Pub Date : 2020-08-01DOI: 10.1109/PMAPS47429.2020.9183684
A. Alamri, Maad Alowaifeer, A. P. Sakis Meliopoulos
This paper presents a multi-objective unit commitment economic dispatch (UCED) model. The model considers minimizing two conflicting objective functions; the minimization of the generation cost and the minimization (shaving) of the composite demand (CD) peak. The model takes into account conventional generation (CG) operating constraints, variable generation (VG) forced outages and seasonal variation, demand and energy storage system operation constraints. The multi-objective function is solved considering multiple priorities of the two objective functions. Upon retrieving the optimal results from the optimization problems, the reliability indices are computed using the probabilistic production costing (PPC) method. The model is applied to a test system consisting of 10 CG units, wind farms (WFs), solar farms (SFs), and ESS. Example test cases are presented with different penetration levels and ESS size.
{"title":"Multi-Objective Unit Commitment Economic Dispatch for Power Systems Reliability Assessment","authors":"A. Alamri, Maad Alowaifeer, A. P. Sakis Meliopoulos","doi":"10.1109/PMAPS47429.2020.9183684","DOIUrl":"https://doi.org/10.1109/PMAPS47429.2020.9183684","url":null,"abstract":"This paper presents a multi-objective unit commitment economic dispatch (UCED) model. The model considers minimizing two conflicting objective functions; the minimization of the generation cost and the minimization (shaving) of the composite demand (CD) peak. The model takes into account conventional generation (CG) operating constraints, variable generation (VG) forced outages and seasonal variation, demand and energy storage system operation constraints. The multi-objective function is solved considering multiple priorities of the two objective functions. Upon retrieving the optimal results from the optimization problems, the reliability indices are computed using the probabilistic production costing (PPC) method. The model is applied to a test system consisting of 10 CG units, wind farms (WFs), solar farms (SFs), and ESS. Example test cases are presented with different penetration levels and ESS size.","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":"122147400","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/PMAPS47429.2020.9183434
Nestor Sanchez, C. Dent, Amy L. Wilson
A reliable electricity supply is a key consideration for energy system planners. At present, the value of support from other systems is of particular interest in Great Britain (GB), including from Ireland’s (IRL) Single Electricity Market, to which there is currently 1 GW of interconnection capacity. This paper presents a study of how interconnection influences risk levels in the GB and IRL systems, based on the standard Loss of Load Expectation (LOLE) and Expected Energy Unserved (EEU) indices, and a ‘hindcast’ approach for demand and wind generation. Specific areas of investigation include the effect of different resource sharing policies on risk levels, and the dependence of the value of interconnection on the wind capacities in the two systems.
{"title":"Quantifying The Reliability Contribution of Interconnectors in the Britain - Ireland Power System Using a Hindcast Approach","authors":"Nestor Sanchez, C. Dent, Amy L. Wilson","doi":"10.1109/PMAPS47429.2020.9183434","DOIUrl":"https://doi.org/10.1109/PMAPS47429.2020.9183434","url":null,"abstract":"A reliable electricity supply is a key consideration for energy system planners. At present, the value of support from other systems is of particular interest in Great Britain (GB), including from Ireland’s (IRL) Single Electricity Market, to which there is currently 1 GW of interconnection capacity. This paper presents a study of how interconnection influences risk levels in the GB and IRL systems, based on the standard Loss of Load Expectation (LOLE) and Expected Energy Unserved (EEU) indices, and a ‘hindcast’ approach for demand and wind generation. Specific areas of investigation include the effect of different resource sharing policies on risk levels, and the dependence of the value of interconnection on the wind capacities in the two systems.","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":"131487303","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/PMAPS47429.2020.9183653
M. Papic, J. Ellsworth, A. Delgado, E. Schellenberg, G. Travis, G. Preston
As we move into the future, variable energy resources (VERs), such as wind and solar, will begin to dominate utilities resource portfolios. We see indicative signs of this in the western interconnection with utility Integrated Resource Plans (IRPs) bypassing the natural gas "bridge resource" and identifying copious quantities of wind and solar in their 20-year plans as they work to retire increasing amounts of higher energy-cost fossil-based resources – especially coal. Adequacy assessment of systems with ongoing integration of VER, has added new requirements to enhance the current methodologies and tools for computing the widely-used Loss-of-Load-Expectation (LOLE) index. This paper presents the practical experience in evaluating the adequacy of the Idaho Power Company (IPC) generation system with integrated VER such as wind and solar. In this paper the adequacy assessment includes an analysis of uncertainties associated with load, limited energy sources (hydro), variable wind and solar energy sources, and forced and maintenance outages of generating units. The transmission contingency driven constraints have not been considered. The adequacy indexes, such as LOLE and Expected Unserved Energy (EUE), are calculated by using an analytical convolution approach that considers the realistic time series of available generation produced by VER, such as hydro, wind and solar. This paper explores, compares and presents the reliability results of four top Idaho IRPs portfolios that are selected among the 24 studied portfolios based on the cost and risk. The results suggest that the portfolio that includes a new transmission line, wind, and solar resources has the highest reliability and was one selected by IPC. In addition, the case study results indicate which wind and solar resources by location will provide more value in reducing LOLE index and show the impact of Load Forecast Uncertainty (LFU) on the LOLE and EUE indexes. The capacity contributions of future VER are also evaluated by using the Effective Load Carrying Capability (ELCC) approach across five different meteorological profile years (2015-2019).
{"title":"Adequacy Assessment of the Idaho Power Generation System with Integrated Variable Energy Sources","authors":"M. Papic, J. Ellsworth, A. Delgado, E. Schellenberg, G. Travis, G. Preston","doi":"10.1109/PMAPS47429.2020.9183653","DOIUrl":"https://doi.org/10.1109/PMAPS47429.2020.9183653","url":null,"abstract":"As we move into the future, variable energy resources (VERs), such as wind and solar, will begin to dominate utilities resource portfolios. We see indicative signs of this in the western interconnection with utility Integrated Resource Plans (IRPs) bypassing the natural gas \"bridge resource\" and identifying copious quantities of wind and solar in their 20-year plans as they work to retire increasing amounts of higher energy-cost fossil-based resources – especially coal. Adequacy assessment of systems with ongoing integration of VER, has added new requirements to enhance the current methodologies and tools for computing the widely-used Loss-of-Load-Expectation (LOLE) index. This paper presents the practical experience in evaluating the adequacy of the Idaho Power Company (IPC) generation system with integrated VER such as wind and solar. In this paper the adequacy assessment includes an analysis of uncertainties associated with load, limited energy sources (hydro), variable wind and solar energy sources, and forced and maintenance outages of generating units. The transmission contingency driven constraints have not been considered. The adequacy indexes, such as LOLE and Expected Unserved Energy (EUE), are calculated by using an analytical convolution approach that considers the realistic time series of available generation produced by VER, such as hydro, wind and solar. This paper explores, compares and presents the reliability results of four top Idaho IRPs portfolios that are selected among the 24 studied portfolios based on the cost and risk. The results suggest that the portfolio that includes a new transmission line, wind, and solar resources has the highest reliability and was one selected by IPC. In addition, the case study results indicate which wind and solar resources by location will provide more value in reducing LOLE index and show the impact of Load Forecast Uncertainty (LFU) on the LOLE and EUE indexes. The capacity contributions of future VER are also evaluated by using the Effective Load Carrying Capability (ELCC) approach across five different meteorological profile years (2015-2019).","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":"131807955","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/PMAPS47429.2020.9183667
S. F. Myhre, Olav Bjarte Fosso, P. Heegaard, O. Gjerde, G. Kjølle
The extensive integration of information and communication technology (ICT) in the future electrical power system transforms the power system to a cyber physical system (CPS), making it a system-of-systems. This new system topology creates interdependent relationships between the cyber and the physical parts in the power system and introduces new possible vulnerabilities and risks which might lead to unwanted events such as outages and blackouts. For electrical power system operators, it is important to understand the new complexity of the system and how to address these new changes in order to ensure safe system operation and security of electricity supply. This paper focuses on the introduction of complex network theory as a method to discover and measure the importance of the system nodes, both electrical and ICT, in a combined electrical power distribution and communication network. There are two different methods used for measuring the importance, 1) betweenness centrality and 2) node attack method. The methods are evaluated through a case study and found suitable in capturing the important nodes in the combined electrical power and communication network.
{"title":"Modeling Interdependencies with Complex Network Theory in a Combined Electrical Power and ICT System","authors":"S. F. Myhre, Olav Bjarte Fosso, P. Heegaard, O. Gjerde, G. Kjølle","doi":"10.1109/PMAPS47429.2020.9183667","DOIUrl":"https://doi.org/10.1109/PMAPS47429.2020.9183667","url":null,"abstract":"The extensive integration of information and communication technology (ICT) in the future electrical power system transforms the power system to a cyber physical system (CPS), making it a system-of-systems. This new system topology creates interdependent relationships between the cyber and the physical parts in the power system and introduces new possible vulnerabilities and risks which might lead to unwanted events such as outages and blackouts. For electrical power system operators, it is important to understand the new complexity of the system and how to address these new changes in order to ensure safe system operation and security of electricity supply. This paper focuses on the introduction of complex network theory as a method to discover and measure the importance of the system nodes, both electrical and ICT, in a combined electrical power distribution and communication network. There are two different methods used for measuring the importance, 1) betweenness centrality and 2) node attack method. The methods are evaluated through a case study and found suitable in capturing the important nodes in the combined electrical power and communication network.","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":"131798953","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/PMAPS47429.2020.9183656
A. Bracale, P. Caramia, G. Carpinelli, P. De Falco
The smart grid paradigm pushes for intelligent operation of the transformers that are already installed in the networks, to cope with peak load and/or to enable more intense exploitation of renewables. However, transformer loading is affected by several factors that should be considered, among which the thermal stress is recognized as the most influencing one. In this context, the dynamic thermal rating concept is of great interest and it allows fixing the maximum allowable current in different operating conditions, still maintaining acceptable risk levels based on the consequences of loading the transformers beyond the nameplate ratings. A probabilistic procedure for managing the delivery of power to load by the dynamic transformer rating is presented in this paper. The procedure is based on the risk analysis related to the thermal stress introduced by the transformer (over)load, which determines loss of life and potential dielectric failure. Numerical experiments based on actual data are performed for several scenarios, and several cases are presented to support the procedure for the intelligent exploitation of the potentialities of transformers.
{"title":"Probabilistic Management of Power Delivery Based on Dynamic Transformer Rating","authors":"A. Bracale, P. Caramia, G. Carpinelli, P. De Falco","doi":"10.1109/PMAPS47429.2020.9183656","DOIUrl":"https://doi.org/10.1109/PMAPS47429.2020.9183656","url":null,"abstract":"The smart grid paradigm pushes for intelligent operation of the transformers that are already installed in the networks, to cope with peak load and/or to enable more intense exploitation of renewables. However, transformer loading is affected by several factors that should be considered, among which the thermal stress is recognized as the most influencing one. In this context, the dynamic thermal rating concept is of great interest and it allows fixing the maximum allowable current in different operating conditions, still maintaining acceptable risk levels based on the consequences of loading the transformers beyond the nameplate ratings. A probabilistic procedure for managing the delivery of power to load by the dynamic transformer rating is presented in this paper. The procedure is based on the risk analysis related to the thermal stress introduced by the transformer (over)load, which determines loss of life and potential dielectric failure. Numerical experiments based on actual data are performed for several scenarios, and several cases are presented to support the procedure for the intelligent exploitation of the potentialities of transformers.","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":"116620849","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/PMAPS47429.2020.9183701
S. Mathieu, D. Ernst, Quentin Gemine
Electrical distribution systems need to integrate more and more renewable energy generation in their network. Since networks cannot be quickly upgraded at a low cost, new generators are connected to the network under non-firm access contracts. These contracts allow distribution system operators to specify dynamic access limits according to a given regulatory policy, e.g. "last-in, first-out" or a similar policy. Due to operational delays, access limits must be communicated before realtime, e.g. ten minutes ahead. This paper presents an operational method to compute these dynamic access limits using correlated probabilistic forecasts of power consumption and production processes. The method is illustrated on a test-case based on real data where no additional production would be allowed under firm access. Results show that the method allows to safely integrate additional production capacity while limiting congestion events, provided that efficient probabilistic forecasts able to anticipate sudden and important changes are available.
{"title":"Short-term active distribution network operation under uncertainty","authors":"S. Mathieu, D. Ernst, Quentin Gemine","doi":"10.1109/PMAPS47429.2020.9183701","DOIUrl":"https://doi.org/10.1109/PMAPS47429.2020.9183701","url":null,"abstract":"Electrical distribution systems need to integrate more and more renewable energy generation in their network. Since networks cannot be quickly upgraded at a low cost, new generators are connected to the network under non-firm access contracts. These contracts allow distribution system operators to specify dynamic access limits according to a given regulatory policy, e.g. \"last-in, first-out\" or a similar policy. Due to operational delays, access limits must be communicated before realtime, e.g. ten minutes ahead. This paper presents an operational method to compute these dynamic access limits using correlated probabilistic forecasts of power consumption and production processes. The method is illustrated on a test-case based on real data where no additional production would be allowed under firm access. Results show that the method allows to safely integrate additional production capacity while limiting congestion events, provided that efficient probabilistic forecasts able to anticipate sudden and important changes are available.","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":"129886033","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/PMAPS47429.2020.9183426
P. A. G. M. Amarasinghe, S. Abeygunawardane, C. Singh
The rapid integration of intermittent renewables such as wind and solar into the power grid tends to degrade the system's reliability. Therefore, energy storages are required to satisfy consumer demand continuously by compensating for the frequent fluctuations of renewable power generation. In this paper, the impact of integrating pumped storage on the adequacy of renewable rich power generating systems is investigated. The variations of generation system adequacy indices are analyzed for different pumped storage capacities and storage levels. The adequacy indices are obtained using sequential Monte Carlo simulation for the IEEE reliability test system-79 which is modified by integrating a pumped storage and renewable generators. According to the results, the generating system adequacy is significantly affected by both the pumped storage capacity and the storage level. When a pumped storage is integrated, the generation system failures in spring, fall, summer and winter are found to be reduced by 80.4 %, 79.1 %, 58.9 % and 55.6 % respectively. Moreover, the equivalent capacity of a 300 MW pumped hydro plant with 1000 MWh storage level is found to be 216 MW in terms of a conventional generating unit. These results show that a significant level of reliability improvement can be obtained by pumped storage plants, especially in renewable rich power systems.
{"title":"Impact of Pumped Storage on the Adequacy of Renewable Rich Power Generation Systems","authors":"P. A. G. M. Amarasinghe, S. Abeygunawardane, C. Singh","doi":"10.1109/PMAPS47429.2020.9183426","DOIUrl":"https://doi.org/10.1109/PMAPS47429.2020.9183426","url":null,"abstract":"The rapid integration of intermittent renewables such as wind and solar into the power grid tends to degrade the system's reliability. Therefore, energy storages are required to satisfy consumer demand continuously by compensating for the frequent fluctuations of renewable power generation. In this paper, the impact of integrating pumped storage on the adequacy of renewable rich power generating systems is investigated. The variations of generation system adequacy indices are analyzed for different pumped storage capacities and storage levels. The adequacy indices are obtained using sequential Monte Carlo simulation for the IEEE reliability test system-79 which is modified by integrating a pumped storage and renewable generators. According to the results, the generating system adequacy is significantly affected by both the pumped storage capacity and the storage level. When a pumped storage is integrated, the generation system failures in spring, fall, summer and winter are found to be reduced by 80.4 %, 79.1 %, 58.9 % and 55.6 % respectively. Moreover, the equivalent capacity of a 300 MW pumped hydro plant with 1000 MWh storage level is found to be 216 MW in terms of a conventional generating unit. These results show that a significant level of reliability improvement can be obtained by pumped storage plants, especially in renewable rich power systems.","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":"129912343","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/PMAPS47429.2020.9183450
S. Karimi-Arpanahi, M. Jooshaki, M. Fotuhi‐Firuzabad, M. Lehtonen
Increasing grid integration of intermittent renewable energy sources (RESs) and plug-in electric vehicles (PEVs) with uncertain behaviours have necessitated enhancing the flexibility requirements of distribution networks. Thus, in the state-of-the-art distribution network expansion planning (DNEP) models, both flexibility requirements and high penetration of RESs and PEVs should be taken into consideration. In this respect, a novel collaborative planning model for power distribution network (PDN) and plug-in Electric Vehicle Parking Lots (EVPLs) is proposed in this paper, which leverages sizing, siting, and operation of EVPLs to enhance the distribution network flexibility. Also, to model the uncertain traffic flow of PEVs, a new model is proposed and is utilized to obtain a preliminary dispatch of PEV charging and, in turn, an estimated EVPL demand. Afterwards, this estimated demand is fed into the collaborative planning model to obtain the optimal expansion planning solution for PDN, and the size and location of EVPLs. Nonetheless, to provide the network operator with more flexibility sources, it is assumed that the operator can reschedule the charging pattern of some PEVs by compensating the EVPL owners for the difference in retail electricity prices of various hours. Finally, to illustrate the effectiveness of the proposed model, it is implemented on a test network, and the obtained results are discussed.
{"title":"Flexibility-Oriented Collaborative Planning Model for Distribution Network and EV Parking Lots Considering Uncertain Behaviour of EVs","authors":"S. Karimi-Arpanahi, M. Jooshaki, M. Fotuhi‐Firuzabad, M. Lehtonen","doi":"10.1109/PMAPS47429.2020.9183450","DOIUrl":"https://doi.org/10.1109/PMAPS47429.2020.9183450","url":null,"abstract":"Increasing grid integration of intermittent renewable energy sources (RESs) and plug-in electric vehicles (PEVs) with uncertain behaviours have necessitated enhancing the flexibility requirements of distribution networks. Thus, in the state-of-the-art distribution network expansion planning (DNEP) models, both flexibility requirements and high penetration of RESs and PEVs should be taken into consideration. In this respect, a novel collaborative planning model for power distribution network (PDN) and plug-in Electric Vehicle Parking Lots (EVPLs) is proposed in this paper, which leverages sizing, siting, and operation of EVPLs to enhance the distribution network flexibility. Also, to model the uncertain traffic flow of PEVs, a new model is proposed and is utilized to obtain a preliminary dispatch of PEV charging and, in turn, an estimated EVPL demand. Afterwards, this estimated demand is fed into the collaborative planning model to obtain the optimal expansion planning solution for PDN, and the size and location of EVPLs. Nonetheless, to provide the network operator with more flexibility sources, it is assumed that the operator can reschedule the charging pattern of some PEVs by compensating the EVPL owners for the difference in retail electricity prices of various hours. Finally, to illustrate the effectiveness of the proposed model, it is implemented on a test network, and the obtained results are 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":"133941493","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/PMAPS47429.2020.9183647
I. Granitsas, T. Souxes, C. Vournas, M. Koivisto, M. Sarkar, P. Sørensen
In this paper two types of synthetic wind power time series are used to assess the effect of wind variability in the long-term voltage stability assessment of a power system. A wind power time series is generated using the wind simulation tool CorWind, which is based on power spectral density. This time series is then used as input to develop a Markov model for wind power simulation. Both the CorWind time series and randomly generated time series using the Markov model are then applied to a simple power system and the effect of wind variability on the maximum power transfer to a remote load is investigated.
{"title":"Use of Synthetic Wind Power Time Series for Long-term Voltage Stability Analysis","authors":"I. Granitsas, T. Souxes, C. Vournas, M. Koivisto, M. Sarkar, P. Sørensen","doi":"10.1109/PMAPS47429.2020.9183647","DOIUrl":"https://doi.org/10.1109/PMAPS47429.2020.9183647","url":null,"abstract":"In this paper two types of synthetic wind power time series are used to assess the effect of wind variability in the long-term voltage stability assessment of a power system. A wind power time series is generated using the wind simulation tool CorWind, which is based on power spectral density. This time series is then used as input to develop a Markov model for wind power simulation. Both the CorWind time series and randomly generated time series using the Markov model are then applied to a simple power system and the effect of wind variability on the maximum power transfer to a remote load is investigated.","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":"132662214","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/PMAPS47429.2020.9183591
A. Hilbers, D. Brayshaw, A. Gandy
This paper introduces a generalised version of importance subsampling for time series reduction/aggregation in optimisation-based power system planning models. Recent studies indicate that reliably determining optimal electricity (investment) strategy under climate variability requires the consideration of multiple years of demand and weather data. However, solving planning models over long simulation lengths is typically computationally unfeasible, and established time series reduction approaches induce significant errors. The importance subsampling method reliably estimates long-term planning model outputs at greatly reduced computational cost, allowing the consideration of multi-decadal samples. The key innovation is a systematic identification and preservation of relevant extreme events in modeling subsamples. Simulation studies on generation and transmission expansion planning models illustrate the method’s enhanced performance over established "representative days" clustering approaches. The models, data and sample code are made available as open-source software.
{"title":"Importance subsampling for power system planning under multi-year demand and weather uncertainty","authors":"A. Hilbers, D. Brayshaw, A. Gandy","doi":"10.1109/PMAPS47429.2020.9183591","DOIUrl":"https://doi.org/10.1109/PMAPS47429.2020.9183591","url":null,"abstract":"This paper introduces a generalised version of importance subsampling for time series reduction/aggregation in optimisation-based power system planning models. Recent studies indicate that reliably determining optimal electricity (investment) strategy under climate variability requires the consideration of multiple years of demand and weather data. However, solving planning models over long simulation lengths is typically computationally unfeasible, and established time series reduction approaches induce significant errors. The importance subsampling method reliably estimates long-term planning model outputs at greatly reduced computational cost, allowing the consideration of multi-decadal samples. The key innovation is a systematic identification and preservation of relevant extreme events in modeling subsamples. Simulation studies on generation and transmission expansion planning models illustrate the method’s enhanced performance over established \"representative days\" clustering approaches. The models, data and sample code are made available as open-source software.","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":"134152396","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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