Pub Date : 2020-08-02DOI: 10.1109/PESGM41954.2020.9281496
Huanfeng Zhao, Shengtao Fan, A. Gole
This paper extends the analysis of the stability of electromagnetic transient simulation algorithms to non-linear systems with switching elements and non-linear inductor branches. A theoretical analysis based on common quadratic Lyapunov function (CQLF) theory is used to investigate the stability of numerical algorithms for the simulation of lumped strictly passive switched circuits (LSPSC). It is proved that only when certain fundamental physical properties, i.e., passivity and invariance of Lyapunov energy function are satisfied, does the widely used trapezoidal method result in stable simulations of such networks for any time-step size. This is different from the simulation of linear time invariant (LTI) systems where any real world stable system has a stable simulation if an A-stable integration method (e.g., trapezoidal rule) is used. Subsequently, it is shown that the problem of simulating a piecewise linear inductor can be equivalent to simulating a LSPSC; and ergo its simulation with the trapezoidal rule is also stable.
{"title":"Stability of Algorithms for Electro-MagneticTransient Simulation of Networks with Switches and Non-linear Inductors","authors":"Huanfeng Zhao, Shengtao Fan, A. Gole","doi":"10.1109/PESGM41954.2020.9281496","DOIUrl":"https://doi.org/10.1109/PESGM41954.2020.9281496","url":null,"abstract":"This paper extends the analysis of the stability of electromagnetic transient simulation algorithms to non-linear systems with switching elements and non-linear inductor branches. A theoretical analysis based on common quadratic Lyapunov function (CQLF) theory is used to investigate the stability of numerical algorithms for the simulation of lumped strictly passive switched circuits (LSPSC). It is proved that only when certain fundamental physical properties, i.e., passivity and invariance of Lyapunov energy function are satisfied, does the widely used trapezoidal method result in stable simulations of such networks for any time-step size. This is different from the simulation of linear time invariant (LTI) systems where any real world stable system has a stable simulation if an A-stable integration method (e.g., trapezoidal rule) is used. Subsequently, it is shown that the problem of simulating a piecewise linear inductor can be equivalent to simulating a LSPSC; and ergo its simulation with the trapezoidal rule is also stable.","PeriodicalId":106476,"journal":{"name":"2020 IEEE Power & Energy Society General Meeting (PESGM)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115633693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-02DOI: 10.1109/PESGM41954.2020.9281457
Wei Feng, Qingxin Shi, Hantao Cui, F. Li, Chen Yuan, Renchang Dai, Guangyi Liu
This paper proposes an improved state estimation (SE) method by combining Lagrangian relaxation and WLS (weighted least square) such that the operating limits of voltage sourced converter based multi-terminal direct current (VSC-MTDC) system are considered. Taking advantage of the fast-regulating ability of pulse-width modulation (PWM), the operating range of the converter is strictly restricted within limits. In addition, when the limits violate, the new control strategy can be executed in a very short time to ensure safe operation. However, the conventional SE approaches, which rely on global optimization, may fail to tackle the operating limits due to the different measurement errors of AC and DC grids. To improve the accuracy of SE for VSC-MTDC system, an improved SE method is proposed with three main contributions. First, the operating limits, together with the regulations, are analyzed in detail. Then, a violation-checking procedure is implemented inside the Sequential Method. Finally, once the violated estimations are detected, the corresponding equality constraints which represent the precise operating points are added in WLS and solved by Lagrangian relaxation. The accuracy and efficiency of the proposed method are tested on two typical systems with different control parameters.
{"title":"Using Lagrangian Relaxation to Include Operating Limits of VSC-MTDC System for State Estimation","authors":"Wei Feng, Qingxin Shi, Hantao Cui, F. Li, Chen Yuan, Renchang Dai, Guangyi Liu","doi":"10.1109/PESGM41954.2020.9281457","DOIUrl":"https://doi.org/10.1109/PESGM41954.2020.9281457","url":null,"abstract":"This paper proposes an improved state estimation (SE) method by combining Lagrangian relaxation and WLS (weighted least square) such that the operating limits of voltage sourced converter based multi-terminal direct current (VSC-MTDC) system are considered. Taking advantage of the fast-regulating ability of pulse-width modulation (PWM), the operating range of the converter is strictly restricted within limits. In addition, when the limits violate, the new control strategy can be executed in a very short time to ensure safe operation. However, the conventional SE approaches, which rely on global optimization, may fail to tackle the operating limits due to the different measurement errors of AC and DC grids. To improve the accuracy of SE for VSC-MTDC system, an improved SE method is proposed with three main contributions. First, the operating limits, together with the regulations, are analyzed in detail. Then, a violation-checking procedure is implemented inside the Sequential Method. Finally, once the violated estimations are detected, the corresponding equality constraints which represent the precise operating points are added in WLS and solved by Lagrangian relaxation. The accuracy and efficiency of the proposed method are tested on two typical systems with different control parameters.","PeriodicalId":106476,"journal":{"name":"2020 IEEE Power & Energy Society General Meeting (PESGM)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115638787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-02DOI: 10.1109/PESGM41954.2020.9281553
Pengyuan Wang, Honggang Wang, Philip J. Hart, Xian Guo, Kaveri Mahapatra
The day-to-day operation of modern power systems is highly reliant on prompt and adequate situational-awareness. This can be achieved via various system monitoring functions such as anomaly detection, in which static thresholds are commonly utilized to distinguish the normal and the abnormal system states. However, a predetermined static threshold usually lacks the flexibility to adapt to unobserved scenarios. In this paper, we propose two self-adaptive synchrophasor data driven anomaly detection approaches based on Chebyshev’s Inequality. The proposed approaches have been evaluated with Kundur’s 2area system and Mini-WECC system. Experimental results verify that the proposed approaches can dynamically adapt to unprecedented scenarios, and detect anomalous events with lower false alarm rate compared to static threshold based detection.
{"title":"Application of Chebyshev’s Inequality in Online Anomaly Detection Driven by Streaming PMU Data","authors":"Pengyuan Wang, Honggang Wang, Philip J. Hart, Xian Guo, Kaveri Mahapatra","doi":"10.1109/PESGM41954.2020.9281553","DOIUrl":"https://doi.org/10.1109/PESGM41954.2020.9281553","url":null,"abstract":"The day-to-day operation of modern power systems is highly reliant on prompt and adequate situational-awareness. This can be achieved via various system monitoring functions such as anomaly detection, in which static thresholds are commonly utilized to distinguish the normal and the abnormal system states. However, a predetermined static threshold usually lacks the flexibility to adapt to unobserved scenarios. In this paper, we propose two self-adaptive synchrophasor data driven anomaly detection approaches based on Chebyshev’s Inequality. The proposed approaches have been evaluated with Kundur’s 2area system and Mini-WECC system. Experimental results verify that the proposed approaches can dynamically adapt to unprecedented scenarios, and detect anomalous events with lower false alarm rate compared to static threshold based detection.","PeriodicalId":106476,"journal":{"name":"2020 IEEE Power & Energy Society General Meeting (PESGM)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117352914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-02DOI: 10.1109/PESGM41954.2020.9282041
G. Chang, Yong-Han Hong, Guan-Yi Li
Voltage sags are often manifested as the permanent or incipient faults occurred in the power system because of equipment malfunctions or failures. The incipient faults which are originally self-cleaning faults may repeatedly occur and gradually develop to a permanent fault after its first occurrence. The incipient fault detection is considered as a crucial task in predictive maintenance for power equipment such as transformers, circuit breakers, and underground cables. This paper proposes a hybrid method for incipient faults detection and classification. The proposed method firstly adopts two extraction methods and two feature measures to obtain seven peculiar features from voltage waveforms of abnormal phases recorded by power quality monitors at substations in a transmission network. Then, a feature selection method and the support vector machine combined with particle swarm optimization are applied to classify various types of incipient faults. Test results show that the proposed method contributes relatively accurate classification of incipient faults and can be employed as a useful tool for condition monitoring of major power equipment in the transmission network.
{"title":"A Hybrid Intelligent Approach for Classification of Incipient Faults in Transmission Network","authors":"G. Chang, Yong-Han Hong, Guan-Yi Li","doi":"10.1109/PESGM41954.2020.9282041","DOIUrl":"https://doi.org/10.1109/PESGM41954.2020.9282041","url":null,"abstract":"Voltage sags are often manifested as the permanent or incipient faults occurred in the power system because of equipment malfunctions or failures. The incipient faults which are originally self-cleaning faults may repeatedly occur and gradually develop to a permanent fault after its first occurrence. The incipient fault detection is considered as a crucial task in predictive maintenance for power equipment such as transformers, circuit breakers, and underground cables. This paper proposes a hybrid method for incipient faults detection and classification. The proposed method firstly adopts two extraction methods and two feature measures to obtain seven peculiar features from voltage waveforms of abnormal phases recorded by power quality monitors at substations in a transmission network. Then, a feature selection method and the support vector machine combined with particle swarm optimization are applied to classify various types of incipient faults. Test results show that the proposed method contributes relatively accurate classification of incipient faults and can be employed as a useful tool for condition monitoring of major power equipment in the transmission network.","PeriodicalId":106476,"journal":{"name":"2020 IEEE Power & Energy Society General Meeting (PESGM)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120815390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-02DOI: 10.1109/PESGM41954.2020.9282047
T. Mesbahi, P. Bartholomeus, I. Jorge
The work proposed in this paper deals with an improved configuration of hybrid embedded power supply in electric vehicle applications. New requirements for energy storage systems in the transportation domain are necessary, including high power and energy density, long lifetime, high dynamic charge acceptance particularly for regenerative braking, lightweight design, and relatively modest cost. In order to enhance the system performances and achieve these targets, the proposed system is composed of high-energy density lithium-ion battery as the main source and ultra-high power lithium-ion battery as an auxiliary source. The sizing process of this hybrid embedded power supply incorporating the optimization of the power split between both batteries is carried out thanks to a hybrid Particle Swarm–Nelder–Mead optimization algorithm. Obtained results show that the proposed configuration improves the dynamic charge and discharge, and decreases the power stress applied to the battery. Furthermore, the weight of the hybrid embedded power system is significantly enhanced compared to regular supply using single lithium-ion battery.
{"title":"Hybrid Embedded Power Supply Combining High-Energy Density and Ultra-High Power Lithium-ion Batteries For Electric Vehicle Applications","authors":"T. Mesbahi, P. Bartholomeus, I. Jorge","doi":"10.1109/PESGM41954.2020.9282047","DOIUrl":"https://doi.org/10.1109/PESGM41954.2020.9282047","url":null,"abstract":"The work proposed in this paper deals with an improved configuration of hybrid embedded power supply in electric vehicle applications. New requirements for energy storage systems in the transportation domain are necessary, including high power and energy density, long lifetime, high dynamic charge acceptance particularly for regenerative braking, lightweight design, and relatively modest cost. In order to enhance the system performances and achieve these targets, the proposed system is composed of high-energy density lithium-ion battery as the main source and ultra-high power lithium-ion battery as an auxiliary source. The sizing process of this hybrid embedded power supply incorporating the optimization of the power split between both batteries is carried out thanks to a hybrid Particle Swarm–Nelder–Mead optimization algorithm. Obtained results show that the proposed configuration improves the dynamic charge and discharge, and decreases the power stress applied to the battery. Furthermore, the weight of the hybrid embedded power system is significantly enhanced compared to regular supply using single lithium-ion battery.","PeriodicalId":106476,"journal":{"name":"2020 IEEE Power & Energy Society General Meeting (PESGM)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120968074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-02DOI: 10.1109/PESGM41954.2020.9281577
Shuai Zhang, Xingzhen Bai, Leijiao Ge, Jun Yan
Energy storage systems are promising solutions to the mitigation of power fluctuations and the management of load demands in distribution networks. However, the uncertainty of load demands and wind generations increasingly seen in distribution networks may have a great impact on the configuration of ESS. To solve the problem, a novel optimal configuration method for energy storage system is proposed to reduce the influence of uncertainty of both load demands and WGs. The proposed method first reduce the uncertainty of load through a comprehensive demand response system based on time-of-use and incentive. Then, to predict the output of wind generations, we use the particle swarm optimization and backpropagation neural network to create a predictive model of the wind power. Then, an optimal configuration model is established to minimize the ESS investment cost and the network power loss reduction, subject to technical constraints such as ESS operational constraints and power balance constraint et al. An improved simulated annealing PSO algorithm is used to solve the optimization problem. Finally, the numerical studies on a modified IEEE 33-node distribution system show the advantages of the proposed methodology.
{"title":"Optimal Configuration of Energy Storage System Considering Uncertainty of Load and Wind Generation","authors":"Shuai Zhang, Xingzhen Bai, Leijiao Ge, Jun Yan","doi":"10.1109/PESGM41954.2020.9281577","DOIUrl":"https://doi.org/10.1109/PESGM41954.2020.9281577","url":null,"abstract":"Energy storage systems are promising solutions to the mitigation of power fluctuations and the management of load demands in distribution networks. However, the uncertainty of load demands and wind generations increasingly seen in distribution networks may have a great impact on the configuration of ESS. To solve the problem, a novel optimal configuration method for energy storage system is proposed to reduce the influence of uncertainty of both load demands and WGs. The proposed method first reduce the uncertainty of load through a comprehensive demand response system based on time-of-use and incentive. Then, to predict the output of wind generations, we use the particle swarm optimization and backpropagation neural network to create a predictive model of the wind power. Then, an optimal configuration model is established to minimize the ESS investment cost and the network power loss reduction, subject to technical constraints such as ESS operational constraints and power balance constraint et al. An improved simulated annealing PSO algorithm is used to solve the optimization problem. Finally, the numerical studies on a modified IEEE 33-node distribution system show the advantages of the proposed methodology.","PeriodicalId":106476,"journal":{"name":"2020 IEEE Power & Energy Society General Meeting (PESGM)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125072927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-02DOI: 10.1109/PESGM41954.2020.9281878
Rasel Mahmud, Andy Hoke, D. Narang
Inverter-based DER responses to faults on the electric power system are different than those of conventional generators and are often poorly understood. Inverter fault responses are largely software-defined, within physics-based constraints. DERs are regulated by standards and grid codes that also constrain their responses. Though fault response of DERs will vary widely, for any DER following any particular standard, a pattern of fault response can be synthesized by observing that particular standard. In this paper, the recently published IEEE 1547-2018 is examined to explore the general fault response of any DER that follows IEEE 1547-2018. Additionally, an IEEE 1547-2018 compliant inverter model is developed and tested in simulation to find the fault response, and that response is compared with the fault response of a commercial off-the-shelf inverter.
{"title":"Fault Response of Distributed Energy Resources Considering the Requirements of IEEE 1547-2018","authors":"Rasel Mahmud, Andy Hoke, D. Narang","doi":"10.1109/PESGM41954.2020.9281878","DOIUrl":"https://doi.org/10.1109/PESGM41954.2020.9281878","url":null,"abstract":"Inverter-based DER responses to faults on the electric power system are different than those of conventional generators and are often poorly understood. Inverter fault responses are largely software-defined, within physics-based constraints. DERs are regulated by standards and grid codes that also constrain their responses. Though fault response of DERs will vary widely, for any DER following any particular standard, a pattern of fault response can be synthesized by observing that particular standard. In this paper, the recently published IEEE 1547-2018 is examined to explore the general fault response of any DER that follows IEEE 1547-2018. Additionally, an IEEE 1547-2018 compliant inverter model is developed and tested in simulation to find the fault response, and that response is compared with the fault response of a commercial off-the-shelf inverter.","PeriodicalId":106476,"journal":{"name":"2020 IEEE Power & Energy Society General Meeting (PESGM)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125092666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-02DOI: 10.1109/PESGM41954.2020.9281612
S. Islam, M. A. Mahmud, A. Oo
In this paper, a new low-latency communication scheme is designed for blockchain based peer to peer (P2P) energy trading. The proposed scheme ensures that the energy supply/demand mismatch information is extracted more reliably in P2P energy trading and the participants do not lose profit due to errors. This scheme allows neighbouring prosumers equipped with home energy management system (HEMS) to cooperate by forwarding the extracted information from each other’s energy transaction blocks. The error performance of this scheme has been derived and compared with a direct decode-and-forward (DF) scheme, which has much higher latency. The numerical simulation results demonstrate that the proposed scheme can transfer the energy mismatch information with more accuracy compared to the direct DF scheme and achieve the expected profits when worst case error performannce is considered. On the other hand, the proposed scheme can achieve the same average error performance as direct DF with a constant SNR penalty that does not degrade with channel conditions.
{"title":"A Communication Scheme for Blockchain based Peer to Peer Energy Trading","authors":"S. Islam, M. A. Mahmud, A. Oo","doi":"10.1109/PESGM41954.2020.9281612","DOIUrl":"https://doi.org/10.1109/PESGM41954.2020.9281612","url":null,"abstract":"In this paper, a new low-latency communication scheme is designed for blockchain based peer to peer (P2P) energy trading. The proposed scheme ensures that the energy supply/demand mismatch information is extracted more reliably in P2P energy trading and the participants do not lose profit due to errors. This scheme allows neighbouring prosumers equipped with home energy management system (HEMS) to cooperate by forwarding the extracted information from each other’s energy transaction blocks. The error performance of this scheme has been derived and compared with a direct decode-and-forward (DF) scheme, which has much higher latency. The numerical simulation results demonstrate that the proposed scheme can transfer the energy mismatch information with more accuracy compared to the direct DF scheme and achieve the expected profits when worst case error performannce is considered. On the other hand, the proposed scheme can achieve the same average error performance as direct DF with a constant SNR penalty that does not degrade with channel conditions.","PeriodicalId":106476,"journal":{"name":"2020 IEEE Power & Energy Society General Meeting (PESGM)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123417263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-02DOI: 10.1109/PESGM41954.2020.9281643
Timur Saifutdinov, C. Patsios, P. Vorobev, E. Gryazina, D. Greenwood, J. Bialek, P. Taylor
This paper addresses the problem of optimal siting, sizing, and technology selection of Energy Storage System (ESS) considering degradation arising from state of charge and Depth of Discharge (DoD). The capacity lost irreversibly due to degradation provides the optimizer with a more accurate and realistic view of the capacity available throughout the asset’s entire lifetime as it depends on the actual operating profiles and particular degradation mechanisms. When taking into account the ESS’s degradation, the optimization problem becomes nonconvex, therefore no standard solver can guarantee the globally optimal solution. To overcome this, the optimization problem has been reformulated to a Mixed Integer Convex Programming (MICP) problem by substituting continuous variables that cause nonconvexity with discrete ones. The resulting MICP problem has been solved using the Branch-and-Bound algorithm along with convex programming, which performs an efficient search and guarantees the globally optimal solution. We found that the optimal battery use does not necesseraly correspond to it reaching its End of Life state at the end of the service lifetime, which is the result of nonlinear degradation mechanicms from both idling and cycling. Finally, the proposed methodology allows formulating computationally tractable stochastic optimization problem to account for future network scenarios.
{"title":"Degradation and Operation-Aware Framework for the Optimal Siting, Sizing and Technology Selection of Battery Storage","authors":"Timur Saifutdinov, C. Patsios, P. Vorobev, E. Gryazina, D. Greenwood, J. Bialek, P. Taylor","doi":"10.1109/PESGM41954.2020.9281643","DOIUrl":"https://doi.org/10.1109/PESGM41954.2020.9281643","url":null,"abstract":"This paper addresses the problem of optimal siting, sizing, and technology selection of Energy Storage System (ESS) considering degradation arising from state of charge and Depth of Discharge (DoD). The capacity lost irreversibly due to degradation provides the optimizer with a more accurate and realistic view of the capacity available throughout the asset’s entire lifetime as it depends on the actual operating profiles and particular degradation mechanisms. When taking into account the ESS’s degradation, the optimization problem becomes nonconvex, therefore no standard solver can guarantee the globally optimal solution. To overcome this, the optimization problem has been reformulated to a Mixed Integer Convex Programming (MICP) problem by substituting continuous variables that cause nonconvexity with discrete ones. The resulting MICP problem has been solved using the Branch-and-Bound algorithm along with convex programming, which performs an efficient search and guarantees the globally optimal solution. We found that the optimal battery use does not necesseraly correspond to it reaching its End of Life state at the end of the service lifetime, which is the result of nonlinear degradation mechanicms from both idling and cycling. Finally, the proposed methodology allows formulating computationally tractable stochastic optimization problem to account for future network scenarios.","PeriodicalId":106476,"journal":{"name":"2020 IEEE Power & Energy Society General Meeting (PESGM)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115103235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-02DOI: 10.1109/PESGM41954.2020.9281777
T. Lan, Zhangxin Zhou, Garng M. Huang
In recent years, many new trends, such as large-scale renewable generations, electric cars and demand response, appear in power systems. Grid uncertainties are greatly increased due to the new trends. Thus, it is necessary to consider the impact of grid uncertainties in the decision-making process of optimal transmission switching. In this paper, a stochastic programming based approach is proposed for optimal transmission switching problems. Grid uncertainties are represented by different scenarios and are taken into consideration in the proposed approach. This new approach is based on the ACOPF and the scenario reduction technique is adopted to preserve only the key scenarios in the stochastic programming formulation. The corresponding scheme is designed for scheduling and online operation. The proposed scheme is validated on the South Carolina-500 bus synthetic system.
{"title":"An AC Stochastic Optimal Transmission Switching Approach with Scenario Reduction Technique","authors":"T. Lan, Zhangxin Zhou, Garng M. Huang","doi":"10.1109/PESGM41954.2020.9281777","DOIUrl":"https://doi.org/10.1109/PESGM41954.2020.9281777","url":null,"abstract":"In recent years, many new trends, such as large-scale renewable generations, electric cars and demand response, appear in power systems. Grid uncertainties are greatly increased due to the new trends. Thus, it is necessary to consider the impact of grid uncertainties in the decision-making process of optimal transmission switching. In this paper, a stochastic programming based approach is proposed for optimal transmission switching problems. Grid uncertainties are represented by different scenarios and are taken into consideration in the proposed approach. This new approach is based on the ACOPF and the scenario reduction technique is adopted to preserve only the key scenarios in the stochastic programming formulation. The corresponding scheme is designed for scheduling and online operation. The proposed scheme is validated on the South Carolina-500 bus synthetic system.","PeriodicalId":106476,"journal":{"name":"2020 IEEE Power & Energy Society General Meeting (PESGM)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115244382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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