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Zuyi Li
Department of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago 60616, United States

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Journal article
Published: 13 July 2021 in Applied Energy
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This paper introduces a decentralized economic dispatch method and an architecture suitable for the virtual power plant (VPP) aggregating massive distributed energy resources (DERs). The convergence condition is given for quadratic cost functions, and is extended to the case of general increasing function of incremental cost (IC). Further analysis shows that the step of this method is adaptive, which is generated from the bottom up according to the responsiveness of each DER unit (DERU). Combined with the decentralized architecture based on message queue (MQ), the algorithm design considers the hosting mechanism of the coordinator failure, which not only improves the efficiency of calculation and communication without losing privacy-protection, but also makes it more fault-tolerant. The correctness and effectiveness of the method are verified in the case studies. The iterative process can respond and converge quickly when DER units reach capacity limits or devices fail/join. Due to the adaptability of the step, the method has strong robustness to the quantity and parameters randomness of underlying units. Therefore, it can be applied to the VPP with a massive number of DERs in order to get consensus solution by rapid economic dispatch.

ACS Style

Lianxin Dong; Shuai Fan; Zhihua Wang; Jucheng Xiao; Huan Zhou; Zuyi Li; Guangyu He. An adaptive decentralized economic dispatch method for virtual power plant. Applied Energy 2021, 300, 117347 .

AMA Style

Lianxin Dong, Shuai Fan, Zhihua Wang, Jucheng Xiao, Huan Zhou, Zuyi Li, Guangyu He. An adaptive decentralized economic dispatch method for virtual power plant. Applied Energy. 2021; 300 ():117347.

Chicago/Turabian Style

Lianxin Dong; Shuai Fan; Zhihua Wang; Jucheng Xiao; Huan Zhou; Zuyi Li; Guangyu He. 2021. "An adaptive decentralized economic dispatch method for virtual power plant." Applied Energy 300, no. : 117347.

Journal article
Published: 17 March 2021 in IEEE Transactions on Power Delivery
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Fragility modeling and real-time risk assessment can be widely applied to evaluate and enhances the resilience of the power system to High-Impact and Low Probability events. In previous studies, fragility modeling generally targets extreme weather conditions other than thunderstorm. This paper proposes a fragility model to describe the relationship between the duration of a thunderstorm and the probability of lightning related trip-out. The duration of thunderstorms, which can usually be forecasted from the meteorological department, together with the fragility function expression can help a power company to predict the possibility of lightning related trip-out. Furthermore, this paper proposes a real-time risk assessment model that can dynamically adjust the risk value based on the update of the location, peak current, and subsequent stroke of real-time thunderstorm. Validation by a case study in Southwest China, the average likelihood of transmission line trip-out in high risk group 10 times that in low risk group. It clearly demonstrates that real-time risk assessment can efficiently distinguish the trip-out risk of different real-time thunderstorms.

ACS Style

Jie Bao; Xin Wang; Yihui Zheng; Feng Zhang; Xuyong Huang; Peng Sun; Zuyi Li. Resilience-Oriented Transmission Line Fragility Modeling and Real-Time Risk Assessment of Thunderstorms. IEEE Transactions on Power Delivery 2021, 36, 2363 -2373.

AMA Style

Jie Bao, Xin Wang, Yihui Zheng, Feng Zhang, Xuyong Huang, Peng Sun, Zuyi Li. Resilience-Oriented Transmission Line Fragility Modeling and Real-Time Risk Assessment of Thunderstorms. IEEE Transactions on Power Delivery. 2021; 36 (4):2363-2373.

Chicago/Turabian Style

Jie Bao; Xin Wang; Yihui Zheng; Feng Zhang; Xuyong Huang; Peng Sun; Zuyi Li. 2021. "Resilience-Oriented Transmission Line Fragility Modeling and Real-Time Risk Assessment of Thunderstorms." IEEE Transactions on Power Delivery 36, no. 4: 2363-2373.

Journal article
Published: 21 January 2021 in IEEE Transactions on Smart Grid
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An incentive-compatible demand response (DR) strategy is proposed for engaging spatially-coupled Internet data center (IDC) and their spatial load regulation potentials in electricity markets. First, an optimal power flow (OPF) model which considers IDC (referred to as IOPF) is proposed to coordinate IDC DRs and power system operations, in which the formulated IDC load model is compatible with the conventional OPF model. Second, the IOPF-based locational marginal price (LMP) (referred to as ILMP) is derived, which is used to analyze the impact of spatially-coupled DR options on ILMPs and the IDC DR’s clearing price. Third, IDC DR activation strategy is proposed as an extension of Net Benefit Test (NBT), where the risk of negative benefit to IDCs is derived. An IDC DR’s activation strategy is proposed based on NBT to determine whether non-zero IDC DR dispatches in IOPF are cost-effective. Last, an extra benefit redistribution mechanism is proposed to achieve the incentive-compatibility between social welfare and IDC benefit. The proposed approach is based on the Vickrey-Clarke-Groves mechanism and the contribution factor theory, where the market’s revenue adequacy is maintained, and benefits to IDCs and other customers are guaranteed. Simulation results verify the efficiency of the proposed method, implying that the proposed spatiallycoupled DRs are compatible with and can enhance existing DR mechanisms.

ACS Style

Min Chen; Ciwei Gao; Mohammad Shahidehpour; Zuyi Li. Incentive-Compatible Demand Response for Spatially Coupled Internet Data Centers in Electricity Markets. IEEE Transactions on Smart Grid 2021, 12, 3056 -3069.

AMA Style

Min Chen, Ciwei Gao, Mohammad Shahidehpour, Zuyi Li. Incentive-Compatible Demand Response for Spatially Coupled Internet Data Centers in Electricity Markets. IEEE Transactions on Smart Grid. 2021; 12 (4):3056-3069.

Chicago/Turabian Style

Min Chen; Ciwei Gao; Mohammad Shahidehpour; Zuyi Li. 2021. "Incentive-Compatible Demand Response for Spatially Coupled Internet Data Centers in Electricity Markets." IEEE Transactions on Smart Grid 12, no. 4: 3056-3069.

Journal article
Published: 29 December 2020 in IEEE Transactions on Smart Grid
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The coordination of multiple coupled regulation methods in Internet data centers (IDCs) is proposed in this paper to make a full use of IDCs’ spatial and temporal load regulation potentials for demand response (DR). A concise and analytical IDC load model is proposed to facilitate the DR in IDCs. First, the unified IDC load considering multiple coupled regulation methods is modeled represented by workloads and servers. The extra power consumption in IT equipment due to redundancy requirements in computing resources is separated to obtain an explicit mathematical relationship among geo-distributed IDCs. Second, the compatible IDC load model is derived based on a bottom-up approach, where electrical decision variables representing the regulation are introduced to replace non-electrical variables and demonstrate the coupling among multiple regulation methods. Last, a hierarchical control design is deduced to reveal the potentials of the compatible IDC load model in power system applications. Simulations show that the joint implementation of coupled methods can enhance IDC DR capabilities. Simulation results also verify the efficiency of compatible IDC load model in DR and reveal its advantages in load characteristic analyses, computational efficiency, and sensitive information protection of IDCs.

ACS Style

Min Chen; Ciwei Gao; Mohammad Shahidehpour; Zuyi Li; Songsong Chen; Dezhi Li. Internet Data Center Load Modeling for Demand Response Considering the Coupling of Multiple Regulation Methods. IEEE Transactions on Smart Grid 2020, 12, 2060 -2076.

AMA Style

Min Chen, Ciwei Gao, Mohammad Shahidehpour, Zuyi Li, Songsong Chen, Dezhi Li. Internet Data Center Load Modeling for Demand Response Considering the Coupling of Multiple Regulation Methods. IEEE Transactions on Smart Grid. 2020; 12 (3):2060-2076.

Chicago/Turabian Style

Min Chen; Ciwei Gao; Mohammad Shahidehpour; Zuyi Li; Songsong Chen; Dezhi Li. 2020. "Internet Data Center Load Modeling for Demand Response Considering the Coupling of Multiple Regulation Methods." IEEE Transactions on Smart Grid 12, no. 3: 2060-2076.

Journal article
Published: 21 December 2020 in IEEE Transactions on Power Delivery
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Vegetation encroaching on overhead power lines can cause short circuit faults and pose a major threat to the security and stability of power grids. Therefore, establishing an effective visual detection algorithm to oversee potential circuit failures of the power lines is critical to the ongoing inspection of vegetation encroachment. This paper establishes a deep-learning-based detection framework that utilizes the images obtained from vision sensors mounted on power transmission towers. The proposed detection framework includes three cascaded modules: (1) detection of vegetation regions based on Faster Region Convolution Neural Network (Faster R-CNN), (2) detection of power lines based on Hough transform, and (3) detection of vegetation encroachment based on an advanced stereovision (SV) algorithm. In particular, the proposed SV algorithm converts the detected two-dimensional (2D) image data of vegetation and power lines to three-dimensional (3D) height and location results in order to obtain precise geographical location. Case studies using field captured images provided by a Transmission System Operator (TSO) demonstrate the effectiveness of the proposed framework in detecting vegetation failures, thus improving overall reliability and reducing economic loss.

ACS Style

Shuaiang Rong; Lina He; Liang Du; Zuyi Li; Shiwen Yu. Intelligent Detection of Vegetation Encroachment of Power Lines with Advanced Stereovision. IEEE Transactions on Power Delivery 2020, PP, 1 -1.

AMA Style

Shuaiang Rong, Lina He, Liang Du, Zuyi Li, Shiwen Yu. Intelligent Detection of Vegetation Encroachment of Power Lines with Advanced Stereovision. IEEE Transactions on Power Delivery. 2020; PP (99):1-1.

Chicago/Turabian Style

Shuaiang Rong; Lina He; Liang Du; Zuyi Li; Shiwen Yu. 2020. "Intelligent Detection of Vegetation Encroachment of Power Lines with Advanced Stereovision." IEEE Transactions on Power Delivery PP, no. 99: 1-1.

Journal article
Published: 11 December 2020 in The Electricity Journal
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This paper proposes the development and validation of an electro-thermal model of Lithium-Ion cell, which is used to recreate the cell’s temperature and voltage evolution given variable operating conditions. The obtained data is used to train and validate a Recurrent Neural Network (RNN) in predicting future cell combustion. Extensive case studies show that the proposed RNN adequately predicts possible cell combustion, so it can be applied to real life applications.

ACS Style

Fernando Almagro Yravedra; Zuyi Li. A complete machine learning approach for predicting lithium-ion cell combustion. The Electricity Journal 2020, 34, 106887 .

AMA Style

Fernando Almagro Yravedra, Zuyi Li. A complete machine learning approach for predicting lithium-ion cell combustion. The Electricity Journal. 2020; 34 (1):106887.

Chicago/Turabian Style

Fernando Almagro Yravedra; Zuyi Li. 2020. "A complete machine learning approach for predicting lithium-ion cell combustion." The Electricity Journal 34, no. 1: 106887.

Journal article
Published: 25 November 2020 in IEEE Transactions on Smart Grid
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This paper proposes a model-free lossless data compression method for time series in smart grids (SGs), namely, Lossless Coding considering Precision (LCP) method. The LCP method encodes the current datapoint only using the immediate previous datapoint by differential coding, XOR coding, and variable length coding and transmits the encoded data once generated. It does not use the dynamics (e.g., many previous datapoints) or prior knowledge (e.g., mathematical models) of the time series. It considers the patterns, potential applications, and associated precision to preprocess the time series and especially suits high-resolution time series with long steady periods. The LCP method features low-latency and generalizability which enables real-time data communication for different time-critical tasks. Sub-metered load profiles in REDD dataset, high-resolution LIFTED dataset, AMPds dataset and PMU dataset are used to evaluate the performance of the LCP method. The results show that the LCP method demonstrates high compression ratio, low latency, and low complexity compared to state-of-the-art Resumable Data Compression (RDC) method, DEFLATE based on LZ77 & Huffman coding, and Lempel-Ziv-Markov Chain Algorithm (LZMA).

ACS Style

Lei Yan; Jiayu Han; Runnan Xu; Zuyi Li. Model-Free Lossless Data Compression for Real-Time Low-Latency Transmission in Smart Grids. IEEE Transactions on Smart Grid 2020, 12, 2601 -2610.

AMA Style

Lei Yan, Jiayu Han, Runnan Xu, Zuyi Li. Model-Free Lossless Data Compression for Real-Time Low-Latency Transmission in Smart Grids. IEEE Transactions on Smart Grid. 2020; 12 (3):2601-2610.

Chicago/Turabian Style

Lei Yan; Jiayu Han; Runnan Xu; Zuyi Li. 2020. "Model-Free Lossless Data Compression for Real-Time Low-Latency Transmission in Smart Grids." IEEE Transactions on Smart Grid 12, no. 3: 2601-2610.

Journal article
Published: 18 November 2020 in IEEE Transactions on Smart Grid
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With an increasing amount of renewable energy resources (RESs) integrated into both distribution system (DS) and microgrids (MGs), a proper market clearing mechanism is required and has a critical impact on the operation reliability and economy of the DS. Combining distribution locational marginal price (DLMP) and uncertainty distribution locational marginal price (ULMP), this paper proposes a new electricity market clearing mechanism to charge both the power exchange and uncertain resources and coordinate DS and MGs. Based on the proposed market clearing mechanism, a bi-level coordinated robust economic dispatch model for DS and MGs is formulated. In the upper level, a two-stage robust economic dispatch model for DS is built, through which DLMP and ULMP are derived and then sent to MGs. In the lower level, each MG optimizes its dispatch based on the received DLMP and ULMP, which is modeled as a two-stage robust optimization model as well. The column and constraint generation algorithm is utilized to solve the robust economic dispatching model for both DS and MGs. Numerical results validate the effectiveness of the proposed bi-level robust economic dispatch model and solution method.

ACS Style

Lingling Wang; Zean Zhu; Chuanwen Jiang; Zuyi Li. Bi-Level Robust Optimization for Distribution System With Multiple Microgrids Considering Uncertainty Distribution Locational Marginal Price. IEEE Transactions on Smart Grid 2020, 12, 1104 -1117.

AMA Style

Lingling Wang, Zean Zhu, Chuanwen Jiang, Zuyi Li. Bi-Level Robust Optimization for Distribution System With Multiple Microgrids Considering Uncertainty Distribution Locational Marginal Price. IEEE Transactions on Smart Grid. 2020; 12 (2):1104-1117.

Chicago/Turabian Style

Lingling Wang; Zean Zhu; Chuanwen Jiang; Zuyi Li. 2020. "Bi-Level Robust Optimization for Distribution System With Multiple Microgrids Considering Uncertainty Distribution Locational Marginal Price." IEEE Transactions on Smart Grid 12, no. 2: 1104-1117.

Journal article
Published: 21 October 2020 in IEEE Transactions on Smart Grid
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With development of power electronic technology, the paralleled current-controlled voltage source converters (CCSs) and virtual synchronous generators (VSGs) system has advantages in providing power and voltage/frequency regulation at the same time in rural area or remote island. However, the paralleled system faces great challenges in safe and stable operation due to their limited thermal capacity and weak anti-disturbance ability, especially during fault periods. This paper focuses on transient stability and stability-oriented control design of the paralleled CCS-VSG system. First, mathematical model of the paralleled system is established and then the effect of two kinds of CCSs’ current injection angle (active current and reactive current) on VSG’s transient stability has been revealed through extended equal area criterion. Based on the theoretical analysis results, transient stability improvement control is put forward by controlling the CCS to track the VSG’s frame. Compared with the conditions that only active-or reactive current is provided by the CCS, the system can achieve the best transient performance when the proposed control is adopted. Moreover, the effect of CCS’s capacity on transient stability of the VSG has also been discussed. Finally, both Lyapunov’s method and simulation/experimental results are provided to validate the correctness of theoretical analysis.

ACS Style

Chao Shen; Zhikang Shuai; Yang Shen; Yelun Peng; Xuan Liu; Zuyi Li; Z. John Shen. Transient Stability and Current Injection Design of Paralleled Current-Controlled VSCs and Virtual Synchronous Generators. IEEE Transactions on Smart Grid 2020, 12, 1118 -1134.

AMA Style

Chao Shen, Zhikang Shuai, Yang Shen, Yelun Peng, Xuan Liu, Zuyi Li, Z. John Shen. Transient Stability and Current Injection Design of Paralleled Current-Controlled VSCs and Virtual Synchronous Generators. IEEE Transactions on Smart Grid. 2020; 12 (2):1118-1134.

Chicago/Turabian Style

Chao Shen; Zhikang Shuai; Yang Shen; Yelun Peng; Xuan Liu; Zuyi Li; Z. John Shen. 2020. "Transient Stability and Current Injection Design of Paralleled Current-Controlled VSCs and Virtual Synchronous Generators." IEEE Transactions on Smart Grid 12, no. 2: 1118-1134.

Research article
Published: 19 October 2020 in IET Generation, Transmission & Distribution
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Electric vehicles (EVs) as the frequency regulation (FR) resources with fast response speed provide a promising solution to improve FR performance. However, the exorbitant battery degradation cost (BDC) restricts EVs providing FR service. To achieve the FR performance with cost-efficiency, a hierarchical dispatching method based on the Hungarian algorithm is proposed for reducing the BDC of EVs in this study. To ensure system security, the required FR power is dispatched to FR units and EV aggregators according to the optimization coordinating strategy for reducing frequency fluctuation. Then, EV aggregators further dispatch the power to each EV for reducing the total BDC of EVs. In the dispatching process, various EVs provide FR service in the light of their actual condition such as BDC characteristics and state-of-charges (SOCs). To calculate the BDC of EVs accurately, the corresponding cost formulas that consider various EVs are fitting for guiding power dispatching. According to the sensitivity analysis, the FR regularity of EVs about FR performance is drawn for promoting the quantity of EVs participating in FR and further improving FR performance. Extensive case studies are presented to validate the effectiveness of the proposed method, where a large number of EVs participate in FR with cost-efficiency.

ACS Style

Long Zeng; Canbing Li; Zuyi Li; Bin Zhou; Hui Liu; Hanyu Yang. Hierarchical dispatching method based on Hungarian algorithm for reducing the battery degradation cost of EVs participating in frequency regulation. IET Generation, Transmission & Distribution 2020, 14, 5617 -5625.

AMA Style

Long Zeng, Canbing Li, Zuyi Li, Bin Zhou, Hui Liu, Hanyu Yang. Hierarchical dispatching method based on Hungarian algorithm for reducing the battery degradation cost of EVs participating in frequency regulation. IET Generation, Transmission & Distribution. 2020; 14 (23):5617-5625.

Chicago/Turabian Style

Long Zeng; Canbing Li; Zuyi Li; Bin Zhou; Hui Liu; Hanyu Yang. 2020. "Hierarchical dispatching method based on Hungarian algorithm for reducing the battery degradation cost of EVs participating in frequency regulation." IET Generation, Transmission & Distribution 14, no. 23: 5617-5625.

Journal article
Published: 22 September 2020 in IEEE Transactions on Smart Grid
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Load data is an essential input for power system analysis and management. However, traditional load analysis methods do not fit well with emerging deep learning models that may require image matrix as input, such as Convolutional Neural Network (CNN) and Generative Adversarial Nets (GAN). This paper proposes a novel analysis method “Load Photo” to create the required image matrix for various loads in power systems by using the HSV color space. A load photo is a 2-D pixel graphical representation of load, in which the x-axis represents sampling time points (e.g., hours) for every day from Sunday to Saturday, the y-axis represents weeks from the first week till the last week, and the pixel color demonstrates the normalized load. A load photo stores all essential load-related parameters such as start time, end time, and sampling period. A load photo can be used to characterize the energy consumption pattern of any load type, just like taking a photo for the load that clearly demonstrates the load’s behavior. Furthermore, a load photo could work before feature selection as an input to deep learning models. Accordingly, the latest advancement in deep learning models related to image processing can be easily applied to the analysis and data mining of load data.

ACS Style

Hong Wang; Linhai Qi; Lei Yan; Zuyi Li. Load Photo: A Novel Analysis Method for Load Data. IEEE Transactions on Smart Grid 2020, 12, 1394 -1404.

AMA Style

Hong Wang, Linhai Qi, Lei Yan, Zuyi Li. Load Photo: A Novel Analysis Method for Load Data. IEEE Transactions on Smart Grid. 2020; 12 (2):1394-1404.

Chicago/Turabian Style

Hong Wang; Linhai Qi; Lei Yan; Zuyi Li. 2020. "Load Photo: A Novel Analysis Method for Load Data." IEEE Transactions on Smart Grid 12, no. 2: 1394-1404.

Journal article
Published: 13 August 2020 in IEEE Transactions on Smart Grid
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In this paper, a hierarchical bipartite graph (HBG) matching method is proposed to promote transactive vehicle-tovehicle (V2V) power exchanges in a distribution power system. A distribution system which includes EVs is divided into a series of subsystems according to EV locations, where V2V power exchanges are optimized for scheduling charging/discharging periods among transacting EVs in each subsystem. Each subsystem’s power surplus or deficit will then be regulated by power exchanges among neighboring subsystems and the utility grid. The one-to-multiple and multiple-to-one modes are adopted in the proposed HBG algorithm for the promotion of transactive V2V power exchanges. Also, individual EV’s electricity trading price can track that of the subsystem by adjusting respective power exchange objectives adaptively. Several case studies are presented to validate the effectiveness of the proposed method, where transactive V2V power exchanges are improved and the energy efficiency in a distribution power system is enhanced.

ACS Style

Long Zeng; Canbing Li; Zuyi Li; Mohammad Shahidehpour; Bin Zhou; Quan Zhou. Hierarchical Bipartite Graph Matching Method for Transactive V2V Power Exchange in Distribution Power System. IEEE Transactions on Smart Grid 2020, 12, 301 -311.

AMA Style

Long Zeng, Canbing Li, Zuyi Li, Mohammad Shahidehpour, Bin Zhou, Quan Zhou. Hierarchical Bipartite Graph Matching Method for Transactive V2V Power Exchange in Distribution Power System. IEEE Transactions on Smart Grid. 2020; 12 (1):301-311.

Chicago/Turabian Style

Long Zeng; Canbing Li; Zuyi Li; Mohammad Shahidehpour; Bin Zhou; Quan Zhou. 2020. "Hierarchical Bipartite Graph Matching Method for Transactive V2V Power Exchange in Distribution Power System." IEEE Transactions on Smart Grid 12, no. 1: 301-311.

Journal article
Published: 10 August 2020 in IEEE Transactions on Smart Grid
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A two-stage Internet data center (IDC)-considered framework in generation and transmission expansion planning (GTEP) (referred to as IGTEP) is proposed to make full use of IDCs’ spatial and chronological load regulation potentials for demand response. Stage one aggregates the data network (DN) to match a transmission network structure. First, IDC load is modeled based on the DN configuration. Second, the aggregated DN (ADN) is proposed to model DN with aggregated front-end servers (FSs) and data flows, where an intuitively accurate mathematical relationship among IDCs is developed. Third, the virtual power network (VPN) is proposed to provide a model for ADN with electrical variables, where the coupling of DN and power network (PN) is proposed to develop a linear aggregated IDC load model. Stage two coordinates IDC DR and GTEP, in which the load coupling among multiple IDCs is managed by VPN and the corresponding IDC load model is compatible with the conventional GTEP load. Simulation results verify the efficiency of the proposed VPN and IDC load model. Simulation results also show that IDC DR may reduce the total IGTEP cost significantly, which implies that DN can play a role equivalent to power lines and generators in power system planning and operations.

ACS Style

Min Chen; Ciwei Gao; Zuyi Li; Mohammad Shahidehpour; Quan Zhou; Songsong Chen; Jianlin Yang. Aggregated Model of Data Network for the Provision of Demand Response in Generation and Transmission Expansion Planning. IEEE Transactions on Smart Grid 2020, 12, 512 -523.

AMA Style

Min Chen, Ciwei Gao, Zuyi Li, Mohammad Shahidehpour, Quan Zhou, Songsong Chen, Jianlin Yang. Aggregated Model of Data Network for the Provision of Demand Response in Generation and Transmission Expansion Planning. IEEE Transactions on Smart Grid. 2020; 12 (1):512-523.

Chicago/Turabian Style

Min Chen; Ciwei Gao; Zuyi Li; Mohammad Shahidehpour; Quan Zhou; Songsong Chen; Jianlin Yang. 2020. "Aggregated Model of Data Network for the Provision of Demand Response in Generation and Transmission Expansion Planning." IEEE Transactions on Smart Grid 12, no. 1: 512-523.

Journal article
Published: 07 May 2020 in IEEE Access
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Gas generation and heat storage are playing a prominent role to multi-energy systems (MES), and coordinated planning of integrated electricity, heat and gas infrastructures can highly benefit MES. In this context, a coordinated planning model of MES is proposed to determine the optimal expansion of conventional generators, transmission lines, gas boilers, combined heat and power units, and gas pipelines. In the model, the one-off investment cost of MES devices in the planning phase plus the operation cost and energy not served cost in the operation phase are considered in the objective, while the energy supply reliability, coupled operational security of multiple energy carriers, as well as the electricity, gas, and heat demand balance are comprehensively taken into account as the constraints. Afterwards, the Benders Decomposition method is adopted to solve the proposed expansion planning model in a divide and conquer manner. Finally three case studies on a 14-bus MES are conducted to demonstrate the effectiveness of the proposed expansion planning model. Simulation results indicate that the total cost of the proposed model in case 3 is saved by 9% and 2.8% compared with the separately planning scheme in case 1 and the coordinated planning scheme without candidate gas pipelines in case 2. Therefore, the proposed coordinated expansion model is very effective for MES Infrastructure planning.

ACS Style

Hong Fan; Qianqian Yuan; Shiwei Xia; Jiayang Lu; Zuyi Li. Optimally Coordinated Expansion Planning of Coupled Electricity, Heat and Natural Gas Infrastructure for Multi-Energy System. IEEE Access 2020, 8, 91139 -91149.

AMA Style

Hong Fan, Qianqian Yuan, Shiwei Xia, Jiayang Lu, Zuyi Li. Optimally Coordinated Expansion Planning of Coupled Electricity, Heat and Natural Gas Infrastructure for Multi-Energy System. IEEE Access. 2020; 8 (99):91139-91149.

Chicago/Turabian Style

Hong Fan; Qianqian Yuan; Shiwei Xia; Jiayang Lu; Zuyi Li. 2020. "Optimally Coordinated Expansion Planning of Coupled Electricity, Heat and Natural Gas Infrastructure for Multi-Energy System." IEEE Access 8, no. 99: 91139-91149.

Journal article
Published: 13 February 2020 in IEEE Access
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Uncertainty in renewable energy and load is a great challenge for microgrid operation, especially in islanded mode as the microgrid may be small in size and has limited flexible resources. In this paper, a multi-timescale, two-stage robust dispatch model is proposed to optimize the microgrid operation. Different from other multi time-scale generation scheduling models, the proposed one uses only one model to combine the hourly and sub-hourly dispatch together, which means the day-ahead hourly dispatch results must also satisfy the sub-hourly conditions. At the same time, the feasibility of the day-ahead dispatch result is verified in the worst-case condition considering the high-level uncertainty in renewable energy output and load consumptions. In addition, battery energy storage system (BESS) and solar PV units are integrated as a combined solar-storage system in the proposed model and the output power of the combined solar-storage system keeps unchanged on an hourly basis. In this way, it largely neutralizes the impact of solar uncertainty and makes the microgrid operation grid friendly. Furthermore, in order to enhance the flexibility and resilience of the microgrid, both BESS and thermal units provide regulating reserve to manage solar and load uncertainty. The model has been tested in a controlled hardware in loop (CHIL) environment for the Bronzeville Community Microgrid system in Chicago. The simulation results show that the proposed model works effectively in managing the uncertainty in solar PV and load and can provide a flexible dispatch in both grid-connected and islanded modes.

ACS Style

Jiayu Han; Lei Yan; Zuyi Li; Liuxi Zhang; Aleksi Paaso; Shay Bahramirad. A Multi-Timescale Two-Stage Robust Grid-Friendly Dispatch Model for Microgrid Operation. IEEE Access 2020, 8, 74267 -74279.

AMA Style

Jiayu Han, Lei Yan, Zuyi Li, Liuxi Zhang, Aleksi Paaso, Shay Bahramirad. A Multi-Timescale Two-Stage Robust Grid-Friendly Dispatch Model for Microgrid Operation. IEEE Access. 2020; 8 (99):74267-74279.

Chicago/Turabian Style

Jiayu Han; Lei Yan; Zuyi Li; Liuxi Zhang; Aleksi Paaso; Shay Bahramirad. 2020. "A Multi-Timescale Two-Stage Robust Grid-Friendly Dispatch Model for Microgrid Operation." IEEE Access 8, no. 99: 74267-74279.

Journal article
Published: 09 January 2020 in IEEE Transactions on Power Electronics
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With the development of virtual synchronous generator (VSG) techniques, parallel operations of synchronous generators (SGs) and VSGs become increasingly common in a microgrid. The differences between paralleled systems will affect transient stability of the system, which probably threatens stable operation of the system, especially under fault conditions. In this paper, transient angle stability of a paralleled synchronous and virtual synchronous generators (SG-VSG) system is investigated by compared with that of paralleled VSGs system. It is observed that the paralleled SG-VSG system is more prone to transient instability due to the differences between their speed governors. Then, a control method is proposed to improve the transient stability of paralleled SG-VSG system. Furthermore, a Lyapunov method is employed to establish the nonlinear model of islanded microgrid, by which the attraction domain of paralleled system is quantified. The hardware-in-loop experiment is performed to validate the theoretical analysis.

ACS Style

Huijie Cheng; Zhikang Shuai; Chao Shen; Xuan Liu; Zuyi Li; Z. John Shen. Transient Angle Stability of Paralleled Synchronous and Virtual Synchronous Generators in Islanded Microgrids. IEEE Transactions on Power Electronics 2020, 35, 8751 -8765.

AMA Style

Huijie Cheng, Zhikang Shuai, Chao Shen, Xuan Liu, Zuyi Li, Z. John Shen. Transient Angle Stability of Paralleled Synchronous and Virtual Synchronous Generators in Islanded Microgrids. IEEE Transactions on Power Electronics. 2020; 35 (8):8751-8765.

Chicago/Turabian Style

Huijie Cheng; Zhikang Shuai; Chao Shen; Xuan Liu; Zuyi Li; Z. John Shen. 2020. "Transient Angle Stability of Paralleled Synchronous and Virtual Synchronous Generators in Islanded Microgrids." IEEE Transactions on Power Electronics 35, no. 8: 8751-8765.

Journal article
Published: 27 December 2019 in Electric Power Systems Research
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Large-scale demand response (DR) is a critical enabler to integrate significant renewable energy sources (RES) into power systems. Current customer baseline load (CBL)-based DR schemes face obstacles in large-scale deployments due to their centralized form, unfair DR performance measurement, and poor effect on decision making approach of customers. To bridge the gaps, this paper proposes the concept of customer directrix load (CDL), which is the desired load profile for customers from the view of the entire DR program, and a novel CDL-based DR scheme. Additionally, an optimization problem considering time-coupling constraints is formulated to help customers respond to the CDL. The computationally intensive problem is then translated into a quadratic programming problem in each time slot using Lyapunov optimization approach. A closed-form solution exists and ensures that the optimal decision is reached in real-time efficiently. Test systems are generated using data from PJM and Open Energy Information. The online algorithm and fairness performance of the proposed scheme are validated in a small system through benchmark comparisons. Further tests on a large-scale system show that the CDL-based DR scheme can help the power system integrate considerably more RES.

ACS Style

Shuai Fan; Zuyi Li; Lin Yang; Guangyu He. Customer directrix load-based large-scale demand response for integrating renewable energy sources. Electric Power Systems Research 2019, 181, 106175 .

AMA Style

Shuai Fan, Zuyi Li, Lin Yang, Guangyu He. Customer directrix load-based large-scale demand response for integrating renewable energy sources. Electric Power Systems Research. 2019; 181 ():106175.

Chicago/Turabian Style

Shuai Fan; Zuyi Li; Lin Yang; Guangyu He. 2019. "Customer directrix load-based large-scale demand response for integrating renewable energy sources." Electric Power Systems Research 181, no. : 106175.

Journal article
Published: 27 December 2019 in IEEE Transactions on Smart Grid
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Optimal operation strategies are essential for maintaining a secure, economic, and resilient operation of power systems in dealing with geomagnetic storms. However, practical efforts for attaining such optimal operations are facing significant modeling and solution challenges that stem from the computational complexity of the geomagnetic disturbance (GMD) mitigation problem. To overcome these challenges, this paper proposes a parallel solution approach to improve the computational efficiency. In this approach, the mixed-integer nonlinear programming (MINLP) problem of mitigating geomagnetic disturbance is split into a nonlinear AC optimal power flow subproblem (ACOPF) and a mixed-integer linear DC geomagnetically-induced current (GIC-DC) mitigation subproblem. The solution mitigates the negative effects of geomagnetic storms by introducing transformer neutral and transmission line series GIC blocking devices, transmission switching, and a host of other operation planning schemes which can enhance the power system resilience. Multiple cases on the 6-bus, 18-bus and 150-bus power systems are studied to show the effectiveness and efficiency of the proposed parallel modeling and solution approach. The studied cases also show that the proposed parallel solution approach offers a promising performance which is based on the applications of augmented Lagrangian relaxation and auxiliary problem principle methods.

ACS Style

Lin Gong; Yong Fu; Mohammad Shahidehpour; Zuyi Li. A Parallel Solution for the Resilient Operation of Power Systems in Geomagnetic Storms. IEEE Transactions on Smart Grid 2019, 11, 3483 -3495.

AMA Style

Lin Gong, Yong Fu, Mohammad Shahidehpour, Zuyi Li. A Parallel Solution for the Resilient Operation of Power Systems in Geomagnetic Storms. IEEE Transactions on Smart Grid. 2019; 11 (4):3483-3495.

Chicago/Turabian Style

Lin Gong; Yong Fu; Mohammad Shahidehpour; Zuyi Li. 2019. "A Parallel Solution for the Resilient Operation of Power Systems in Geomagnetic Storms." IEEE Transactions on Smart Grid 11, no. 4: 3483-3495.

Journal article
Published: 22 November 2019 in IEEE Transactions on Industrial Informatics
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In a cyber-attack, the attacker can impose security impacts by injecting false data into measurements to affect the power system scheduling and dispatch. In real-time, the system is dispatched in successive dispatch intervals. The existing methods analyze the attacks based on a snapshot of the system condition at the end of a dispatch interval, at which the dispatch is achieved. Such analysis falls into a static analysis framework (SAF). However, with the increasing share of intermittent resources, the system is suffering short-term fluctuations which will increase the system vulnerability and render weak points during a dispatch interval. These weak points can be exploited by smart attackers to impose large impacts on the intra-interval operational security. Such cyber risk may be ignored or underestimated by the existing methods under the SAF. To address this risk, this paper analyzes the intra-interval operational security under a dynamic analysis framework (DAF) and quantifies the impacts of potential data attacks on the intra-interval security. Simulations are performed based on the historical wind data on the IEEE 118-bus system, which verify the proposed approach and highlight the risk of such issues in power systems with significant wind penetration.

ACS Style

Xuan Liu; Liang Che; Kunlun Gao; Zuyi Li. Power System Intra-Interval Operational Security Under False Data Injection Attacks. IEEE Transactions on Industrial Informatics 2019, 16, 4997 -5008.

AMA Style

Xuan Liu, Liang Che, Kunlun Gao, Zuyi Li. Power System Intra-Interval Operational Security Under False Data Injection Attacks. IEEE Transactions on Industrial Informatics. 2019; 16 (8):4997-5008.

Chicago/Turabian Style

Xuan Liu; Liang Che; Kunlun Gao; Zuyi Li. 2019. "Power System Intra-Interval Operational Security Under False Data Injection Attacks." IEEE Transactions on Industrial Informatics 16, no. 8: 4997-5008.

Journal article
Published: 20 November 2019 in IEEE Journal of Emerging and Selected Topics in Power Electronics
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This paper presents an impedance-based method for stability analysis of multi-converter power systems based on the Generalized Nyquist Stability Criterion. The return-ratio matrix of the system is formulated on the basis of the nodal admittance matrix as well as output admittance of the converters, which can be applicable for the large-scale systems with complicated structure. A modified IEEE 13-bus system is used as the testing system, which shows that the proposed method can be easily implemented for location optimization of the converters. And the participation factors of return-ratio matrix’s critical eigenvalues (which encircle the critical point (-1, 0j)) at the instability frequencies are used to identify which converters have significant contributions to the instability, and then guidance for the design of system parameters can be provided. Simulations in PSCAD/EMTDC validate the effectiveness of the proposed stability analysis method.

ACS Style

Yang Li; Zhikang Shuai; Xuan Liu; Yandong Chen; Zuyi Li; Yi Hong; Z. John Shen. Stability Analysis and Location Optimization Method for Multiconverter Power Systems Based on Nodal Admittance Matrix. IEEE Journal of Emerging and Selected Topics in Power Electronics 2019, 9, 529 -538.

AMA Style

Yang Li, Zhikang Shuai, Xuan Liu, Yandong Chen, Zuyi Li, Yi Hong, Z. John Shen. Stability Analysis and Location Optimization Method for Multiconverter Power Systems Based on Nodal Admittance Matrix. IEEE Journal of Emerging and Selected Topics in Power Electronics. 2019; 9 (1):529-538.

Chicago/Turabian Style

Yang Li; Zhikang Shuai; Xuan Liu; Yandong Chen; Zuyi Li; Yi Hong; Z. John Shen. 2019. "Stability Analysis and Location Optimization Method for Multiconverter Power Systems Based on Nodal Admittance Matrix." IEEE Journal of Emerging and Selected Topics in Power Electronics 9, no. 1: 529-538.