Pub Date : 2023-09-08DOI: 10.17775/CSEEJPES.2022.00580
Bin Luo;Guangzhao Luo;Sihai Li
With high-frequency, low power dissipation and high-efficiency characteristics, Gallium nitride (GaN) power devices are of significant benefit in designing high-speed motor drives, as they improve performance and reduce weight. However, due to the cascode structure, coupling with the parasitics in gate driver and power circuits, power converters based on cascode GaN are prone to overshoot and oscillate on switching waveforms, which may lead to serious EMC problems, or even device breakdown. The complicated structure of cascode GaN device makes the gate driver design comparatively complex. An analytical model of the switching process considering gate driver parameters is proposed in this article. The influence of gate driver parameters on switching behavior is investigated from the perspective of switching speed, waveform overshoot, and power loss. Trade-offs among overshoot, switching speed, and power loss are discussed; guidelines to design gate driver parameters are given.
{"title":"Switching Behavior of Cascode GaN Under Influence of Gate Driver","authors":"Bin Luo;Guangzhao Luo;Sihai Li","doi":"10.17775/CSEEJPES.2022.00580","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2022.00580","url":null,"abstract":"With high-frequency, low power dissipation and high-efficiency characteristics, Gallium nitride (GaN) power devices are of significant benefit in designing high-speed motor drives, as they improve performance and reduce weight. However, due to the cascode structure, coupling with the parasitics in gate driver and power circuits, power converters based on cascode GaN are prone to overshoot and oscillate on switching waveforms, which may lead to serious EMC problems, or even device breakdown. The complicated structure of cascode GaN device makes the gate driver design comparatively complex. An analytical model of the switching process considering gate driver parameters is proposed in this article. The influence of gate driver parameters on switching behavior is investigated from the perspective of switching speed, waveform overshoot, and power loss. Trade-offs among overshoot, switching speed, and power loss are discussed; guidelines to design gate driver parameters are given.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"10 4","pages":"1816-1833"},"PeriodicalIF":6.9,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10246140","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141966284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-08DOI: 10.17775/CSEEJPES.2022.08580
Hao Xiao;Xianzhong Duan;Yi Zhang
Distinction of weak and strong AC grids for emerging hierarchical-infeed LCC-UHVDC systems is important for planning and operation departments. However, accuracy of earlier distinction methods is limited as they were developed by empirical reasoning without rigorous theoretical analysis. Hence in this letter, hierarchical-infeed interactive effective short-circuit ratio (HIESCR) index is first used for strength evaluation of HIDC systems with complex inter-inverter interactions considered. Boundary HIESCR (BHIESCR) is also introduced in the proposed distinction method of weak and strong AC grids. That is, weak (or strong) AC grids are, respectively, identified when HIESCR is less (or greater) than BHIESCR. Second, it is shown BHIESCR remains almost unchanged as 3.0 versus various system parameters and rated operation variables based on rigorous theoretical analysis. This salient feature makes the proposed method more accurate than earlier methods. Finally, the proposed method is validated by simulations based on the PSCAD/EMTDC program.
{"title":"Accurate Distinction of Weak and Strong AC Grids for Emerging Hierarchical-Infeed LCC-UHVDC Systems","authors":"Hao Xiao;Xianzhong Duan;Yi Zhang","doi":"10.17775/CSEEJPES.2022.08580","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2022.08580","url":null,"abstract":"Distinction of weak and strong AC grids for emerging hierarchical-infeed LCC-UHVDC systems is important for planning and operation departments. However, accuracy of earlier distinction methods is limited as they were developed by empirical reasoning without rigorous theoretical analysis. Hence in this letter, hierarchical-infeed interactive effective short-circuit ratio (HIESCR) index is first used for strength evaluation of HIDC systems with complex inter-inverter interactions considered. Boundary HIESCR (BHIESCR) is also introduced in the proposed distinction method of weak and strong AC grids. That is, weak (or strong) AC grids are, respectively, identified when HIESCR is less (or greater) than BHIESCR. Second, it is shown BHIESCR remains almost unchanged as 3.0 versus various system parameters and rated operation variables based on rigorous theoretical analysis. This salient feature makes the proposed method more accurate than earlier methods. Finally, the proposed method is validated by simulations based on the PSCAD/EMTDC program.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"10 2","pages":"772-777"},"PeriodicalIF":7.1,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10246179","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140351559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Increasing penetration of distributed energy resources in the distribution network (DN) is threatening safe operation of the DN, which necessitates setup of the ancillary service market in the DN. In the ancillary service market, distribution system operator (DSO) is responsible for safety of the DN by procuring available capacities of aggregators. Unlike existing studies, this paper proposes a novel market mechanism composed of two parts: choice rule and payment rule. The proposed choice rule simultaneously considers social welfare and fairness, encouraging risk-averse aggregators to participate in the ancillary service market. It is then formulated as a linear programming problem, and a distributed solution using the multi-cut Benders decomposition is presented. Moreover, successful implementation of the choice rule depends on each aggregator's truthful adoption of private parameters. Therefore, a payment rule is also designed, which is proved to possess two properties: incentive compatibility and individual rationality. Simulation results demonstrate effectiveness of the proposed choice rule on improving fairness and verify properties of the payment rule.
{"title":"Mechanism Design for Ancillary Service Market Considering Social Welfare and Fairness","authors":"Zhi Wu;Yuanxi Wu;Wei Gu;Zheng Xu;Shu Zheng;Jingtao Zhao","doi":"10.17775/CSEEJPES.2022.01510","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2022.01510","url":null,"abstract":"Increasing penetration of distributed energy resources in the distribution network (DN) is threatening safe operation of the DN, which necessitates setup of the ancillary service market in the DN. In the ancillary service market, distribution system operator (DSO) is responsible for safety of the DN by procuring available capacities of aggregators. Unlike existing studies, this paper proposes a novel market mechanism composed of two parts: choice rule and payment rule. The proposed choice rule simultaneously considers social welfare and fairness, encouraging risk-averse aggregators to participate in the ancillary service market. It is then formulated as a linear programming problem, and a distributed solution using the multi-cut Benders decomposition is presented. Moreover, successful implementation of the choice rule depends on each aggregator's truthful adoption of private parameters. Therefore, a payment rule is also designed, which is proved to possess two properties: incentive compatibility and individual rationality. Simulation results demonstrate effectiveness of the proposed choice rule on improving fairness and verify properties of the payment rule.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"10 3","pages":"1000-1010"},"PeriodicalIF":7.1,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10246136","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141304063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-27DOI: 10.17775/CSEEJPES.2022.07130
Tong Cheng;Haiwang Zhong;Qing Xia
Market participants can only bid with lagged information disclosure under the existing market mechanism, which can lead to information asymmetry and irrational market behavior, thus influencing market efficiency. To promote rational bidding behavior of market participants and improve market efficiency, a novel electricity market mechanism based on cloudedge collaboration is proposed in this paper. Critical market information, called residual demand curve, is published to market participants in real-time on the cloud side, while participants on the edge side are allowed to adjust their bids according to the information disclosure prior to closure gate. The proposed mechanism can encourage rational bids in an incentive-compatible way through the process of dynamic equilibrium while protecting participants' privacy. This paper further formulates the mathematical model of market equilibrium to simulate the process of each market participant's strategic bidding behavior towards equilibrium. A case study based on the IEEE 30-bus system shows the proposed market mechanism can effectively guide bidding behavior of market participants, while condensing exchanged information and protecting privacy of participants.
{"title":"Market Equilibrium Based on Cloud-edge Collaboration","authors":"Tong Cheng;Haiwang Zhong;Qing Xia","doi":"10.17775/CSEEJPES.2022.07130","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2022.07130","url":null,"abstract":"Market participants can only bid with lagged information disclosure under the existing market mechanism, which can lead to information asymmetry and irrational market behavior, thus influencing market efficiency. To promote rational bidding behavior of market participants and improve market efficiency, a novel electricity market mechanism based on cloudedge collaboration is proposed in this paper. Critical market information, called residual demand curve, is published to market participants in real-time on the cloud side, while participants on the edge side are allowed to adjust their bids according to the information disclosure prior to closure gate. The proposed mechanism can encourage rational bids in an incentive-compatible way through the process of dynamic equilibrium while protecting participants' privacy. This paper further formulates the mathematical model of market equilibrium to simulate the process of each market participant's strategic bidding behavior towards equilibrium. A case study based on the IEEE 30-bus system shows the proposed market mechanism can effectively guide bidding behavior of market participants, while condensing exchanged information and protecting privacy of participants.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"10 1","pages":"96-104"},"PeriodicalIF":7.1,"publicationDate":"2023-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10165681","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139695103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-27DOI: 10.17775/CSEEJPES.2022.02880
Yanda Huo;Peng Li;Haoran Ji;Hao Yu;Jinli Zhao;Wei Xi;Jianzhong Wu;Chengshan Wang
Integration of distributed energy storage (DES) is beneficial for mitigating voltage fluctuations in highly distributed generator (DG)-penetrated active distribution networks (ADNs). Based on an accurate physical model of ADN, conventional model-based methods can realize optimal control of DES. However, absence of network parameters and complex operational states of ADN poses challenges to model-based methods. This paper proposes a data-driven predictive voltage control method for DES. First, considering time-series constraints, a data-driven predictive control model is formulated for DES by using measurement data. Then, a data-driven coordination method is proposed for DES and DGs in each area. Through boundary information interaction, voltage mitigation effects can be improved by inter-area coordination control. Finally, control performance is tested on a modified IEEE 33-node test case. Case studies demonstrate that by fully utilizing multi-source data, the proposed predictive control method can effectively regulate DES and DGs to mitigate voltage violations.
在高度分布式发电机（DG）渗透的有源配电网（ADN）中，集成分布式储能（DES）有利于缓解电压波动。基于精确的 ADN 物理模型，传统的基于模型的方法可以实现 DES 的优化控制。然而，网络参数的缺失和 ADN 复杂的运行状态给基于模型的方法带来了挑战。本文提出了一种数据驱动的 DES 预测电压控制方法。首先，考虑时间序列约束，利用测量数据为 DES 建立数据驱动预测控制模型。然后，针对每个区域的 DES 和 DG，提出了一种数据驱动协调方法。通过边界信息交互，区域间协调控制可改善电压缓解效果。最后，在修改后的 IEEE 33 节点测试案例中测试了控制性能。案例研究表明，通过充分利用多源数据，所提出的预测控制方法可以有效调节 DES 和 DG，从而缓解电压违规问题。
{"title":"Data-Driven Predictive Voltage Control for Distributed Energy Storage in Active Distribution Networks","authors":"Yanda Huo;Peng Li;Haoran Ji;Hao Yu;Jinli Zhao;Wei Xi;Jianzhong Wu;Chengshan Wang","doi":"10.17775/CSEEJPES.2022.02880","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2022.02880","url":null,"abstract":"Integration of distributed energy storage (DES) is beneficial for mitigating voltage fluctuations in highly distributed generator (DG)-penetrated active distribution networks (ADNs). Based on an accurate physical model of ADN, conventional model-based methods can realize optimal control of DES. However, absence of network parameters and complex operational states of ADN poses challenges to model-based methods. This paper proposes a data-driven predictive voltage control method for DES. First, considering time-series constraints, a data-driven predictive control model is formulated for DES by using measurement data. Then, a data-driven coordination method is proposed for DES and DGs in each area. Through boundary information interaction, voltage mitigation effects can be improved by inter-area coordination control. Finally, control performance is tested on a modified IEEE 33-node test case. Case studies demonstrate that by fully utilizing multi-source data, the proposed predictive control method can effectively regulate DES and DGs to mitigate voltage violations.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"10 5","pages":"1876-1886"},"PeriodicalIF":6.9,"publicationDate":"2023-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10165656","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142397508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-27DOI: 10.17775/CSEEJPES.2022.07290
Yuwei Xiang;Tong Wang;Zengping Wang
Enhancing power system resilience against extreme events is becoming increasingly critical. This paper discusses a unified framework for preventive control of power systems to enhance system resilience, which includes three parts: resilience assessment, resilience grading, and resilience enhancement. First, the resilience assessment contains facility-level and system-level resilience assessment. The concept of fragility curve is used in the facility-level resilience assessment. Various resilience indices are developed in system-level resilience assessment to roundly depict the impacts of extreme events on power systems and determine the system resilience. On this basis, the resilience is divided into different levels by resilience grading strategy, which can efficiently quantify the severity of the impact of extreme events and provide decision-making for the resilience enhancement strategies. Then, control strategies for enhancing power system resilience are also divided according to different resilience levels. A controlled islanding based preventive control is proposed to enhance system resilience, which aims to strengthen the first defensive line of power systems to deal with extreme events. Finally, taking the typhoon disaster in extreme events as an example, two tests carried out with two typhoons demonstrate the efficiency of the proposed method.
{"title":"Framework for Preventive Control of Power Systems to Defend Against Extreme Events","authors":"Yuwei Xiang;Tong Wang;Zengping Wang","doi":"10.17775/CSEEJPES.2022.07290","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2022.07290","url":null,"abstract":"Enhancing power system resilience against extreme events is becoming increasingly critical. This paper discusses a unified framework for preventive control of power systems to enhance system resilience, which includes three parts: resilience assessment, resilience grading, and resilience enhancement. First, the resilience assessment contains facility-level and system-level resilience assessment. The concept of fragility curve is used in the facility-level resilience assessment. Various resilience indices are developed in system-level resilience assessment to roundly depict the impacts of extreme events on power systems and determine the system resilience. On this basis, the resilience is divided into different levels by resilience grading strategy, which can efficiently quantify the severity of the impact of extreme events and provide decision-making for the resilience enhancement strategies. Then, control strategies for enhancing power system resilience are also divided according to different resilience levels. A controlled islanding based preventive control is proposed to enhance system resilience, which aims to strengthen the first defensive line of power systems to deal with extreme events. Finally, taking the typhoon disaster in extreme events as an example, two tests carried out with two typhoons demonstrate the efficiency of the proposed method.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"10 2","pages":"856-870"},"PeriodicalIF":7.1,"publicationDate":"2023-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10165677","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140351440","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper addresses the planning problem of parallel DC electric springs (DCESs). DCES, a demand-side management method, realizes automatic matching of power consumption and power generation by adjusting non-critical load (NCL) and internal storage. It can offer higher power quality to critical load (CL), reduce power imbalance and relieve pressure on energy storage systems (RESs). In this paper, a planning method for parallel DCESs is proposed to maximize stability gain, economic benefits, and penetration of RESs. The planning model is a master optimization with sub-optimization to highlight the priority of objectives. Master optimization is used to improve stability of the network, and sub-optimization aims to improve economic benefit and allowable penetration of RESs. This issue is a multivariable nonlinear mixed integer problem, requiring huge calculations by using common solvers. Therefore, particle Swarm optimization (PSO) and Elitist non-dominated sorting genetic algorithm (NSGA-II) were used to solve this model. Considering uncertainty of RESs, this paper verifies effectiveness of the proposed planning method on IEEE 33-bus system based on deterministic scenarios obtained by scenario analysis.
{"title":"Planning of DC Electric Spring with Particle Swarm Optimization and Elitist Non-Dominated Sorting Genetic Algorithm","authors":"Qingsong Wang;Siwei Li;Hao Ding;Ming Cheng;Giuseppe Buja","doi":"10.17775/CSEEJPES.2022.04510","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2022.04510","url":null,"abstract":"This paper addresses the planning problem of parallel DC electric springs (DCESs). DCES, a demand-side management method, realizes automatic matching of power consumption and power generation by adjusting non-critical load (NCL) and internal storage. It can offer higher power quality to critical load (CL), reduce power imbalance and relieve pressure on energy storage systems (RESs). In this paper, a planning method for parallel DCESs is proposed to maximize stability gain, economic benefits, and penetration of RESs. The planning model is a master optimization with sub-optimization to highlight the priority of objectives. Master optimization is used to improve stability of the network, and sub-optimization aims to improve economic benefit and allowable penetration of RESs. This issue is a multivariable nonlinear mixed integer problem, requiring huge calculations by using common solvers. Therefore, particle Swarm optimization (PSO) and Elitist non-dominated sorting genetic algorithm (NSGA-II) were used to solve this model. Considering uncertainty of RESs, this paper verifies effectiveness of the proposed planning method on IEEE 33-bus system based on deterministic scenarios obtained by scenario analysis.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"10 2","pages":"574-583"},"PeriodicalIF":7.1,"publicationDate":"2023-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10165667","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140351541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In order to improve the ability of power transmission system to cope with compound faults on the communication side and power side, a cyber-physical collaborative restoration strategy is proposed. First, according to the information system's role in fault diagnosis, remote control of equipment maintenance and automatic output adjustment of generator restoration, a cyber-physical coupling model is proposed. On this basis, a collaborative restoration model of power transmission system is established by studying interactions among maintenance schedule paths, information system operation, and power system operation. Based on power flow linearization and the large M-∊ method, the above model is transformed into a mixed integer linear programming model, whose computational burden is reduced further by the clustering algorithm. According to the parameters of IEEE39 New England system, the geographic wiring diagram of the cyber-physical system is established. Simulation results show the proposed restoration strategy can consider the support function of the information system and space-time coordination of equipment maintenance at both sides comprehensively to speed up load recovery progress.
{"title":"Cyber-Physical Collaborative Restoration Strategy for Power Transmission System Considering Maintenance Scheduling","authors":"Baozhong Ti;Chuanyun Zhang;Jingfei Liu;Zhaoyuan Wu;Ziyang Huang","doi":"10.17775/CSEEJPES.2022.04440","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2022.04440","url":null,"abstract":"In order to improve the ability of power transmission system to cope with compound faults on the communication side and power side, a cyber-physical collaborative restoration strategy is proposed. First, according to the information system's role in fault diagnosis, remote control of equipment maintenance and automatic output adjustment of generator restoration, a cyber-physical coupling model is proposed. On this basis, a collaborative restoration model of power transmission system is established by studying interactions among maintenance schedule paths, information system operation, and power system operation. Based on power flow linearization and the large M-∊ method, the above model is transformed into a mixed integer linear programming model, whose computational burden is reduced further by the clustering algorithm. According to the parameters of IEEE39 New England system, the geographic wiring diagram of the cyber-physical system is established. Simulation results show the proposed restoration strategy can consider the support function of the information system and space-time coordination of equipment maintenance at both sides comprehensively to speed up load recovery progress.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"10 3","pages":"1331-1341"},"PeriodicalIF":7.1,"publicationDate":"2023-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10165666","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141304087","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hydrogen-enriched compressed natural gas (HCNG) has great potential for renewable energy and hydrogen utilization. However, injecting hydrogen into the natural gas network will change original fluid dynamics and complicate compressed gas's physical properties, threatening operational safety of the electricity-HCNG-integrated energy system (E-HCNG-IES). To resolve such problem, this paper investigates effect of HCNG on gas network dynamics and presents an improved HCNG network model, which embodies the influence of blending hydrogen on the pressure drop equation and line pack equation. In addition, an optimal dispatch model for the E-HCNG-IES, considering the “production-storage-blending-transportation-utilization” link of the HCNG supply chain, is also proposed. The dispatch model is converted into a mixed-integer second-order conic programming (MISOCP) problem using the second-order cone (SOC) relaxation and piecewise linearization techniques. An iterative algorithm is proposed based on the convex-concave procedure and bound-tightening method to obtain a tight solution. Finally, the proposed methodology is evaluated through two E-HCNG-IES numerical testbeds with different hydrogen volume fractions. Detailed operation analysis reveals that E-HCNG-IES can benefit from economic and environmental improvement with increased hydrogen volume fraction, despite declining energy delivery capacity and line pack flexibility.
{"title":"Network Modeling and Operation Optimization of Electricity-HCNG-Integrated Energy System","authors":"Yue Qiu;Suyang Zhou;Wei Gu;Yuping Lu;Xiao-Ping Zhang;Kang Zhang;Gaoyan Han;Hongkun Lyu","doi":"10.17775/CSEEJPES.2022.07810","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2022.07810","url":null,"abstract":"Hydrogen-enriched compressed natural gas (HCNG) has great potential for renewable energy and hydrogen utilization. However, injecting hydrogen into the natural gas network will change original fluid dynamics and complicate compressed gas's physical properties, threatening operational safety of the electricity-HCNG-integrated energy system (E-HCNG-IES). To resolve such problem, this paper investigates effect of HCNG on gas network dynamics and presents an improved HCNG network model, which embodies the influence of blending hydrogen on the pressure drop equation and line pack equation. In addition, an optimal dispatch model for the E-HCNG-IES, considering the “production-storage-blending-transportation-utilization” link of the HCNG supply chain, is also proposed. The dispatch model is converted into a mixed-integer second-order conic programming (MISOCP) problem using the second-order cone (SOC) relaxation and piecewise linearization techniques. An iterative algorithm is proposed based on the convex-concave procedure and bound-tightening method to obtain a tight solution. Finally, the proposed methodology is evaluated through two E-HCNG-IES numerical testbeds with different hydrogen volume fractions. Detailed operation analysis reveals that E-HCNG-IES can benefit from economic and environmental improvement with increased hydrogen volume fraction, despite declining energy delivery capacity and line pack flexibility.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"9 4","pages":"1251-1265"},"PeriodicalIF":0.0,"publicationDate":"2023-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/7054730/10213441/10165639.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50352009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-27DOI: 10.17775/CSEEJPES.2022.02210
Hoay Beng Gooi;Tianjing Wang;Yong Tang
With the booming of artificial intelligence (AI), Internet of Things (IoT), and high-speed communication technology, integrating these technologies to innovate the smart grid (SG) further is future development direction of the power grid. Driven by this trend, billions of devices in the SG are connected to the Internet and generate a large amount of data at network edge. To reduce pressure of cloud computing and overcome defects of centralized learning, emergence of edge computing (EC) makes the computing task transfer from the network center to the network edge. When further exploring the relationship between EC and AI, edge intelligence (EI) has become one of the research hotspots. Advantages of EI in flexibly utilizing EC resources and improving AI model learning efficiency make its application in SG a good prospect. However, since only a few existing studies have applied EI to SG, this paper focuses on the application potential of EI in SG. First, the concepts, characteristics, frameworks, and key technologies of EI are investigated. Then, a comprehensive review of AI and EC applications in SG is presented. Furthermore, application potentials for EI in SG are explored, and four application scenarios of EI for SG are proposed. Finally, challenges and future directions for EI in SG are discussed. This application survey of EI on SG is carried out before EI enters the large-scale commercial stage to provide references and guidelines for developing future EI frameworks in the SG paradigm.
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