Pub Date : 2021-10-25DOI: 10.1109/SmartGridComm51999.2021.9632310
Hao Huang, Abheek Chatterjee, A. Layton, K. Davis
Power systems consist of interdependent cyber and physical networks: the physical network supplies energy to the cyber network for data exchange, while the data exchange provides for observation and operation of the power system. This mix of a physical and a cyber/information network means that network disturbances can be synthesized in both physical and cyber forms. Cyber incidents in particular have been increasing, highlighting the importance of both designing for and measuring the reliability and robustness of cyber networks. Industry guidelines exist to inform network designs for security and availability, but they are limited when it comes to being able to rigorously account for cyber-physical interdependencies in these networks. This presents cyber-physical network designers with a lack of design tools to guide network creation. This paper introduces a bio-inspired approach that has been successfully applied to the physical component of power networks, extending it for evaluation and guidance in a cyber-physical power system. The power system's cyber-physical network is modeled here as an ecological food web. The potential benefits of selected ecological metrics related to food web resilience are evaluated, including robustness $(R_{ECO})$, average mutual information (AMI), cyclicity $(lambda_{max})$ and cycling index (CI). The paper investigates the use of these metrics and our understanding of food web characteristics to enhance the resilience and robustness of cyber-physical network design and data routing. Two cases are explored to highlight this potential, a 3-substation and an 8-substation cyber-physical system. The analysis suggests that increasing redundancy in the network design and more equally distributing data flow can improve the security and availability of data being transferred to operators.
{"title":"An Investigation into Ecological Network Analysis for Cyber-Physical Power Systems","authors":"Hao Huang, Abheek Chatterjee, A. Layton, K. Davis","doi":"10.1109/SmartGridComm51999.2021.9632310","DOIUrl":"https://doi.org/10.1109/SmartGridComm51999.2021.9632310","url":null,"abstract":"Power systems consist of interdependent cyber and physical networks: the physical network supplies energy to the cyber network for data exchange, while the data exchange provides for observation and operation of the power system. This mix of a physical and a cyber/information network means that network disturbances can be synthesized in both physical and cyber forms. Cyber incidents in particular have been increasing, highlighting the importance of both designing for and measuring the reliability and robustness of cyber networks. Industry guidelines exist to inform network designs for security and availability, but they are limited when it comes to being able to rigorously account for cyber-physical interdependencies in these networks. This presents cyber-physical network designers with a lack of design tools to guide network creation. This paper introduces a bio-inspired approach that has been successfully applied to the physical component of power networks, extending it for evaluation and guidance in a cyber-physical power system. The power system's cyber-physical network is modeled here as an ecological food web. The potential benefits of selected ecological metrics related to food web resilience are evaluated, including robustness $(R_{ECO})$, average mutual information (AMI), cyclicity $(lambda_{max})$ and cycling index (CI). The paper investigates the use of these metrics and our understanding of food web characteristics to enhance the resilience and robustness of cyber-physical network design and data routing. Two cases are explored to highlight this potential, a 3-substation and an 8-substation cyber-physical system. The analysis suggests that increasing redundancy in the network design and more equally distributing data flow can improve the security and availability of data being transferred to operators.","PeriodicalId":378884,"journal":{"name":"2021 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131645056","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 : 2021-10-25DOI: 10.1109/SmartGridComm51999.2021.9632298
Jing Wang, Jeffery Simpson, Rui Yang, B. Palmintier, Soumya Tiwari, Y. Zhang
This paper presents performance evaluation of a new distributed energy resource management system (DERMS) algorithm via an advanced hardware-in-the-loop (HIL) platform. The HIL platform provides realistic testing in a laboratory environment, including the accurate modeling of sub-transmission and distribution networks, the DERMS software controller, and 84 power hardware solar photovoltaic (PV) inverters, standard communication protocols, and a capacitor bank controller. The DERMS algorithm is also called, Grid-Optimization of Solar (GO-Solar) platform which includes predictive state estimation (PSE) and online multiple objective optimization (OMOO) to dispatch the legacy devices and distributed energy resources (e.g., PV). The voltage regulation performance is evaluated under three scenarios, volt-var smart inverter (baseline), and DERMS control for 100% and 30% of PV. The results show that controlling 30% of PV systems with the GO-Solar platform may provide the best balance of control performance and implementation cost.
{"title":"Performance Evaluation of an Advanced Distributed Energy Resource Management Algorithm","authors":"Jing Wang, Jeffery Simpson, Rui Yang, B. Palmintier, Soumya Tiwari, Y. Zhang","doi":"10.1109/SmartGridComm51999.2021.9632298","DOIUrl":"https://doi.org/10.1109/SmartGridComm51999.2021.9632298","url":null,"abstract":"This paper presents performance evaluation of a new distributed energy resource management system (DERMS) algorithm via an advanced hardware-in-the-loop (HIL) platform. The HIL platform provides realistic testing in a laboratory environment, including the accurate modeling of sub-transmission and distribution networks, the DERMS software controller, and 84 power hardware solar photovoltaic (PV) inverters, standard communication protocols, and a capacitor bank controller. The DERMS algorithm is also called, Grid-Optimization of Solar (GO-Solar) platform which includes predictive state estimation (PSE) and online multiple objective optimization (OMOO) to dispatch the legacy devices and distributed energy resources (e.g., PV). The voltage regulation performance is evaluated under three scenarios, volt-var smart inverter (baseline), and DERMS control for 100% and 30% of PV. The results show that controlling 30% of PV systems with the GO-Solar platform may provide the best balance of control performance and implementation cost.","PeriodicalId":378884,"journal":{"name":"2021 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131086620","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 : 2021-10-25DOI: 10.1109/SmartGridComm51999.2021.9632318
Hang Du, Jun Yan, Mohsen Ghafouri, Rawad F. Zgheib, Marthe Kassouf, M. Debbabi
Subsynchronous resonance (SSR) is among the most severe instability conditions that may happen when grid-tied inverter-based renewable energy sources (RESs), like wind power, connect to a weak transmission grid. The potential impact of SSR includes loss of wind power generation, physical equipment damage, or instability that could spread to a larger area. Such risks make the subsynchronous stability of permanent magnet synchronous generator (PMSG) based wind farms a potential target for adversaries. To this end, this paper investigates and models two new cyber attack schemes targeting SSR in PMSG-based wind farms, which have high energy output and less maintenance. Considering the major causes and different damping controls for SSR in PMSG-based wind farms, this paper demonstrates the feasibility of the threat from the two proposed cyber attacks and compares them using the IEEE 9-bus benchmark. The results show that smartly craft cyber attacks can successfully degrade SSR damping, trigger an SSR, and even destabilize the power grid.
{"title":"Modeling of Cyber Attacks Against Converter-Driven Stability of PMSG-Based Wind Farms with Intentional Subsynchronous Resonance","authors":"Hang Du, Jun Yan, Mohsen Ghafouri, Rawad F. Zgheib, Marthe Kassouf, M. Debbabi","doi":"10.1109/SmartGridComm51999.2021.9632318","DOIUrl":"https://doi.org/10.1109/SmartGridComm51999.2021.9632318","url":null,"abstract":"Subsynchronous resonance (SSR) is among the most severe instability conditions that may happen when grid-tied inverter-based renewable energy sources (RESs), like wind power, connect to a weak transmission grid. The potential impact of SSR includes loss of wind power generation, physical equipment damage, or instability that could spread to a larger area. Such risks make the subsynchronous stability of permanent magnet synchronous generator (PMSG) based wind farms a potential target for adversaries. To this end, this paper investigates and models two new cyber attack schemes targeting SSR in PMSG-based wind farms, which have high energy output and less maintenance. Considering the major causes and different damping controls for SSR in PMSG-based wind farms, this paper demonstrates the feasibility of the threat from the two proposed cyber attacks and compares them using the IEEE 9-bus benchmark. The results show that smartly craft cyber attacks can successfully degrade SSR damping, trigger an SSR, and even destabilize the power grid.","PeriodicalId":378884,"journal":{"name":"2021 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114864146","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 : 2021-10-25DOI: 10.1109/SmartGridComm51999.2021.9632324
Mehrdad Sheikholeslami, Zuyi Li
This paper presents the challenges and also suggests solutions associated with developing data communication interfaces between real-time digital simulator (RTDS) and hardware or software devices under study. While RTDS supports a wide range of standard and well-established communication protocols, employing such communication protocols generally increases the cost of the educational project as these standard communication protocols require licenses as well as third-party hardware and software devices to act as gateways. The need for these licenses and third-party hardware and software devices adds to the total cost of the project and also requires additional training. This paper provides two sets of cost-effective data interface solutions for local and remote networks based on the lessons learned from different projects that the authors were involved with. These practical solutions are especially useful for projects that involve multiple partners located remotely that are facing logistic challenges due to the Covid-19 pandemic.
{"title":"Data Communication Interfaces in Smart Grid Real-time Simulations: Challenges and Solutions","authors":"Mehrdad Sheikholeslami, Zuyi Li","doi":"10.1109/SmartGridComm51999.2021.9632324","DOIUrl":"https://doi.org/10.1109/SmartGridComm51999.2021.9632324","url":null,"abstract":"This paper presents the challenges and also suggests solutions associated with developing data communication interfaces between real-time digital simulator (RTDS) and hardware or software devices under study. While RTDS supports a wide range of standard and well-established communication protocols, employing such communication protocols generally increases the cost of the educational project as these standard communication protocols require licenses as well as third-party hardware and software devices to act as gateways. The need for these licenses and third-party hardware and software devices adds to the total cost of the project and also requires additional training. This paper provides two sets of cost-effective data interface solutions for local and remote networks based on the lessons learned from different projects that the authors were involved with. These practical solutions are especially useful for projects that involve multiple partners located remotely that are facing logistic challenges due to the Covid-19 pandemic.","PeriodicalId":378884,"journal":{"name":"2021 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114764948","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 : 2021-10-25DOI: 10.1109/SmartGridComm51999.2021.9632294
Qiyue Li, Shengquan Dai, Ximing Li, Weitao Li, Wei Sun
When a fault occurs in the active distribution network, it's important to divide islands according to the realtime operating status of the grid to form multiple independent microgrid systems. However, existing methods of island partition ignore the actual communication requirements of the active distribution network, so it is difficult to adapt to the impact of fluctuations in the communication quality of grid nodes, which may cause the performance of the system to deteriorate. This paper proposes an active distribution network island partition method based on graph convolutional network combined with autoencoder, which considers grid communication delay constraints and multi-objective optimization. Detailed simulation and experimental results show that the method can divide the partitions reasonably and effectively which can meet the power grid's energy and information requirements and achieve the established multiple optimization goals.
{"title":"Graph Convolution Networks-Based Island Partition for Energy and Information Coupled Active Distribution Systems","authors":"Qiyue Li, Shengquan Dai, Ximing Li, Weitao Li, Wei Sun","doi":"10.1109/SmartGridComm51999.2021.9632294","DOIUrl":"https://doi.org/10.1109/SmartGridComm51999.2021.9632294","url":null,"abstract":"When a fault occurs in the active distribution network, it's important to divide islands according to the realtime operating status of the grid to form multiple independent microgrid systems. However, existing methods of island partition ignore the actual communication requirements of the active distribution network, so it is difficult to adapt to the impact of fluctuations in the communication quality of grid nodes, which may cause the performance of the system to deteriorate. This paper proposes an active distribution network island partition method based on graph convolutional network combined with autoencoder, which considers grid communication delay constraints and multi-objective optimization. Detailed simulation and experimental results show that the method can divide the partitions reasonably and effectively which can meet the power grid's energy and information requirements and achieve the established multiple optimization goals.","PeriodicalId":378884,"journal":{"name":"2021 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129216860","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 : 2021-10-25DOI: 10.1109/SmartGridComm51999.2021.9632290
Leonard Fisser, A. Timm‐Giel
Exchanging information between actively-managed components is key for establishing distributed control schemes in future Low Voltage Distribution Grids (LVDGs). Each node's measurements and control data has to be disseminated to all other nodes in the electrical grid, to allow for safe operation and control. However, periodic all-to-all flooding procedures are challenging for wireless communication networks and especially so, if end-to-end reliability is required. The effectiveness of a flooding protocol is well captured in the Age of Information (AoI) performance indicator, combining the time it took to disseminate a data chunk and the time in between updates. Existing flooding protocols are not concerned with keeping AoI low in scenarios where status updates have to be continuously distributed. We propose a novel Parallel Sequential All-to-All Flooding (PSAA) protocol which is tailored to LVDGs and tries to minimize the average AoI. Special focus is given to the relation between AoI and retransmissions which are necessitated by unreliable communication channels. We show that PSAA is able to significantly outperform simple flooding schemes in characteristic LVDG topologies. Extensive simulation studies highlight the interaction between retransmission timer and AoI.
{"title":"Minimizing Age of Information for Distributed Control in Smart Grids","authors":"Leonard Fisser, A. Timm‐Giel","doi":"10.1109/SmartGridComm51999.2021.9632290","DOIUrl":"https://doi.org/10.1109/SmartGridComm51999.2021.9632290","url":null,"abstract":"Exchanging information between actively-managed components is key for establishing distributed control schemes in future Low Voltage Distribution Grids (LVDGs). Each node's measurements and control data has to be disseminated to all other nodes in the electrical grid, to allow for safe operation and control. However, periodic all-to-all flooding procedures are challenging for wireless communication networks and especially so, if end-to-end reliability is required. The effectiveness of a flooding protocol is well captured in the Age of Information (AoI) performance indicator, combining the time it took to disseminate a data chunk and the time in between updates. Existing flooding protocols are not concerned with keeping AoI low in scenarios where status updates have to be continuously distributed. We propose a novel Parallel Sequential All-to-All Flooding (PSAA) protocol which is tailored to LVDGs and tries to minimize the average AoI. Special focus is given to the relation between AoI and retransmissions which are necessitated by unreliable communication channels. We show that PSAA is able to significantly outperform simple flooding schemes in characteristic LVDG topologies. Extensive simulation studies highlight the interaction between retransmission timer and AoI.","PeriodicalId":378884,"journal":{"name":"2021 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123857262","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 : 2021-10-25DOI: 10.1109/smartgridcomm51999.2021.9632336
M. Kamal, A. Shahsavari, Hamed Mohsenian Rad
Distribution-level phasor measurement units (D-PMUs), a.k.a., micro-PMUs, have received a growing attention in recent years to support various applications in power distribution systems. Many of the applications of micro-PMUs work based on the analysis of events in the stream of synchrophasor measurements to achieve situational awareness. A key step in almost every event-based method in this emerging field is to classify the type of the event, where classification can be done with respect to various factors. However, if the task of event classification is compromised, then an adversary can highly affect the perception of the utility operator and undermine any event-based application that makes use of the event classification results. In this paper, we explore a new cyber-threat against data-driven event classification in micro-PMU measurements. In particular, we model the poisoning attack against support vector machine (SVM) as the method of event classification; which has been used in practice to study distribution synchrophasors. We apply the new attack model to an event classifier that uses real-world micro-PMU data. In addition to conducting vulnerability analysis, we also propose a novel attack detection method which can detect and evaluate the changes in the decision boundary of the SVM due to the poisoning attack. The proposed attack detection method is also able to identify the number of poisoned data points in the training dataset.
{"title":"Poisoning Attack against Event Classification in Distribution Synchrophasor Measurements","authors":"M. Kamal, A. Shahsavari, Hamed Mohsenian Rad","doi":"10.1109/smartgridcomm51999.2021.9632336","DOIUrl":"https://doi.org/10.1109/smartgridcomm51999.2021.9632336","url":null,"abstract":"Distribution-level phasor measurement units (D-PMUs), a.k.a., micro-PMUs, have received a growing attention in recent years to support various applications in power distribution systems. Many of the applications of micro-PMUs work based on the analysis of events in the stream of synchrophasor measurements to achieve situational awareness. A key step in almost every event-based method in this emerging field is to classify the type of the event, where classification can be done with respect to various factors. However, if the task of event classification is compromised, then an adversary can highly affect the perception of the utility operator and undermine any event-based application that makes use of the event classification results. In this paper, we explore a new cyber-threat against data-driven event classification in micro-PMU measurements. In particular, we model the poisoning attack against support vector machine (SVM) as the method of event classification; which has been used in practice to study distribution synchrophasors. We apply the new attack model to an event classifier that uses real-world micro-PMU data. In addition to conducting vulnerability analysis, we also propose a novel attack detection method which can detect and evaluate the changes in the decision boundary of the SVM due to the poisoning attack. The proposed attack detection method is also able to identify the number of poisoned data points in the training dataset.","PeriodicalId":378884,"journal":{"name":"2021 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125273132","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 : 2021-10-25DOI: 10.1109/SmartGridComm51999.2021.9632323
Niklas Ebell, M. Pruckner
The energy transition towards a more sustainable, secure and affordable electrical power system consisting of high shares of renewable energy sources increases the energy system's complexity. It creates an energy system in a more decentralized pattern with many more stakeholders involved. In this context, new data-driven operation control strategies play an important role in order to provide fast decision support and a better coordination of electrical assets in the distribution grid. In this paper, we evaluate a novel Multi-Agent Reinforcement Learning approach which focuses on cooperative agents with only local state information and aim to balance the electricity generation and consumption of an energy community consisting of ten households. This approach is compared to a rule-based and an optimal control policy. Results show that independent Q-learner achieve performance 35 % better than rule-based control and compensate high computational effort with adaptability, simplicity in communication requirements and respect of data-privacy.
{"title":"Benchmarking a Decentralized Reinforcement Learning Control Strategy for an Energy Community","authors":"Niklas Ebell, M. Pruckner","doi":"10.1109/SmartGridComm51999.2021.9632323","DOIUrl":"https://doi.org/10.1109/SmartGridComm51999.2021.9632323","url":null,"abstract":"The energy transition towards a more sustainable, secure and affordable electrical power system consisting of high shares of renewable energy sources increases the energy system's complexity. It creates an energy system in a more decentralized pattern with many more stakeholders involved. In this context, new data-driven operation control strategies play an important role in order to provide fast decision support and a better coordination of electrical assets in the distribution grid. In this paper, we evaluate a novel Multi-Agent Reinforcement Learning approach which focuses on cooperative agents with only local state information and aim to balance the electricity generation and consumption of an energy community consisting of ten households. This approach is compared to a rule-based and an optimal control policy. Results show that independent Q-learner achieve performance 35 % better than rule-based control and compensate high computational effort with adaptability, simplicity in communication requirements and respect of data-privacy.","PeriodicalId":378884,"journal":{"name":"2021 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116772387","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 : 2021-10-25DOI: 10.1109/SmartGridComm51999.2021.9632295
Philipp Maucher, H. Lens
The dynamic requirements for the provision of Frequency Containment Reserves (FCR) in Continental Europe are defined in the respective network codes (e.g. System Operation Guideline). However, this definition is precise only for a sudden frequency deviation of ±200 mHz. The requirements for smaller and/or slower frequency deviations are only described indirectly by referring to the case of ±200 mHz. As a result, different interpretations are possible, among which requiring activation dynamics that a) correspond to a linear time-invariant (LTI) system or b) exhibit a constant rate of change of power (RoCoP). This paper assesses the effects of these two different requirement interpretations on FCR providers and system stability by comparing their effect for different frequency deviations. It turns out that the RoCoP interpretation is disadvantageous, as it provides a slower response for large and fast frequency deviations and a fast response for small frequency deviations. Apart from Battery Energy Storage Systems (BESS), most FCR providers cannot perform FCR activation with a fixed RoCoP. In a further step, we consider the effects of the different requirement interpretations on system stability. For a constant RoCoP, it is assumed that the FCR is provided by BESS, while a conventional power plant model is used to implement LTI behavior. The comparison is performed both with model parameters corresponding to the current grid and with model parameters corresponding to a future grid. For each grid model, two scenarios are considered: The first scenario considers active power imbalances caused by load noise only (normal operation), while the second takes an additional significant generation outage into account (contingency). The results show that, in the load noise scenario, FCR activation with constant RoCoP reduces the frequency deviations slightly at the cost of higher total FCR provision and higher maximum FCR activation. However, in case of an additional generation outage, constant RoCoP activation results in a larger maximum frequency deviation, which means that the stability margin of the system is reduced.
{"title":"On the specification of requirements for the activation dynamics of Frequency Containment Reserves","authors":"Philipp Maucher, H. Lens","doi":"10.1109/SmartGridComm51999.2021.9632295","DOIUrl":"https://doi.org/10.1109/SmartGridComm51999.2021.9632295","url":null,"abstract":"The dynamic requirements for the provision of Frequency Containment Reserves (FCR) in Continental Europe are defined in the respective network codes (e.g. System Operation Guideline). However, this definition is precise only for a sudden frequency deviation of ±200 mHz. The requirements for smaller and/or slower frequency deviations are only described indirectly by referring to the case of ±200 mHz. As a result, different interpretations are possible, among which requiring activation dynamics that a) correspond to a linear time-invariant (LTI) system or b) exhibit a constant rate of change of power (RoCoP). This paper assesses the effects of these two different requirement interpretations on FCR providers and system stability by comparing their effect for different frequency deviations. It turns out that the RoCoP interpretation is disadvantageous, as it provides a slower response for large and fast frequency deviations and a fast response for small frequency deviations. Apart from Battery Energy Storage Systems (BESS), most FCR providers cannot perform FCR activation with a fixed RoCoP. In a further step, we consider the effects of the different requirement interpretations on system stability. For a constant RoCoP, it is assumed that the FCR is provided by BESS, while a conventional power plant model is used to implement LTI behavior. The comparison is performed both with model parameters corresponding to the current grid and with model parameters corresponding to a future grid. For each grid model, two scenarios are considered: The first scenario considers active power imbalances caused by load noise only (normal operation), while the second takes an additional significant generation outage into account (contingency). The results show that, in the load noise scenario, FCR activation with constant RoCoP reduces the frequency deviations slightly at the cost of higher total FCR provision and higher maximum FCR activation. However, in case of an additional generation outage, constant RoCoP activation results in a larger maximum frequency deviation, which means that the stability margin of the system is reduced.","PeriodicalId":378884,"journal":{"name":"2021 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"358 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125644076","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 : 2021-10-25DOI: 10.1109/SmartGridComm51999.2021.9632339
Jingtao Qin, N. Yu, Yuanqi Gao
Solving the unit commitment (UC) problem in a computationally efficient manner is a critical issue of electricity market operations. Optimization-based methods such as heuristics, dynamic programming, and mixed-integer quadratic programming (MIQP) often yield good solutions to the UC problem. However, the computation time of optimization-based methods grows exponentially with the number of generating units, which is a major bottleneck in practice. To address this issue, we formulate the UC problem as a Markov decision process and propose a novel multi-step deep reinforcement learning (RL)-based algorithm to solve the problem. We approximate the action-value function with neural networks and design an algorithm to determine the feasible action space. Numerical studies on a 5-generator test case show that our proposed algorithm significantly outperforms the deep Q-learning and yields similar level of performance as that of MIQP-based optimization in terms of optimality. The computation time of our proposed algorithm is much shorter than that of MIQP-based optimization methods.
{"title":"Solving Unit Commitment Problems with Multi-step Deep Reinforcement Learning","authors":"Jingtao Qin, N. Yu, Yuanqi Gao","doi":"10.1109/SmartGridComm51999.2021.9632339","DOIUrl":"https://doi.org/10.1109/SmartGridComm51999.2021.9632339","url":null,"abstract":"Solving the unit commitment (UC) problem in a computationally efficient manner is a critical issue of electricity market operations. Optimization-based methods such as heuristics, dynamic programming, and mixed-integer quadratic programming (MIQP) often yield good solutions to the UC problem. However, the computation time of optimization-based methods grows exponentially with the number of generating units, which is a major bottleneck in practice. To address this issue, we formulate the UC problem as a Markov decision process and propose a novel multi-step deep reinforcement learning (RL)-based algorithm to solve the problem. We approximate the action-value function with neural networks and design an algorithm to determine the feasible action space. Numerical studies on a 5-generator test case show that our proposed algorithm significantly outperforms the deep Q-learning and yields similar level of performance as that of MIQP-based optimization in terms of optimality. The computation time of our proposed algorithm is much shorter than that of MIQP-based optimization methods.","PeriodicalId":378884,"journal":{"name":"2021 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131081995","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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