Pub Date : 2016-10-01DOI: 10.1109/PMAPS.2016.7763925
A. Konara, U. Annakkage, B. Bagen
This paper presents a probabilistic approach to evaluate the reliability of a synchrophasor-based multi-input damping controller. Considering the probabilities of losing input signals to the controller, expected damping for the critical electromechanical oscillatory modes are determined. A two input power system stabilizer that uses a local and a remote signal is considered as a test system to evaluate the expected damping. Different probabilities of failures are considered for different controller inputs and the resultant expected damping values are compared. The importance of using a probabilistic index in the design stage of a controller is highlighted.
{"title":"The probabilistic approach to determine the reliability of synchrophasor-based damping controllers","authors":"A. Konara, U. Annakkage, B. Bagen","doi":"10.1109/PMAPS.2016.7763925","DOIUrl":"https://doi.org/10.1109/PMAPS.2016.7763925","url":null,"abstract":"This paper presents a probabilistic approach to evaluate the reliability of a synchrophasor-based multi-input damping controller. Considering the probabilities of losing input signals to the controller, expected damping for the critical electromechanical oscillatory modes are determined. A two input power system stabilizer that uses a local and a remote signal is considered as a test system to evaluate the expected damping. Different probabilities of failures are considered for different controller inputs and the resultant expected damping values are compared. The importance of using a probabilistic index in the design stage of a controller is highlighted.","PeriodicalId":265474,"journal":{"name":"2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128113412","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 : 2016-10-01DOI: 10.1109/PMAPS.2016.7764184
S. Khuntia, Jose L. Rueda, M. A. Meijden
Electrical load forecasting in long-term horizon of power systems plays an important role for system planning and development. Load forecast in long-term horizon is represented as time-series. Thus, it is important to check the effect of volatility in the forecasted load time-series. In short, volatility in long-term horizon affects four main actions: risk management, long-term actions, reliability, and bets on future volatility. To check the effect of volatility in load series, this paper presents a univariate time series-based load forecasting technique for long-term horizon based on data corresponding to a U.S. independent system operator. The study employs ARIMA technique to forecast electrical load, and also the analyzes the ARCH and GARCH effects on the residual time-series.
{"title":"Volatility in electrical load forecasting for long-term horizon — An ARIMA-GARCH approach","authors":"S. Khuntia, Jose L. Rueda, M. A. Meijden","doi":"10.1109/PMAPS.2016.7764184","DOIUrl":"https://doi.org/10.1109/PMAPS.2016.7764184","url":null,"abstract":"Electrical load forecasting in long-term horizon of power systems plays an important role for system planning and development. Load forecast in long-term horizon is represented as time-series. Thus, it is important to check the effect of volatility in the forecasted load time-series. In short, volatility in long-term horizon affects four main actions: risk management, long-term actions, reliability, and bets on future volatility. To check the effect of volatility in load series, this paper presents a univariate time series-based load forecasting technique for long-term horizon based on data corresponding to a U.S. independent system operator. The study employs ARIMA technique to forecast electrical load, and also the analyzes the ARCH and GARCH effects on the residual time-series.","PeriodicalId":265474,"journal":{"name":"2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121450763","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 : 2016-10-01DOI: 10.1109/PMAPS.2016.7764201
Yeonchan Lee, Ungjin Oh, Duy-Phuong N. Do, Jaeseok Choi, Hongseok Choi, J. Cha, D. Jeon
This paper develops a conversion function and method transforming from daily peak load curve used LOLED [days/year] to hourly load curve used LOLEH [hours/year] firstly. The indices can not only be conversed just arithmetically but also have different characteristics physically because of using their different load curves. The conversion function is formulated as variables of capacity and forced outage rate of generator, hourly load daily load factor and daily peak load yearly load factor, etc. Therefore, the conversion function (γ = φ(·)) can not be formulated in simple but in complex and difficult. In this study, therefore, the function is formulated as linear times of separated two functions. One is exponential formed conversion function of daily load factor. Another is formulated exponential typed conversion function of daily peak load yearly load factor. Furthermore, this paper presents algorithm and flow chart for conversing from LOLED [days/year] to LOLEH[hours/year]. The proposed conversion function is applied to sample system and actual KPS(Korea Power System) in 2015. The exponent coefficients of the conversion functions are assessed using proposed method. Finally, assessment errors using conversion function for case studies of sample system and actual system are evaluated to certify the firstly proposed method.
{"title":"Relation formulation between daily and hourly load curve based loss of load expectation indices","authors":"Yeonchan Lee, Ungjin Oh, Duy-Phuong N. Do, Jaeseok Choi, Hongseok Choi, J. Cha, D. Jeon","doi":"10.1109/PMAPS.2016.7764201","DOIUrl":"https://doi.org/10.1109/PMAPS.2016.7764201","url":null,"abstract":"This paper develops a conversion function and method transforming from daily peak load curve used LOLED [days/year] to hourly load curve used LOLEH [hours/year] firstly. The indices can not only be conversed just arithmetically but also have different characteristics physically because of using their different load curves. The conversion function is formulated as variables of capacity and forced outage rate of generator, hourly load daily load factor and daily peak load yearly load factor, etc. Therefore, the conversion function (γ = φ(·)) can not be formulated in simple but in complex and difficult. In this study, therefore, the function is formulated as linear times of separated two functions. One is exponential formed conversion function of daily load factor. Another is formulated exponential typed conversion function of daily peak load yearly load factor. Furthermore, this paper presents algorithm and flow chart for conversing from LOLED [days/year] to LOLEH[hours/year]. The proposed conversion function is applied to sample system and actual KPS(Korea Power System) in 2015. The exponent coefficients of the conversion functions are assessed using proposed method. Finally, assessment errors using conversion function for case studies of sample system and actual system are evaluated to certify the firstly proposed method.","PeriodicalId":265474,"journal":{"name":"2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130272807","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 : 2016-10-01DOI: 10.1109/PMAPS.2016.7764144
Chao Yan, Lucarelli Giambattista Luca, Z. Bie, Tao Ding, Gengfeng Li
This paper proposes an interesting three-stage algorithm targeting at highly reliable high dimension composite system reliability evaluation using Importance Sampling (IS). The central idea is at the first stage (the Screening stage) picking out those bottle-neck components which have the most main impact on composite system reliability indexes calculation. The Screening process is specially customized for composite system to adaptively achieve the recognition process once the bottleneck percentage parameter μ is set reasonably. The relative perturbation value of each component is calculated firstly as the basis of recognition progress. In one time of iterations in recognition progress, a given percentage of the exciting bottle-neck components will be removed. After some iteration, those bottle-neck components will be screened out. The remaining Cross Entropy Optimization and Importance Sampling Evaluation stages are performed only considering the distortion of those bottle-neck components' sampling parameters. Numerical tests show that the method has good estimation accuracy performance and substantial variance reduction on highly reliable high dimension system. This also verifies the existence of degeneracy phenomenon of likelihood with the increase of dimension.
{"title":"A three-stage CE-IS Monte Carlo algorithm for highly reliable composite system reliability evaluation based on screening method","authors":"Chao Yan, Lucarelli Giambattista Luca, Z. Bie, Tao Ding, Gengfeng Li","doi":"10.1109/PMAPS.2016.7764144","DOIUrl":"https://doi.org/10.1109/PMAPS.2016.7764144","url":null,"abstract":"This paper proposes an interesting three-stage algorithm targeting at highly reliable high dimension composite system reliability evaluation using Importance Sampling (IS). The central idea is at the first stage (the Screening stage) picking out those bottle-neck components which have the most main impact on composite system reliability indexes calculation. The Screening process is specially customized for composite system to adaptively achieve the recognition process once the bottleneck percentage parameter μ is set reasonably. The relative perturbation value of each component is calculated firstly as the basis of recognition progress. In one time of iterations in recognition progress, a given percentage of the exciting bottle-neck components will be removed. After some iteration, those bottle-neck components will be screened out. The remaining Cross Entropy Optimization and Importance Sampling Evaluation stages are performed only considering the distortion of those bottle-neck components' sampling parameters. Numerical tests show that the method has good estimation accuracy performance and substantial variance reduction on highly reliable high dimension system. This also verifies the existence of degeneracy phenomenon of likelihood with the increase of dimension.","PeriodicalId":265474,"journal":{"name":"2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133975361","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 : 2016-10-01DOI: 10.1109/PMAPS.2016.7764080
Zhen Wang, D. Feng, Sheng Lin, Zhengyou He
Weather condition has a great influence on the reliability assessment of the high-speed railway catenary system. This paper proposes a reliability assessment method for high-speed railway catenary system considering weather conditions. The weather condition is classified according to IEEE standard, and the failure rate model of catenary component is built under three weather conditions. Then the failure rate and repair rate under different weather conditions are considered as random fuzzy variables. Credibility theory is applied to evaluate the influence of uncertainties on the reliability assessment of catenary system. Finally, fault tree analysis method is introduced to calculate the reliability indices of the catenary system. Case study shows the proposed method achieves reliability assessment for catenary of high-speed railway system considering the influence of weather conditions, and the reliability indices under different weather conditions are obtained.
{"title":"Research on reliability evaluation method of catenary of high speed railway considering weather condition","authors":"Zhen Wang, D. Feng, Sheng Lin, Zhengyou He","doi":"10.1109/PMAPS.2016.7764080","DOIUrl":"https://doi.org/10.1109/PMAPS.2016.7764080","url":null,"abstract":"Weather condition has a great influence on the reliability assessment of the high-speed railway catenary system. This paper proposes a reliability assessment method for high-speed railway catenary system considering weather conditions. The weather condition is classified according to IEEE standard, and the failure rate model of catenary component is built under three weather conditions. Then the failure rate and repair rate under different weather conditions are considered as random fuzzy variables. Credibility theory is applied to evaluate the influence of uncertainties on the reliability assessment of catenary system. Finally, fault tree analysis method is introduced to calculate the reliability indices of the catenary system. Case study shows the proposed method achieves reliability assessment for catenary of high-speed railway system considering the influence of weather conditions, and the reliability indices under different weather conditions are obtained.","PeriodicalId":265474,"journal":{"name":"2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":"278 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134346782","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 : 2016-10-01DOI: 10.1109/PMAPS.2016.7764148
Chen Liang, Peng Wang, Xiaoqing Han, W. Qin, Yanbing Jia
A major concern for wind farm connection to power systems is large variation of power output caused by the variability and unpredictability of wind speed. For a power system with high wind power penetration, the frequency control process of conventional generators (CGs) to match load and wind power variation becomes an important operation issue. Energy storage systems play an important role in solving the problem. This paper proposes an analytical technique to select the optimal size of battery storage system (BSS) for a power system based on operational reliability analysis and frequency control process. According to optimal size of BSS, the optimal size of state of charge (SOC) and depth of discharge (DOD) are selected to achieve the minimal frequency variation for the fixed wind farm.
{"title":"Reliability and efficiency-based energy storage sizing from the aspect of system frequency","authors":"Chen Liang, Peng Wang, Xiaoqing Han, W. Qin, Yanbing Jia","doi":"10.1109/PMAPS.2016.7764148","DOIUrl":"https://doi.org/10.1109/PMAPS.2016.7764148","url":null,"abstract":"A major concern for wind farm connection to power systems is large variation of power output caused by the variability and unpredictability of wind speed. For a power system with high wind power penetration, the frequency control process of conventional generators (CGs) to match load and wind power variation becomes an important operation issue. Energy storage systems play an important role in solving the problem. This paper proposes an analytical technique to select the optimal size of battery storage system (BSS) for a power system based on operational reliability analysis and frequency control process. According to optimal size of BSS, the optimal size of state of charge (SOC) and depth of discharge (DOD) are selected to achieve the minimal frequency variation for the fixed wind farm.","PeriodicalId":265474,"journal":{"name":"2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131890125","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 : 2016-10-01DOI: 10.1109/PMAPS.2016.7764164
E. Ciapessoni, D. Cirio, A. Pitto, N. Omont
The increasing penetration of renewables and the constraints posed by pan-European market make more and more crucial the need to evaluate the dynamic behaviour of the whole grid and to cope with forecast uncertainties from operational planning to online environment. The FP7 EU project iTesla addresses these needs and encompasses several major objectives, including the definition of a platform architecture, a dynamic data structure, and dynamic model validation. The on line security assessment is characterised by a multi-stage filtering process: this includes a “Monte Carlo like approach” which applies the security rules derived from extensive security analyses performed offline to a set of “new base cases” sampled around the power system (PS) forecast state with the aim to discard as many stable contingencies as possible. The paper will focus on the management of historical data - related to stochastic renewable and load snapshots and forecasts-in order to solve some intrinsic criticalities of raw data and to derive a reliable model of the multivariate distributions of renewables and loads conditioned to the specific forecast state of the grid, with the final aim to generate the “uncertainty region” of states around the forecast state.
{"title":"Forecast uncertainty modeling and data management for a cutting-edge security assessment platform","authors":"E. Ciapessoni, D. Cirio, A. Pitto, N. Omont","doi":"10.1109/PMAPS.2016.7764164","DOIUrl":"https://doi.org/10.1109/PMAPS.2016.7764164","url":null,"abstract":"The increasing penetration of renewables and the constraints posed by pan-European market make more and more crucial the need to evaluate the dynamic behaviour of the whole grid and to cope with forecast uncertainties from operational planning to online environment. The FP7 EU project iTesla addresses these needs and encompasses several major objectives, including the definition of a platform architecture, a dynamic data structure, and dynamic model validation. The on line security assessment is characterised by a multi-stage filtering process: this includes a “Monte Carlo like approach” which applies the security rules derived from extensive security analyses performed offline to a set of “new base cases” sampled around the power system (PS) forecast state with the aim to discard as many stable contingencies as possible. The paper will focus on the management of historical data - related to stochastic renewable and load snapshots and forecasts-in order to solve some intrinsic criticalities of raw data and to derive a reliable model of the multivariate distributions of renewables and loads conditioned to the specific forecast state of the grid, with the final aim to generate the “uncertainty region” of states around the forecast state.","PeriodicalId":265474,"journal":{"name":"2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132936781","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 : 2016-10-01DOI: 10.1109/PMAPS.2016.7764163
T. Xu, Zongxiang Lu, Yichao Huang, Ruanming Huang, Aili Pang
With the increase of load density and the high request of supply reliability, voltage level of urban power grids is continuously rising. 220 kV has been popular in cities and even 500 kV substations have been directly located in urban area. Multiple voltage levels coexist in a rather small area, forming a meshed transmission and distribution network in urban region. So traditional distribution system reliability evaluation approaches can barely satisfy the requirements of reliability evaluation in urban power grid planning and operation. A reliability assessment approach for multiple-voltage regional systems based on reliability equivalent law of series system is proposed. An equivalent model of substation bus system has been introduced, considering simultaneous outage of multiple feeders and common mode failure (CMF) inside substations, which incorporates the effect of substation failures on the reliability of the network. This method has been applied on a typical urban grid in China with medium- and high-voltage distribution network. Simulation results have proven the effectiveness and advantages of this method, which can act as an aid in decision making for urban grid planning and design.
{"title":"Reliability assessment of multiple-voltage regional transmission and distribution system considering substation interior failure","authors":"T. Xu, Zongxiang Lu, Yichao Huang, Ruanming Huang, Aili Pang","doi":"10.1109/PMAPS.2016.7764163","DOIUrl":"https://doi.org/10.1109/PMAPS.2016.7764163","url":null,"abstract":"With the increase of load density and the high request of supply reliability, voltage level of urban power grids is continuously rising. 220 kV has been popular in cities and even 500 kV substations have been directly located in urban area. Multiple voltage levels coexist in a rather small area, forming a meshed transmission and distribution network in urban region. So traditional distribution system reliability evaluation approaches can barely satisfy the requirements of reliability evaluation in urban power grid planning and operation. A reliability assessment approach for multiple-voltage regional systems based on reliability equivalent law of series system is proposed. An equivalent model of substation bus system has been introduced, considering simultaneous outage of multiple feeders and common mode failure (CMF) inside substations, which incorporates the effect of substation failures on the reliability of the network. This method has been applied on a typical urban grid in China with medium- and high-voltage distribution network. Simulation results have proven the effectiveness and advantages of this method, which can act as an aid in decision making for urban grid planning and design.","PeriodicalId":265474,"journal":{"name":"2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126573166","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 : 2016-10-01DOI: 10.1109/PMAPS.2016.7764202
Yuting Tian, M. Benidris, Samer Sulaeman, S. Elsaiah, J. Mitra
This paper presents a methodology to determine the optimal distribution system feeder reconfiguration and distributed generation placement simultaneously, and is optimal in that the system reliability is maximized. An important consideration of optimal distribution system feeder reconfiguration is the effect of the variable output of intermittent resources. The work presented in this paper considers the stochastic behavior of variable resources, and open/close status of the sectionalizing and tie-switches as variables in determining the optimal DG locations and optimal configuration that enhance system reliability. Genetic algorithm is applied to search for the optimal or near-optimal solution. The proposed method is demonstrated on a 33-bus radial distribution system, which is extensively used as an example in solving the distribution system reconfiguration problem.
{"title":"Optimal feeder reconfiguration and distributed generation placement for reliability improvement","authors":"Yuting Tian, M. Benidris, Samer Sulaeman, S. Elsaiah, J. Mitra","doi":"10.1109/PMAPS.2016.7764202","DOIUrl":"https://doi.org/10.1109/PMAPS.2016.7764202","url":null,"abstract":"This paper presents a methodology to determine the optimal distribution system feeder reconfiguration and distributed generation placement simultaneously, and is optimal in that the system reliability is maximized. An important consideration of optimal distribution system feeder reconfiguration is the effect of the variable output of intermittent resources. The work presented in this paper considers the stochastic behavior of variable resources, and open/close status of the sectionalizing and tie-switches as variables in determining the optimal DG locations and optimal configuration that enhance system reliability. Genetic algorithm is applied to search for the optimal or near-optimal solution. The proposed method is demonstrated on a 33-bus radial distribution system, which is extensively used as an example in solving the distribution system reconfiguration problem.","PeriodicalId":265474,"journal":{"name":"2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130728179","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 : 2016-10-01DOI: 10.1109/PMAPS.2016.7764132
Max Csef, Andrea Antenucci, G. Sansavini
High penetrations of intermittent renewable energy sources (RES) affect the operations of power plants whose task is the balancing of generation and demand, and may induce critical states in interdependent energy infrastructures. In this contribution, the interdependent electric power and gas transmission networks are assessed under an operational risk perspective for different levels of wind energy integration. This investigation is exemplified with reference to a case study of the gas and electric transmission network of Great Britain (GB). A D-vine copula is developed for producing spatio-temporally correlated wind speed time series. In contrast to multivariate models built with autoregressive techniques or one-parameter multidimensional copulas which are restricted to modelling linear dependence or one type of dependence respectively, vine copulas offer high flexibility in modelling dependence. Due to large penetrations of wind power operational constraint violations in the gas network, e.g. pressure violations or compressor shut-downs, may occur when gas-fired power plants (GFPPs) need to ramp up quickly to compensate correlated fluctuations in wind generation. Results identify that large ramp-down rates of wind generation may cause large energy-not-served (ENS) in the electric network. For high levels of wind energy integration, unfavorable combinations of ramp-up and ramp-down are a realistic starting point of failure cascades leading to high levels of demand-not-served in the electric grid and curtailments and component failures in the gas network. Failure prone components in the gas network are identified.
{"title":"Impact of spatio-temporally correlated wind generation on the interdependent operations of gas and electric networks","authors":"Max Csef, Andrea Antenucci, G. Sansavini","doi":"10.1109/PMAPS.2016.7764132","DOIUrl":"https://doi.org/10.1109/PMAPS.2016.7764132","url":null,"abstract":"High penetrations of intermittent renewable energy sources (RES) affect the operations of power plants whose task is the balancing of generation and demand, and may induce critical states in interdependent energy infrastructures. In this contribution, the interdependent electric power and gas transmission networks are assessed under an operational risk perspective for different levels of wind energy integration. This investigation is exemplified with reference to a case study of the gas and electric transmission network of Great Britain (GB). A D-vine copula is developed for producing spatio-temporally correlated wind speed time series. In contrast to multivariate models built with autoregressive techniques or one-parameter multidimensional copulas which are restricted to modelling linear dependence or one type of dependence respectively, vine copulas offer high flexibility in modelling dependence. Due to large penetrations of wind power operational constraint violations in the gas network, e.g. pressure violations or compressor shut-downs, may occur when gas-fired power plants (GFPPs) need to ramp up quickly to compensate correlated fluctuations in wind generation. Results identify that large ramp-down rates of wind generation may cause large energy-not-served (ENS) in the electric network. For high levels of wind energy integration, unfavorable combinations of ramp-up and ramp-down are a realistic starting point of failure cascades leading to high levels of demand-not-served in the electric grid and curtailments and component failures in the gas network. Failure prone components in the gas network are identified.","PeriodicalId":265474,"journal":{"name":"2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132999992","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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