden is very high. Therefore, researchers have proposed various meta-heuristic based methods to solve the SR problem. But since, these methods are probability based;one single algorithm cannot guarantee optimal solution for all scenarios. Hence, the authors have proposed a Machine Learning (ML) based framework, which can predict the best SR scheme for a particular fault scenario among the SR solutions obtained through various meta-heuristic algorithms. The supervised ML model is developed using the fault features as input values and the best performing meta-heuristic algorithm as the target value. To check the validity of the ML framework, the authors have taken four different meta-heuristic algorithms, which are, Enhanced Integer Coded Particle Swarm Optimization (EICPSO), Shuffled Frog Leaping Algorithm (SFLA), Non-Dominated Sorting Genetic Algorithm-II (NSGA-II), and Ant Colony Optimization (ACO) algorithm. The ML model can be extended for any number of algorithms. Multi-class Support Vector Machine (SVM) algorithm is used as the estimator in the current work to train and test the developed model. The results obtained through SVM are 95.95% accuracy, 94% precision, and 94% f1-score. The performance of SVM is better when compared with other state-of-the-art ML estimators namely K-Nearest Neighbor (KNN), Random Forest (RF), and Logistic Regression (LR). The experiment is conducted for IEEE 33 bus and IEEE 69 bus test systems. A total of 320 fault instances are created using power system Computer-Aided Design (PSCAD) software. The features of these fault points are used as input for the ML model which is extracted using a discrete wavelet transform. This study is conducted for the balanced radial test system.

关键词： distribution automation expert system machine learning meta‐ heuristic techniques power distribution power system optimization service restoration support vector machine

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Probabilistic Planning of Transmission Network Considering Operational Flexibility of power system

Probabilistic Planning of Transmission Network Considering O...

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Smart power & Internet Energy systems (SPIES), International Conference on

作者： Jianjie Li Ping Li Peng Li Junshao Guo Mingqiang Wang Binzhou Electric Company Binzhou China Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Shandong University Jinan China

The uncertainties about equipment failure will bring great challenges to the operation of transmission network. Therefore, it is important for transmission network to possess sufficient flexibility to accommodate the fluctuation of load and deal with unit failures. This paper proposes a probabilistic planning model of transmission network considering operational flexibility, which makes decision-making optimization for transmission network planning and reduces the influence of uncertainties about equipment failure. Moreover, the proposed model introduces the probability and expectation of up-flexibility-not-supplied (UFNS) and expected-energy-not-supplied (EENS), then uses penalty cost to quantify them, which enhances the reliability and economy of transmission network planning. Furthermore, the absolute value linearization method is used to linearize the expectation of UFNS and EENS, which greatly improves the calculation efficiency. The proposed model is solved using the CPLEX solver in General Algebraic Modeling system (GAMS). The practicality of model is verified by the IEEE-RTS system.

关键词： Uncertainty Fluctuations Probabilistic logic Software Planning power system reliability Software reliability

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