Combined heat and power (CHP) units can be operated flexibly to mitigate the impact of renewable resources. However, when used in district heating systems, the constraint governing heat and electricity outputs limits the capability of CHP in supporting the power grid. To addresses this issue, this paper presents a two-layer control system to coordinate CHP, district heating network and buildings. With this control system, CHP can meet the heat demand of local users and provide frequency response for the power grid simultaneously. The excess/deficit heat of CHP supply is balanced by heat stored in buildings and pipelines. The proposed method is tested in the GB Firm Frequency Response market. Numerical results show that the capability of CHP in providing frequency response is determined by the following factors: capacity and ramping rate of CHP, the restriction in the supply temperature of district heating network and the temperature of buildings.
{"title":"Unlocking the Flexibility of CHP in District Heating Systems to Provide Frequency Response","authors":"Xiandong Xu, Yue Zhou, Meysam Qadrdan, Jianzhong Wu","doi":"10.1109/PTC.2019.8810576","DOIUrl":"https://doi.org/10.1109/PTC.2019.8810576","url":null,"abstract":"Combined heat and power (CHP) units can be operated flexibly to mitigate the impact of renewable resources. However, when used in district heating systems, the constraint governing heat and electricity outputs limits the capability of CHP in supporting the power grid. To addresses this issue, this paper presents a two-layer control system to coordinate CHP, district heating network and buildings. With this control system, CHP can meet the heat demand of local users and provide frequency response for the power grid simultaneously. The excess/deficit heat of CHP supply is balanced by heat stored in buildings and pipelines. The proposed method is tested in the GB Firm Frequency Response market. Numerical results show that the capability of CHP in providing frequency response is determined by the following factors: capacity and ramping rate of CHP, the restriction in the supply temperature of district heating network and the temperature of buildings.","PeriodicalId":187144,"journal":{"name":"2019 IEEE Milan PowerTech","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122187630","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 : 2019-06-23DOI: 10.1109/PTC.2019.8810613
Ahmed Hadjsaid, V. Debusschere, M. Alvarez‐Herault, R. Caire
This work studies the impact of local PV production on the main indicators of planning studies in the context of low voltage grids. The two criteria that are assessed are the maximal power transmitted and its equivalent yearly duration. An analytical expression is put in place, considering the impact on the aggregation of the load consumption and the production at the point of coupling of a distribution grid. Steps are identified depending on the penetration rate of the PV production system in the grid and the sign of the peak power flowing through the MV/LV substation. Simulations validate the mathematical models as well as illustrate the identified three steps as a function of theoretically expressed PV penetration rates. It is shown that better considering PV penetration rate is useful for distribution system operators, as it underline the reduction of the peak power in the grid and consequently allow a lower line cross section.
{"title":"Considering local photovoltaic production in planning studies for low voltage distribution grids","authors":"Ahmed Hadjsaid, V. Debusschere, M. Alvarez‐Herault, R. Caire","doi":"10.1109/PTC.2019.8810613","DOIUrl":"https://doi.org/10.1109/PTC.2019.8810613","url":null,"abstract":"This work studies the impact of local PV production on the main indicators of planning studies in the context of low voltage grids. The two criteria that are assessed are the maximal power transmitted and its equivalent yearly duration. An analytical expression is put in place, considering the impact on the aggregation of the load consumption and the production at the point of coupling of a distribution grid. Steps are identified depending on the penetration rate of the PV production system in the grid and the sign of the peak power flowing through the MV/LV substation. Simulations validate the mathematical models as well as illustrate the identified three steps as a function of theoretically expressed PV penetration rates. It is shown that better considering PV penetration rate is useful for distribution system operators, as it underline the reduction of the peak power in the grid and consequently allow a lower line cross section.","PeriodicalId":187144,"journal":{"name":"2019 IEEE Milan PowerTech","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127510077","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 : 2019-06-23DOI: 10.1109/PTC.2019.8810585
R. Ciavarella, M. di Somma, G. Graditi, M. Valenti
With the increasing penetration levels of distributed energy resources (DER), grid congestion events may occur by causing severe damages and potential black outs in power systems. Developing innovative operation planning strategies and control tools for the grid congestion management is thus a primary goal for ensuring network reliability and security. In this paper, we propose a Grid Congestion Management Controller (GCMC) to solve grid congestion issues by controlling the active power of flexible DER (e.g. storage, flexible loads, electric vehicles, distributed generators) present in the grid, thus increasing availability of active resources to maintain the network stability. The GCMC is developed here as a self-contained control acting on distribution level, and will be further developed to be integrated in the INTEgrated opeRation PLANning tool, which will be the main outcome of the INTERPLAN H2020 project. INTERPLAN (Nov.2016Nov.2020) aims to provide an integrated tool to support transmission system operators and distribution system operators in the operation planning of the pan-European network. The GCMC effectiveness is tested in the presence of specific congestion events by using the Cigrè benchmark grid model under different scenarios. Simulation results show that the proposed control logic is efficient in mitigating grid congestion through optimally re-dispatching active power variation to the flexible DER connected to each busbar in the network.
{"title":"Congestion Management in distribution grid networks through active power control of flexible distributed energy resources","authors":"R. Ciavarella, M. di Somma, G. Graditi, M. Valenti","doi":"10.1109/PTC.2019.8810585","DOIUrl":"https://doi.org/10.1109/PTC.2019.8810585","url":null,"abstract":"With the increasing penetration levels of distributed energy resources (DER), grid congestion events may occur by causing severe damages and potential black outs in power systems. Developing innovative operation planning strategies and control tools for the grid congestion management is thus a primary goal for ensuring network reliability and security. In this paper, we propose a Grid Congestion Management Controller (GCMC) to solve grid congestion issues by controlling the active power of flexible DER (e.g. storage, flexible loads, electric vehicles, distributed generators) present in the grid, thus increasing availability of active resources to maintain the network stability. The GCMC is developed here as a self-contained control acting on distribution level, and will be further developed to be integrated in the INTEgrated opeRation PLANning tool, which will be the main outcome of the INTERPLAN H2020 project. INTERPLAN (Nov.2016Nov.2020) aims to provide an integrated tool to support transmission system operators and distribution system operators in the operation planning of the pan-European network. The GCMC effectiveness is tested in the presence of specific congestion events by using the Cigrè benchmark grid model under different scenarios. Simulation results show that the proposed control logic is efficient in mitigating grid congestion through optimally re-dispatching active power variation to the flexible DER connected to each busbar in the network.","PeriodicalId":187144,"journal":{"name":"2019 IEEE Milan PowerTech","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126959894","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 : 2019-06-23DOI: 10.1109/PTC.2019.8810772
E. O. Kontis, Angelos I. Nousdilis, G. Papagiannis, M. Syed, E. Guillo‐Sansano, G. Burt, T. Papadopoulos
During the last decades, a significant number of mode identification techniques and dynamic equivalent models have been proposed in the literature to analyze the dynamic properties of transmission grids and active distribution networks (ADNs). The majority of these methods are developed using the measurement-based approach, i.e., by exploiting dynamic responses acquired from phasor measurement units (PMUs). However, there is lack of a common framework in the literature for the performance evaluation of such methods under real field conditions. Aiming to address this gap, in this paper, a power hardware-in-the-loop setup is introduced to generate dynamic responses, suitable for the testing and validation of measurementbased mode identification techniques and dynamic equivalent models. The setup consists of a high voltage transmission grid, two medium voltage distribution grids as well as a low voltage ADN. Using this setup, several disturbances are emulated and the resulting dynamic responses are recorded using PMUs. The measurements are made available to other researchers through a public repository to act as benchmark responses for the evaluation of measurement-based methods.
{"title":"Power Hardware-in-the-Loop Setup for Developing, Analyzing and Testing Mode Identification Techniques and Dynamic Equivalent Models","authors":"E. O. Kontis, Angelos I. Nousdilis, G. Papagiannis, M. Syed, E. Guillo‐Sansano, G. Burt, T. Papadopoulos","doi":"10.1109/PTC.2019.8810772","DOIUrl":"https://doi.org/10.1109/PTC.2019.8810772","url":null,"abstract":"During the last decades, a significant number of mode identification techniques and dynamic equivalent models have been proposed in the literature to analyze the dynamic properties of transmission grids and active distribution networks (ADNs). The majority of these methods are developed using the measurement-based approach, i.e., by exploiting dynamic responses acquired from phasor measurement units (PMUs). However, there is lack of a common framework in the literature for the performance evaluation of such methods under real field conditions. Aiming to address this gap, in this paper, a power hardware-in-the-loop setup is introduced to generate dynamic responses, suitable for the testing and validation of measurementbased mode identification techniques and dynamic equivalent models. The setup consists of a high voltage transmission grid, two medium voltage distribution grids as well as a low voltage ADN. Using this setup, several disturbances are emulated and the resulting dynamic responses are recorded using PMUs. The measurements are made available to other researchers through a public repository to act as benchmark responses for the evaluation of measurement-based methods.","PeriodicalId":187144,"journal":{"name":"2019 IEEE Milan PowerTech","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126246245","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 : 2019-06-23DOI: 10.1109/PTC.2019.8810440
Mostafa Nazemi, P. Dehghanian, M. Lejeune
This paper proposes a distributionally robust chance-constrained (DRCC) optimization model for optimal topology control in power grids overwhelmed with significant renewable uncertainties. A novel moment-based ambiguity set is characterized to capture the renewable uncertainties with no knowledge on the probability distributions of the random parameters. A distributionally robust optimization (DRO) formulation is proposed to guarantee the robustness of the network topology control plans against all uncertainty distributions defined within the moment-based ambiguity set. The proposed model minimizes the system operation cost by co-optimizing dispatch of the lower-cost generating units and network topology—i.e., dynamically harnessing the way how electricity flows through the system. In order to solve the problem, the DRCC problem are reformulated into a tractable mixed-integer second order cone programming problem (MISOCP) which can be efficiently solved by off-the-shelf solvers. Numerical results on the IEEE 118-bus test system verify the effectiveness of the proposed network reconfiguration methodology under uncertainties.
{"title":"A Mixed-Integer Distributionally Robust Chance-Constrained Model for Optimal Topology Control in Power Grids with Uncertain Renewables","authors":"Mostafa Nazemi, P. Dehghanian, M. Lejeune","doi":"10.1109/PTC.2019.8810440","DOIUrl":"https://doi.org/10.1109/PTC.2019.8810440","url":null,"abstract":"This paper proposes a distributionally robust chance-constrained (DRCC) optimization model for optimal topology control in power grids overwhelmed with significant renewable uncertainties. A novel moment-based ambiguity set is characterized to capture the renewable uncertainties with no knowledge on the probability distributions of the random parameters. A distributionally robust optimization (DRO) formulation is proposed to guarantee the robustness of the network topology control plans against all uncertainty distributions defined within the moment-based ambiguity set. The proposed model minimizes the system operation cost by co-optimizing dispatch of the lower-cost generating units and network topology—i.e., dynamically harnessing the way how electricity flows through the system. In order to solve the problem, the DRCC problem are reformulated into a tractable mixed-integer second order cone programming problem (MISOCP) which can be efficiently solved by off-the-shelf solvers. Numerical results on the IEEE 118-bus test system verify the effectiveness of the proposed network reconfiguration methodology under uncertainties.","PeriodicalId":187144,"journal":{"name":"2019 IEEE Milan PowerTech","volume":"171 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133039248","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 : 2019-06-23DOI: 10.1109/PTC.2019.8810922
S. Chakraborty, M. Cvetković, R. Verzijlbergh, Z. Lukszo, K. Baker
The large-scale integration of renewables to the electrical grid is resulting in the increase of price volatility in electricity markets. This increase is undesirable from both electricity producer and consumer perspectives. In this paper, we present a framework that allows consumers to hedge against the price volatility. Using optimization duality theory, we quantify the amount of demand-side flexibility that an Energy Storage System (ESS) is required to provide for constraining marginal prices to a consumer’s maximum willingness to pay for electricity. The ESS is operated using Model Predictive Control (MPC) and depends on renewable generation forecasts. Forecast uncertainties are accounted through probabilistic constraints that are applied on the ESS operation. Probabilistic constraints enable the Energy Storage Operator to set a priori robustness guarantees on the solution which are cheaper than robust approaches. Through simulations it is demonstrated that the formulation is able to successfully hedge against price volatility considering uncertainty.
{"title":"Consumer Hedging Against Price Volatility Under Uncertainty","authors":"S. Chakraborty, M. Cvetković, R. Verzijlbergh, Z. Lukszo, K. Baker","doi":"10.1109/PTC.2019.8810922","DOIUrl":"https://doi.org/10.1109/PTC.2019.8810922","url":null,"abstract":"The large-scale integration of renewables to the electrical grid is resulting in the increase of price volatility in electricity markets. This increase is undesirable from both electricity producer and consumer perspectives. In this paper, we present a framework that allows consumers to hedge against the price volatility. Using optimization duality theory, we quantify the amount of demand-side flexibility that an Energy Storage System (ESS) is required to provide for constraining marginal prices to a consumer’s maximum willingness to pay for electricity. The ESS is operated using Model Predictive Control (MPC) and depends on renewable generation forecasts. Forecast uncertainties are accounted through probabilistic constraints that are applied on the ESS operation. Probabilistic constraints enable the Energy Storage Operator to set a priori robustness guarantees on the solution which are cheaper than robust approaches. Through simulations it is demonstrated that the formulation is able to successfully hedge against price volatility considering uncertainty.","PeriodicalId":187144,"journal":{"name":"2019 IEEE Milan PowerTech","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116014715","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 : 2019-06-23DOI: 10.1109/PTC.2019.8810755
İbrahim Şengör, Alper Çiçek, Ayşe Kübra Erenoğlu, O. Erdinç, A. Taşcıkaraoǧlu, C. João P. S.
The number of electric vehicles (EVs) has been gradually increasing over the last decades. In order to eliminate the concerns related to charging demand in power systems, the appropriate integration of EVs to the grid is of great importance. Electric vehicle parking lots (EVPLs) offer a crucial occasion to manage the charging process of EVs. Further, EVs are capable of either charging from the grid or supplying power to the grid due to the vehicle-to-grid (V2G) features. Through an agent, namely an aggregator, EVPLs can participate in the electricity market and a considerable amount of profit can be obtained in terms of EVPLs, EV owners, and aggregators by energy selling. However, EV owners may not be willing to participate in this structure due to the concerns related to their comforts. In this context, a model in which EVPLs can bid for energy selling to the grid through an aggregator is proposed in this study. Additionally, the comfort violation of EV owners is taken into account. In order to validate the effectiveness of the devised model, various case studies are also performed.
{"title":"User-Comfort Oriented Bidding Strategy for Electric Vehicle Parking Lots","authors":"İbrahim Şengör, Alper Çiçek, Ayşe Kübra Erenoğlu, O. Erdinç, A. Taşcıkaraoǧlu, C. João P. S.","doi":"10.1109/PTC.2019.8810755","DOIUrl":"https://doi.org/10.1109/PTC.2019.8810755","url":null,"abstract":"The number of electric vehicles (EVs) has been gradually increasing over the last decades. In order to eliminate the concerns related to charging demand in power systems, the appropriate integration of EVs to the grid is of great importance. Electric vehicle parking lots (EVPLs) offer a crucial occasion to manage the charging process of EVs. Further, EVs are capable of either charging from the grid or supplying power to the grid due to the vehicle-to-grid (V2G) features. Through an agent, namely an aggregator, EVPLs can participate in the electricity market and a considerable amount of profit can be obtained in terms of EVPLs, EV owners, and aggregators by energy selling. However, EV owners may not be willing to participate in this structure due to the concerns related to their comforts. In this context, a model in which EVPLs can bid for energy selling to the grid through an aggregator is proposed in this study. Additionally, the comfort violation of EV owners is taken into account. In order to validate the effectiveness of the devised model, various case studies are also performed.","PeriodicalId":187144,"journal":{"name":"2019 IEEE Milan PowerTech","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114870881","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 : 2019-06-23DOI: 10.1109/PTC.2019.8810989
Taulant Kërçi, F. Milano
This paper provides a sensitivity analysis of the interaction between the dynamic response of power systems and the unit commitment problem. A sub-hourly, mixed-integer linear programming Security Constrained Unit Commitment (SCUC) with a 24-hour rolling horizon is considered to cope with the uncertainty introduced by the large-scale penetration of nonsynchronous, stochastic renewable energy sources (RES). The SCUC is then integrated into Time Domain Simulations (TDS) and a sensitivity analysis with respect to different frequency controllers/machine parameters and different scheduling time intervals is carried out. Simulation results based on the 39-bus system show that shorter scheduling periods of the SCUC leads to lower operating cost and lower frequency variations.
{"title":"Sensitivity Analysis of the Interaction between Power System Dynamics and Unit Commitment","authors":"Taulant Kërçi, F. Milano","doi":"10.1109/PTC.2019.8810989","DOIUrl":"https://doi.org/10.1109/PTC.2019.8810989","url":null,"abstract":"This paper provides a sensitivity analysis of the interaction between the dynamic response of power systems and the unit commitment problem. A sub-hourly, mixed-integer linear programming Security Constrained Unit Commitment (SCUC) with a 24-hour rolling horizon is considered to cope with the uncertainty introduced by the large-scale penetration of nonsynchronous, stochastic renewable energy sources (RES). The SCUC is then integrated into Time Domain Simulations (TDS) and a sensitivity analysis with respect to different frequency controllers/machine parameters and different scheduling time intervals is carried out. Simulation results based on the 39-bus system show that shorter scheduling periods of the SCUC leads to lower operating cost and lower frequency variations.","PeriodicalId":187144,"journal":{"name":"2019 IEEE Milan PowerTech","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130359157","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 : 2019-06-23DOI: 10.1109/PTC.2019.8810617
E. Sauma, Catalina Rosende
In this paper, we study investment decisions regarding power generation and transmission when considering wind speed distortions due to Climate Change. We use a Mixed-Integer Linear Program (MILP) model to analyze the optimal investments in diverse types of power generation technologies, throughout the years and geographical locations. We implement our model using the main Chilean power system. We compare two scenarios: one assuming that climate change affects wind speeds and hence wind farm capacity factors and the other assuming it does not. Our results reveal that, when taking into account the impact of climate change on wind speed, the optimal power generation and transmission expansion plan is significantly different than when ignoring this effect. The variation of wind speed affects not only wind power investments, but also other-technology generation investments.
{"title":"Impact of Wind Speed Distortions on Chilean Power System Expansion Planning","authors":"E. Sauma, Catalina Rosende","doi":"10.1109/PTC.2019.8810617","DOIUrl":"https://doi.org/10.1109/PTC.2019.8810617","url":null,"abstract":"In this paper, we study investment decisions regarding power generation and transmission when considering wind speed distortions due to Climate Change. We use a Mixed-Integer Linear Program (MILP) model to analyze the optimal investments in diverse types of power generation technologies, throughout the years and geographical locations. We implement our model using the main Chilean power system. We compare two scenarios: one assuming that climate change affects wind speeds and hence wind farm capacity factors and the other assuming it does not. Our results reveal that, when taking into account the impact of climate change on wind speed, the optimal power generation and transmission expansion plan is significantly different than when ignoring this effect. The variation of wind speed affects not only wind power investments, but also other-technology generation investments.","PeriodicalId":187144,"journal":{"name":"2019 IEEE Milan PowerTech","volume":"1994 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131034367","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 : 2019-06-23DOI: 10.1109/PTC.2019.8810568
Xiaorui Liu, Charalambos Konstantinou
The protection of power systems is of paramount significance for the supply of electricity. Contingency analysis allows to access the impact of power grid components failures. Typically, power systems are designed to handle $N-2$ contingencies. Existing algorithms mainly focus on performance and computational efficiency. There has been little effort in designing contingency methods from a cybersecurity perspective. To address this limitation, we study contingency analysis in the context of power system planning and operation towards cyber-physical security assessment. The proposed methodology considers attackers transitions in the network based on the $N-2$ critical contingency pairs. We develop an online reinforcement $Q -$learning scheme to solve a Markov decision process that models adversarial actions. In this model, the adversary aims to maximize the cumulative reward before making any action and learns adaptively how to optimize the attack strategies. We validate and test the algorithm on eleven literature-based and synthetic power grid test cases.
{"title":"Reinforcement Learning for Cyber-Physical Security Assessment of Power Systems","authors":"Xiaorui Liu, Charalambos Konstantinou","doi":"10.1109/PTC.2019.8810568","DOIUrl":"https://doi.org/10.1109/PTC.2019.8810568","url":null,"abstract":"The protection of power systems is of paramount significance for the supply of electricity. Contingency analysis allows to access the impact of power grid components failures. Typically, power systems are designed to handle $N-2$ contingencies. Existing algorithms mainly focus on performance and computational efficiency. There has been little effort in designing contingency methods from a cybersecurity perspective. To address this limitation, we study contingency analysis in the context of power system planning and operation towards cyber-physical security assessment. The proposed methodology considers attackers transitions in the network based on the $N-2$ critical contingency pairs. We develop an online reinforcement $Q -$learning scheme to solve a Markov decision process that models adversarial actions. In this model, the adversary aims to maximize the cumulative reward before making any action and learns adaptively how to optimize the attack strategies. We validate and test the algorithm on eleven literature-based and synthetic power grid test cases.","PeriodicalId":187144,"journal":{"name":"2019 IEEE Milan PowerTech","volume":"83 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130997495","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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