Pub Date : 2020-08-01DOI: 10.1109/PMAPS47429.2020.9183548
D. Logan, M. Papic
There is a vast amount of literature dealing with composite system reliability. A survey was conducted by the IEEE Composite System Reliability Task Force to assess the state of industry practice in probabilistic assessment in general and composite system reliability (CSR) analysis in particular. Increasing interest has been seen in evaluating the reliability impact of the high penetration of renewables such as photovoltaics and wind, retirement of coal plants, regulatory requirements, and other policies on a composite system basis – that is, including both generation and transmission. These have all significantly increased the uncertainties in power systems and made the reliability assessment of composite power systems much more complicated. The survey questions addressed the types of analyses being done, the contexts and purposes of these analyses, the software tools in use, the importance of various features of the software tools, and whether the implementation of these features is adequate or lacking. The survey also sought to identify impediments that may be constraining more widespread implementation of probabilistic and CSR analysis.
{"title":"A Survey of Industry Practices in Probabilistic Assessment and Composite System Reliability Analysis","authors":"D. Logan, M. Papic","doi":"10.1109/PMAPS47429.2020.9183548","DOIUrl":"https://doi.org/10.1109/PMAPS47429.2020.9183548","url":null,"abstract":"There is a vast amount of literature dealing with composite system reliability. A survey was conducted by the IEEE Composite System Reliability Task Force to assess the state of industry practice in probabilistic assessment in general and composite system reliability (CSR) analysis in particular. Increasing interest has been seen in evaluating the reliability impact of the high penetration of renewables such as photovoltaics and wind, retirement of coal plants, regulatory requirements, and other policies on a composite system basis – that is, including both generation and transmission. These have all significantly increased the uncertainties in power systems and made the reliability assessment of composite power systems much more complicated. The survey questions addressed the types of analyses being done, the contexts and purposes of these analyses, the software tools in use, the importance of various features of the software tools, and whether the implementation of these features is adequate or lacking. The survey also sought to identify impediments that may be constraining more widespread implementation of probabilistic and CSR analysis.","PeriodicalId":126918,"journal":{"name":"2020 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132471708","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 : 2020-08-01DOI: 10.1109/PMAPS47429.2020.9183642
M. Goodridge, J. Moriarty, A. Pizzoferrato
Following disturbances to a power system triggering emergency responses such as protection or load/generation shedding, several factors affect the way in which these responses may cascade through the network. Beyond deterministic factors such as network topology, in this paper we aim to quantify the effect of correlations in power disturbances. These arise, for example, from common weather patterns causing correlated forecast errors in renewable generation. Our results suggest that for highly connected networks, the cascade size distribution is bimodal and positively correlated disturbances have the benefit of reducing cascade size. For a fixed network the latter relationship is observed to be stronger when emergency responses are rare, which is consistent with the mathematical theory of large deviations.
{"title":"Distributions of cascade sizes in power system emergency response","authors":"M. Goodridge, J. Moriarty, A. Pizzoferrato","doi":"10.1109/PMAPS47429.2020.9183642","DOIUrl":"https://doi.org/10.1109/PMAPS47429.2020.9183642","url":null,"abstract":"Following disturbances to a power system triggering emergency responses such as protection or load/generation shedding, several factors affect the way in which these responses may cascade through the network. Beyond deterministic factors such as network topology, in this paper we aim to quantify the effect of correlations in power disturbances. These arise, for example, from common weather patterns causing correlated forecast errors in renewable generation. Our results suggest that for highly connected networks, the cascade size distribution is bimodal and positively correlated disturbances have the benefit of reducing cascade size. For a fixed network the latter relationship is observed to be stronger when emergency responses are rare, which is consistent with the mathematical theory of large deviations.","PeriodicalId":126918,"journal":{"name":"2020 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134635619","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 : 2020-08-01DOI: 10.1109/PMAPS47429.2020.9183472
F. Treistman, M. Maceira, J. M. Damázio, C. Cruz
In countries that present a high share of hydropower, as is the case of Brazil, the operation planning is based on optimization models that require the generation of synthetic hydrological inflow scenarios by models capable of representing the associated natural periodic behavior. For example, in Brazil, the PAR(p) model is employed in the computational models officially used by the National Electrical System Operator for the long- and medium-term operation planning. Usually, the average of the synthetic monthly inflow scenarios generated by the PAR(p) model presents the usual prognostic of returning to the historical average roughly in some months even when the actual regime is presenting very dry or wet partner. This paper presents an extended memory approach for the PAR(p) model to overcome this drawback by including a new term in the periodic autoregressive regression given by the average of the 12 previous inflows. A case study of the monthly long-term operation program conducted by ONS with a real configuration of the Brazilian large scale interconnected hydrothermal system is presented and discussed.
{"title":"Periodic Time Series Model with Annual Component Applied to Operation Planning of Hydrothermal Systems","authors":"F. Treistman, M. Maceira, J. M. Damázio, C. Cruz","doi":"10.1109/PMAPS47429.2020.9183472","DOIUrl":"https://doi.org/10.1109/PMAPS47429.2020.9183472","url":null,"abstract":"In countries that present a high share of hydropower, as is the case of Brazil, the operation planning is based on optimization models that require the generation of synthetic hydrological inflow scenarios by models capable of representing the associated natural periodic behavior. For example, in Brazil, the PAR(p) model is employed in the computational models officially used by the National Electrical System Operator for the long- and medium-term operation planning. Usually, the average of the synthetic monthly inflow scenarios generated by the PAR(p) model presents the usual prognostic of returning to the historical average roughly in some months even when the actual regime is presenting very dry or wet partner. This paper presents an extended memory approach for the PAR(p) model to overcome this drawback by including a new term in the periodic autoregressive regression given by the average of the 12 previous inflows. A case study of the monthly long-term operation program conducted by ONS with a real configuration of the Brazilian large scale interconnected hydrothermal system is presented and discussed.","PeriodicalId":126918,"journal":{"name":"2020 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128093860","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 : 2020-08-01DOI: 10.1109/PMAPS47429.2020.9183506
B. Pierre, Bryan Arguello, Manuel J. Garcia
This paper presents a multi-time period two-stage stochastic mixed-integer linear optimization model which determines the optimal hardening investments to improve power system resilience to natural disaster threat scenarios. The input to the optimization model is a set of scenarios for specific natural disaster events, that is based on historical data. The objective of the optimization model is to minimize the expected weighted load shed from the initial impact and the restoration process over all scenarios. The optimization model considers the initial impact of the severe event by using electromechanical transient dynamic simulations. The initial impact weighted load shed is determined by the transient simulation, which allows for secondary transients from protection devices and cascading failures. The rest of the event, after the initial shock, is modeled in the optimization with a multi-time period dc optimal power flow (DCOPF) which is initialized with the solution from the dynamic simulation. The first stage of the optimization model determines the optimal investments. The second stage, given the investments, determines the optimal unit commitment, generator dispatch, and transmission line switching during the multi-time period restoration process to minimize the weighted load shed over all scenarios. Note, an investment will change the transient simulation result, and therefore change the initialization to the DCOPF restoration model. The investment optimization model encompasses both the initial impact (dynamic transient simulation results) and the restoration period (DCOPF) of the event, as components come back online. The model is tested on the IEEE RTS-96 system.
{"title":"Optimal Investments to Improve Grid Resilience Considering Initial Transient Response and Long-term Restoration","authors":"B. Pierre, Bryan Arguello, Manuel J. Garcia","doi":"10.1109/PMAPS47429.2020.9183506","DOIUrl":"https://doi.org/10.1109/PMAPS47429.2020.9183506","url":null,"abstract":"This paper presents a multi-time period two-stage stochastic mixed-integer linear optimization model which determines the optimal hardening investments to improve power system resilience to natural disaster threat scenarios. The input to the optimization model is a set of scenarios for specific natural disaster events, that is based on historical data. The objective of the optimization model is to minimize the expected weighted load shed from the initial impact and the restoration process over all scenarios. The optimization model considers the initial impact of the severe event by using electromechanical transient dynamic simulations. The initial impact weighted load shed is determined by the transient simulation, which allows for secondary transients from protection devices and cascading failures. The rest of the event, after the initial shock, is modeled in the optimization with a multi-time period dc optimal power flow (DCOPF) which is initialized with the solution from the dynamic simulation. The first stage of the optimization model determines the optimal investments. The second stage, given the investments, determines the optimal unit commitment, generator dispatch, and transmission line switching during the multi-time period restoration process to minimize the weighted load shed over all scenarios. Note, an investment will change the transient simulation result, and therefore change the initialization to the DCOPF restoration model. The investment optimization model encompasses both the initial impact (dynamic transient simulation results) and the restoration period (DCOPF) of the event, as components come back online. The model is tested on the IEEE RTS-96 system.","PeriodicalId":126918,"journal":{"name":"2020 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129400132","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 : 2020-08-01DOI: 10.1109/PMAPS47429.2020.9183389
Sebastian Gonzato, K. Bruninx, E. Delarue
Energy system optimisation (ESOM) and generation expansion planning (GEP) models are often used to study energy transition pathways. These typically entail an increased penetration of variable renewable energy sources (VRES), which can lead to increased operating reserve requirements due to their associated forecast uncertainty. Representing this effect has previously been tackled using either stochastic programming techniques or deterministic GEPs which use heuristics to size reserves while ignoring their activation cost. In this paper, we propose a novel GEP formulation which determines operating reserve requirements using a second order cone (SOC) constraint. This formulation approximates the solution of a stochastic GEP by accounting for reserve activation costs without resorting to scenario based methods. A case study on the Belgian system indicates possible cost savings of 70 MAC(0.9%) and less bias towards installing peaking technologies to satisfy reserve requirements compared to a deterministic GEP. The sensitivity of the results to the assumption of normality of forecast errors and temporal detail is also investigated. Two final case studies on the value of emergency measures and improving forecast uncertainties illustrate the benefits of accounting for reserve activation costs and appropriate reserve sizing.
{"title":"An improved treatment of operating reserves in generation expansion planning models","authors":"Sebastian Gonzato, K. Bruninx, E. Delarue","doi":"10.1109/PMAPS47429.2020.9183389","DOIUrl":"https://doi.org/10.1109/PMAPS47429.2020.9183389","url":null,"abstract":"Energy system optimisation (ESOM) and generation expansion planning (GEP) models are often used to study energy transition pathways. These typically entail an increased penetration of variable renewable energy sources (VRES), which can lead to increased operating reserve requirements due to their associated forecast uncertainty. Representing this effect has previously been tackled using either stochastic programming techniques or deterministic GEPs which use heuristics to size reserves while ignoring their activation cost. In this paper, we propose a novel GEP formulation which determines operating reserve requirements using a second order cone (SOC) constraint. This formulation approximates the solution of a stochastic GEP by accounting for reserve activation costs without resorting to scenario based methods. A case study on the Belgian system indicates possible cost savings of 70 MAC(0.9%) and less bias towards installing peaking technologies to satisfy reserve requirements compared to a deterministic GEP. The sensitivity of the results to the assumption of normality of forecast errors and temporal detail is also investigated. Two final case studies on the value of emergency measures and improving forecast uncertainties illustrate the benefits of accounting for reserve activation costs and appropriate reserve sizing.","PeriodicalId":126918,"journal":{"name":"2020 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130531032","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 : 2020-08-01DOI: 10.1109/PMAPS47429.2020.9183585
M. Ortega-Vazquez, N. Costilla-Enríquez, E. Ela, A. Tuohy
Operating reserves are needed to accommodate the vagaries generated by stochastic resources such as the ever-increasing shares of variable renewable energy (VRE). Increasing the amounts of reserve to accommodate the increased stochasticity needs to be carefully justified since this resource comes at a cost. Therefore, reserve procurement needs to be determined considering both, the benefits in terms of reliability improvements and the increased operating costs to the system. Traditionally the procurement of this service has relied on deterministic rules-of-thumb, while academic research has demonstrated the advantages of modeling the variability and uncertainty endogenously in the decision-making process through advanced scheduling methods. Those approaches do not explicitly model the risk (or its components) in the decision-making process. This work proposes practical methods to determine the reserve requirements to maintain risk (or risk component) below a desired threshold during system operation. Numerical results on the RTS-GMLC system demonstrate the effectiveness of the proposed methods.
{"title":"Risk-Based Reserve Procurement","authors":"M. Ortega-Vazquez, N. Costilla-Enríquez, E. Ela, A. Tuohy","doi":"10.1109/PMAPS47429.2020.9183585","DOIUrl":"https://doi.org/10.1109/PMAPS47429.2020.9183585","url":null,"abstract":"Operating reserves are needed to accommodate the vagaries generated by stochastic resources such as the ever-increasing shares of variable renewable energy (VRE). Increasing the amounts of reserve to accommodate the increased stochasticity needs to be carefully justified since this resource comes at a cost. Therefore, reserve procurement needs to be determined considering both, the benefits in terms of reliability improvements and the increased operating costs to the system. Traditionally the procurement of this service has relied on deterministic rules-of-thumb, while academic research has demonstrated the advantages of modeling the variability and uncertainty endogenously in the decision-making process through advanced scheduling methods. Those approaches do not explicitly model the risk (or its components) in the decision-making process. This work proposes practical methods to determine the reserve requirements to maintain risk (or risk component) below a desired threshold during system operation. Numerical results on the RTS-GMLC system demonstrate the effectiveness of the proposed methods.","PeriodicalId":126918,"journal":{"name":"2020 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125705000","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 : 2020-08-01DOI: 10.1109/PMAPS47429.2020.9183566
Wilson A. Vasquez, D. Jayaweera
Identifying the most important components for system reliability helps asset managers to optimize maintenance and replacement plans. In that context, this paper proposes a novel methodology to rank underground power distribution cables considering their age-related repairable failures and their loading conditions. A non-homogeneous Poisson process is used to model age-related repairable failures of cables and to incorporate the loading conditions into the prioritization process. Cables are ranked by using a component-level index that quantifies the impact of their failures (random and age-related) on the system interruption cost. A power distribution system with 64 underground power cable sections was used to assess the methodology. Results suggest that the importance of underground power cables can change when their age-related repairable failures and their loading levels are incorporated into the ranking lists.
{"title":"Prioritization of Aging Underground Power Distribution Cables for Maintenance Activities","authors":"Wilson A. Vasquez, D. Jayaweera","doi":"10.1109/PMAPS47429.2020.9183566","DOIUrl":"https://doi.org/10.1109/PMAPS47429.2020.9183566","url":null,"abstract":"Identifying the most important components for system reliability helps asset managers to optimize maintenance and replacement plans. In that context, this paper proposes a novel methodology to rank underground power distribution cables considering their age-related repairable failures and their loading conditions. A non-homogeneous Poisson process is used to model age-related repairable failures of cables and to incorporate the loading conditions into the prioritization process. Cables are ranked by using a component-level index that quantifies the impact of their failures (random and age-related) on the system interruption cost. A power distribution system with 64 underground power cable sections was used to assess the methodology. Results suggest that the importance of underground power cables can change when their age-related repairable failures and their loading levels are incorporated into the ranking lists.","PeriodicalId":126918,"journal":{"name":"2020 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129061562","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 : 2020-08-01DOI: 10.1109/PMAPS47429.2020.9183646
Jonathan Dumas, B. Cornélusse, Antonello Giannitrapani, S. Paoletti, A. Vicino
This paper addresses the energy management of a grid-connected photovoltaic plant coupled with a battery energy storage device, within the capacity firming specifications of the French Energy Regulatory Commission. The paper contributions are positioned in the continuity of the studies adopting stochastic models for optimizing the bids of renewable energy sources in a day-ahead market by considering a storage device. The proposed deterministic and stochastic approaches are optimization problems formulated as quadratic problems with linear constraints. The case study is a real microgrid with PV production monitored on site. The results demonstrate the validity of the stochastic formulation by using an ideal predictor that produces unbiased PV scenarios.
{"title":"Stochastic and deterministic formulations for capacity firming nominations","authors":"Jonathan Dumas, B. Cornélusse, Antonello Giannitrapani, S. Paoletti, A. Vicino","doi":"10.1109/PMAPS47429.2020.9183646","DOIUrl":"https://doi.org/10.1109/PMAPS47429.2020.9183646","url":null,"abstract":"This paper addresses the energy management of a grid-connected photovoltaic plant coupled with a battery energy storage device, within the capacity firming specifications of the French Energy Regulatory Commission. The paper contributions are positioned in the continuity of the studies adopting stochastic models for optimizing the bids of renewable energy sources in a day-ahead market by considering a storage device. The proposed deterministic and stochastic approaches are optimization problems formulated as quadratic problems with linear constraints. The case study is a real microgrid with PV production monitored on site. The results demonstrate the validity of the stochastic formulation by using an ideal predictor that produces unbiased PV scenarios.","PeriodicalId":126918,"journal":{"name":"2020 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130882422","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 : 2020-08-01DOI: 10.1109/PMAPS47429.2020.9183711
I. B. Sperstad, E. Solvang, O. Gjerde
The long-term planning frameworks currently used by electricity distribution grid companies are not designed to account for new challenges such as variable distributed generation or for new opportunities of active grid measures. Various advanced optimization methods for active grid measures are presented in the research literature, but they are rarely used in practice and are not always well suited to informing decision processes in distribution grid planning. To bridge this gap, this paper presents a framework for active distribution grid planning that takes as a starting point the traditional planning framework commonly used by Norwegian grid companies. The framework with selected, probabilistic methodologies is demonstrated through a case study considering voltage problems due to distributed photovoltaic (PV) generation, and battery energy storage systems and PV curtailment as active measures to defer grid reinforcement. The paper moreover discusses how probabilistic approaches can contribute to better informed distribution grid planning decisions.
{"title":"Framework and methodology for active distribution grid planning in Norway","authors":"I. B. Sperstad, E. Solvang, O. Gjerde","doi":"10.1109/PMAPS47429.2020.9183711","DOIUrl":"https://doi.org/10.1109/PMAPS47429.2020.9183711","url":null,"abstract":"The long-term planning frameworks currently used by electricity distribution grid companies are not designed to account for new challenges such as variable distributed generation or for new opportunities of active grid measures. Various advanced optimization methods for active grid measures are presented in the research literature, but they are rarely used in practice and are not always well suited to informing decision processes in distribution grid planning. To bridge this gap, this paper presents a framework for active distribution grid planning that takes as a starting point the traditional planning framework commonly used by Norwegian grid companies. The framework with selected, probabilistic methodologies is demonstrated through a case study considering voltage problems due to distributed photovoltaic (PV) generation, and battery energy storage systems and PV curtailment as active measures to defer grid reinforcement. The paper moreover discusses how probabilistic approaches can contribute to better informed distribution grid planning decisions.","PeriodicalId":126918,"journal":{"name":"2020 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114210058","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 : 2020-08-01DOI: 10.1109/PMAPS47429.2020.9183639
K. Kamps, F. Möhrke, K. Schäfer, M. Zdrallek, A. Wasserrab, R. Schwerdfeger, M. Thiele
According to the N-1 criterion, system security in the event of a failure of a network element (N-1 situation) must still be guaranteed. In transmission systems, this is traditionally realized with different preventive (i. e. pre-fault) actions, e. g. the provision of unexploited transmission capacities and redispatch of power plants. In contrast to this, the curative approach ensures a N-1 security reactively (i. e. post-fault). This approach is based on comprehensive information and communication technologies which allow a highly automated process for identifying critical system states and the determination of subsequent corrective actions, e. g. load shedding or generator rejection. These actions are commonly designated as Special Protection Schemes (SPS). However, with increasing applications of SPS, the reliability of SPS needs to be determined and the impact of SPS on the security of supply needs to be assessed. In this contribution analytical methods are applied to determine the probability of different states (in service, limited operation and outage) for five different SPS. Furthermore, the probability and maximum level of overloads, quantifying risk in situations where curative and preventive actions fail, are compared in certain network areas in the transmission system. Results show that a highly redundant design of SPS (especially communication networks, battery storages) is crucial to reach a similar level of reliability compared to conventional network elements. The risk analysis emphasizes that the probability and level of overloads can be reduced or is on a similar level compared to preventive actions.
{"title":"Modelling and Risk Assessment of Special Protection Schemes in Transmission Systems","authors":"K. Kamps, F. Möhrke, K. Schäfer, M. Zdrallek, A. Wasserrab, R. Schwerdfeger, M. Thiele","doi":"10.1109/PMAPS47429.2020.9183639","DOIUrl":"https://doi.org/10.1109/PMAPS47429.2020.9183639","url":null,"abstract":"According to the N-1 criterion, system security in the event of a failure of a network element (N-1 situation) must still be guaranteed. In transmission systems, this is traditionally realized with different preventive (i. e. pre-fault) actions, e. g. the provision of unexploited transmission capacities and redispatch of power plants. In contrast to this, the curative approach ensures a N-1 security reactively (i. e. post-fault). This approach is based on comprehensive information and communication technologies which allow a highly automated process for identifying critical system states and the determination of subsequent corrective actions, e. g. load shedding or generator rejection. These actions are commonly designated as Special Protection Schemes (SPS). However, with increasing applications of SPS, the reliability of SPS needs to be determined and the impact of SPS on the security of supply needs to be assessed. In this contribution analytical methods are applied to determine the probability of different states (in service, limited operation and outage) for five different SPS. Furthermore, the probability and maximum level of overloads, quantifying risk in situations where curative and preventive actions fail, are compared in certain network areas in the transmission system. Results show that a highly redundant design of SPS (especially communication networks, battery storages) is crucial to reach a similar level of reliability compared to conventional network elements. The risk analysis emphasizes that the probability and level of overloads can be reduced or is on a similar level compared to preventive actions.","PeriodicalId":126918,"journal":{"name":"2020 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117026069","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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