Pub Date : 2018-06-01DOI: 10.1109/EEM.2018.8469827
Toni Tukia, Semen Uimonen, M. Lehtonen
This paper analyzes the potential of applying elevators in power system frequency containment reserves (FCR). As an example, the study employs the Finnish FCR market structure. The markets are split into two segments: frequency containment reserves for normal operation (FCR-N) and for disturbances (FCR-D). Both of the markets have distinct minimum bid sizes and thresholds for the maximum allowed delay for activating the reserves. The paper uses a unique elevator simulator to assess the power consumption profiles of common elevator setups. Then, the elevators are aggregated into a virtual power plant (VPP) and controlled with a variety of approaches to rank the effectiveness of each control method. As a result, the paper estimates the potential contribution of elevators to a VPP-provided service as well as the adverse impact on traffic performance f or different elevator types in hourly granularity for weekdays and weekends.
{"title":"Evaluating the Applicability of Elevators in Frequency Containment Reserves","authors":"Toni Tukia, Semen Uimonen, M. Lehtonen","doi":"10.1109/EEM.2018.8469827","DOIUrl":"https://doi.org/10.1109/EEM.2018.8469827","url":null,"abstract":"This paper analyzes the potential of applying elevators in power system frequency containment reserves (FCR). As an example, the study employs the Finnish FCR market structure. The markets are split into two segments: frequency containment reserves for normal operation (FCR-N) and for disturbances (FCR-D). Both of the markets have distinct minimum bid sizes and thresholds for the maximum allowed delay for activating the reserves. The paper uses a unique elevator simulator to assess the power consumption profiles of common elevator setups. Then, the elevators are aggregated into a virtual power plant (VPP) and controlled with a variety of approaches to rank the effectiveness of each control method. As a result, the paper estimates the potential contribution of elevators to a VPP-provided service as well as the adverse impact on traffic performance f or different elevator types in hourly granularity for weekdays and weekends.","PeriodicalId":334674,"journal":{"name":"2018 15th International Conference on the European Energy Market (EEM)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114447585","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 : 2018-06-01DOI: 10.1109/EEM.2018.8469920
A. Sanchez de la Nieta, M. Gibescu
The day-ahead electricity market is composed of demand and supply orders. Once market participants have sent their orders, the market clearing algorithm decides the accepted and rejected orders, according to the principle of social welfare maximization. This paper proposes the maximization of daily social welfare through demand side management (DSM), modeled as flexible demand orders per time interval. For that purpose, a linear programming model is implemented whose objective function maximizes the daily social welfare following the balance and the demand side management constraints. A test case over 24 hours shows three strategies through a new price order. These strategies are as follows: the new price order is equal to, higher or lower than the price of the original demand order. Some conclusions are also drawn with respect to the social welfare and the consequences for the suppliers.
{"title":"Maximal Daily Social Welfare Through Demand Side Management in the Day-Ahead Electricity Market","authors":"A. Sanchez de la Nieta, M. Gibescu","doi":"10.1109/EEM.2018.8469920","DOIUrl":"https://doi.org/10.1109/EEM.2018.8469920","url":null,"abstract":"The day-ahead electricity market is composed of demand and supply orders. Once market participants have sent their orders, the market clearing algorithm decides the accepted and rejected orders, according to the principle of social welfare maximization. This paper proposes the maximization of daily social welfare through demand side management (DSM), modeled as flexible demand orders per time interval. For that purpose, a linear programming model is implemented whose objective function maximizes the daily social welfare following the balance and the demand side management constraints. A test case over 24 hours shows three strategies through a new price order. These strategies are as follows: the new price order is equal to, higher or lower than the price of the original demand order. Some conclusions are also drawn with respect to the social welfare and the consequences for the suppliers.","PeriodicalId":334674,"journal":{"name":"2018 15th International Conference on the European Energy Market (EEM)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128598488","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 : 2018-06-01DOI: 10.1109/EEM.2018.8469766
M. Vasilyev
The paper develops a capacity market model for dispersed electric power systems (EPS) characterized by long distances and low transfer capabilities of transmission lines. The model includes discrete optimization of an optimal generation set considering network limitations. Potential competition and generation development are integrated into the model. Forming investment price signals is discussed as far as the capacity price is not calculated by the discrete market model. The developed model provides nodal generation investment signals depending on existing power plants, network transfer capabilities and possible generation projects. Additionally network development is considered from the viewpoint of total fixed costs of the power plants included into the optimal generation set. An example of a simple abstract 14-node EPS is used to illustrate how the model works.
{"title":"Combined Generation and Transmission Capacity Market Model for Dispersed Systems","authors":"M. Vasilyev","doi":"10.1109/EEM.2018.8469766","DOIUrl":"https://doi.org/10.1109/EEM.2018.8469766","url":null,"abstract":"The paper develops a capacity market model for dispersed electric power systems (EPS) characterized by long distances and low transfer capabilities of transmission lines. The model includes discrete optimization of an optimal generation set considering network limitations. Potential competition and generation development are integrated into the model. Forming investment price signals is discussed as far as the capacity price is not calculated by the discrete market model. The developed model provides nodal generation investment signals depending on existing power plants, network transfer capabilities and possible generation projects. Additionally network development is considered from the viewpoint of total fixed costs of the power plants included into the optimal generation set. An example of a simple abstract 14-node EPS is used to illustrate how the model works.","PeriodicalId":334674,"journal":{"name":"2018 15th International Conference on the European Energy Market (EEM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130320496","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 : 2018-06-01DOI: 10.1109/EEM.2018.8469967
Ziming Mal, H. Zhong, Jianxiao Wang, Ershun Du, Q. Xia
Reserve resources shortage has occurred with the increasing penetration of renewable energy. To share reserve resources and improve operation reliability of interconnected power grids, a reserve sharing mechanism based on block chain is proposed. Probabilistic forecasting scenarios are used to depict stochastic wind and solar generation. Renewable energy curtailment, unserved demand and reserve shortage are considered in the system operation cost. Then Shapley values are calculated as the settlement for external market participants to remunerate reserve capacity, which evaluate the values of the shared reserve resources to the interconnected power grid. Block chain technology is first adopted in reserve sharing for practical implementation to build trust among market participants. Case studies based on the IEEE 57-bus system validate the effectiveness of the proposed mechanism and models.
{"title":"The Reserve Sharing Mechanism Among Interconnected Power Grids Based on Block Chain","authors":"Ziming Mal, H. Zhong, Jianxiao Wang, Ershun Du, Q. Xia","doi":"10.1109/EEM.2018.8469967","DOIUrl":"https://doi.org/10.1109/EEM.2018.8469967","url":null,"abstract":"Reserve resources shortage has occurred with the increasing penetration of renewable energy. To share reserve resources and improve operation reliability of interconnected power grids, a reserve sharing mechanism based on block chain is proposed. Probabilistic forecasting scenarios are used to depict stochastic wind and solar generation. Renewable energy curtailment, unserved demand and reserve shortage are considered in the system operation cost. Then Shapley values are calculated as the settlement for external market participants to remunerate reserve capacity, which evaluate the values of the shared reserve resources to the interconnected power grid. Block chain technology is first adopted in reserve sharing for practical implementation to build trust among market participants. Case studies based on the IEEE 57-bus system validate the effectiveness of the proposed mechanism and models.","PeriodicalId":334674,"journal":{"name":"2018 15th International Conference on the European Energy Market (EEM)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124206139","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 : 2018-06-01DOI: 10.1109/EEM.2018.8470006
Grzegorz Dudek, A. Gawlak, Mirosław Kornatka, J. Szkutnik
There are no proven systems on the market that deal with the detection of illegal electricity consumption. The AMI system gives new possibilities in this area. Based on the network configuration data, electric energy consumption and voltage values at the customer connection point (in phases), the analysis of electricity consumption was carried out. For the analyzed place in the network, the current was calculated from the voltage drop and the current resulting from the consumption of electricity. If the current determined from the voltage drop is greater than the current determined from the electricity consumption, it means that in relation to the recipient connected at a given point in the network, suspicion of illegal electricity consumption may be suspected.
{"title":"The Method of Detecting Illegal Electricity Consumption Using the AMI System","authors":"Grzegorz Dudek, A. Gawlak, Mirosław Kornatka, J. Szkutnik","doi":"10.1109/EEM.2018.8470006","DOIUrl":"https://doi.org/10.1109/EEM.2018.8470006","url":null,"abstract":"There are no proven systems on the market that deal with the detection of illegal electricity consumption. The AMI system gives new possibilities in this area. Based on the network configuration data, electric energy consumption and voltage values at the customer connection point (in phases), the analysis of electricity consumption was carried out. For the analyzed place in the network, the current was calculated from the voltage drop and the current resulting from the consumption of electricity. If the current determined from the voltage drop is greater than the current determined from the electricity consumption, it means that in relation to the recipient connected at a given point in the network, suspicion of illegal electricity consumption may be suspected.","PeriodicalId":334674,"journal":{"name":"2018 15th International Conference on the European Energy Market (EEM)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123454204","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}
This paper describes a multistage stochastic mixed integer programming problem for a hydro power producer that maximizes profit in the low liquid intraday market and balancing market. A comprehensive modelling framework with an internal rolling horizon is presented and the continuous intraday market is modelled using stochastic residual demand curves.
{"title":"Stochastic Multistage Bidding Optimisation in an Intraday Market with Limited Liquidity","authors":"Edda Engmark, Hanne Sandven, Stein-Erik Fleten, Gro Klæboe","doi":"10.1109/EEM.2018.8469997","DOIUrl":"https://doi.org/10.1109/EEM.2018.8469997","url":null,"abstract":"This paper describes a multistage stochastic mixed integer programming problem for a hydro power producer that maximizes profit in the low liquid intraday market and balancing market. A comprehensive modelling framework with an internal rolling horizon is presented and the continuous intraday market is modelled using stochastic residual demand curves.","PeriodicalId":334674,"journal":{"name":"2018 15th International Conference on the European Energy Market (EEM)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121408880","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 : 2018-06-01DOI: 10.1109/EEM.2018.8469963
L. Szabó, A. Mezősi, Z. Pató, E. Kácsor, A. Kelemen, G. Resch, L. Liebmann
Three long term power market scenarios are used in the SEERMAP project to analyse the energy transition options for the SEE region. A deep ‘decarbonisation’ scenario can be measured and compared to a ‘no target’ scenario, with no explicit CO2and renewable targets, and a ‘delayed action’ scenario when targets are set later in the time period. The main drivers of these scenarios are the increasing RES deployment levels and the carbon pricing scheme, assumed to be introduced in 2030 for the non-EU countries of the region. The results highlight the strong decarbonisation potential in the region resulting from high RES potential. In the decarbonisation scenarios for most West Balkan countries, gas assumes a transitory role.
{"title":"South East Europe Electricity Roadmap (SEERMAP)","authors":"L. Szabó, A. Mezősi, Z. Pató, E. Kácsor, A. Kelemen, G. Resch, L. Liebmann","doi":"10.1109/EEM.2018.8469963","DOIUrl":"https://doi.org/10.1109/EEM.2018.8469963","url":null,"abstract":"Three long term power market scenarios are used in the SEERMAP project to analyse the energy transition options for the SEE region. A deep ‘decarbonisation’ scenario can be measured and compared to a ‘no target’ scenario, with no explicit CO2and renewable targets, and a ‘delayed action’ scenario when targets are set later in the time period. The main drivers of these scenarios are the increasing RES deployment levels and the carbon pricing scheme, assumed to be introduced in 2030 for the non-EU countries of the region. The results highlight the strong decarbonisation potential in the region resulting from high RES potential. In the decarbonisation scenarios for most West Balkan countries, gas assumes a transitory role.","PeriodicalId":334674,"journal":{"name":"2018 15th International Conference on the European Energy Market (EEM)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128189533","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 : 2018-06-01DOI: 10.1109/EEM.2018.8469770
Nicolas Thie, Lukas Kloibhofer
To increase economic efficiency of distributed energy resources, the political demand for stronger market integration has intensified across European market areas. In contrast to subsidy based, fixed feed-in tariffs, direct marketing is subject to market risks. These risks are caused by forecasting uncertainties of both intermittent generation and spot market prices. The specifics of different European markets can increase or reduce risks. Aggregating DER to a Virtual Power Plant (VPP) helps to comply with market requirements. Additionally, a systematic use of the available trading options by the VPP operator can be used as risk management. The complexity of market frameworks, trading options and generation technologies within a VPP, makes a detailed market scheduling necessary. Therefore, this paper proposes a stochastic scheduling process, which considers both the expected revenue and market risk in the optimization. The method is applied to various European markets and the influence on risks is evaluated.
{"title":"Influence of European Market Frameworks on Market Participation and Risk Management of Virtual Power Plants","authors":"Nicolas Thie, Lukas Kloibhofer","doi":"10.1109/EEM.2018.8469770","DOIUrl":"https://doi.org/10.1109/EEM.2018.8469770","url":null,"abstract":"To increase economic efficiency of distributed energy resources, the political demand for stronger market integration has intensified across European market areas. In contrast to subsidy based, fixed feed-in tariffs, direct marketing is subject to market risks. These risks are caused by forecasting uncertainties of both intermittent generation and spot market prices. The specifics of different European markets can increase or reduce risks. Aggregating DER to a Virtual Power Plant (VPP) helps to comply with market requirements. Additionally, a systematic use of the available trading options by the VPP operator can be used as risk management. The complexity of market frameworks, trading options and generation technologies within a VPP, makes a detailed market scheduling necessary. Therefore, this paper proposes a stochastic scheduling process, which considers both the expected revenue and market risk in the optimization. The method is applied to various European markets and the influence on risks is evaluated.","PeriodicalId":334674,"journal":{"name":"2018 15th International Conference on the European Energy Market (EEM)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131455155","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 : 2018-06-01DOI: 10.1109/EEM.2018.8469994
Dawid Chudy
This paper presents the implementation of the energy storage for unit commitment and dispatch of conventional power plants. The optimization employs Mixed Integer Linear Programming. The simulations with different scenarios have been carried out to demonstrate the effectiveness of the approach applied. The results obtained indicated that start-up energy of conventional power plants may impose the specific operation of energy storage systems. Cost benefits of energy storage implementation are also demonstrated.
{"title":"Energy Storage Systems for Commitment and Dispatch of Conventional Power Plants","authors":"Dawid Chudy","doi":"10.1109/EEM.2018.8469994","DOIUrl":"https://doi.org/10.1109/EEM.2018.8469994","url":null,"abstract":"This paper presents the implementation of the energy storage for unit commitment and dispatch of conventional power plants. The optimization employs Mixed Integer Linear Programming. The simulations with different scenarios have been carried out to demonstrate the effectiveness of the approach applied. The results obtained indicated that start-up energy of conventional power plants may impose the specific operation of energy storage systems. Cost benefits of energy storage implementation are also demonstrated.","PeriodicalId":334674,"journal":{"name":"2018 15th International Conference on the European Energy Market (EEM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130149535","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 : 2018-06-01DOI: 10.1109/EEM.2018.8469837
J. Zupancic, E. Lakić, T. Medved, A. Gubina
The installation of new smart grid technologies brings additional possibilities for power system operation. Among those technologies, energy storage promises to support energy transition towards a system with a high share of renewable energy sources. The paper outlines the results of the large-scale simulation in the distribution grid obtained within Horizon 2020 project STORY. Due to the characteristics of the modelled network, a stochastic Monte Carlo simulation approach is used for the network simulation with Matlab and OpenDSS software. The real-world database was tuned for Central European region and daily power flow simulations were performed for all four seasons. The impact of the storage was compared, based on the installed capacity in the network and in combination with different technology drivers. The results confirmed that the integration of battery storage devices has a considerable positive impact on the power system but there are still many challenges awaiting in the near future.
{"title":"Analysis of Large Scale Storage Impact on Distribution Network","authors":"J. Zupancic, E. Lakić, T. Medved, A. Gubina","doi":"10.1109/EEM.2018.8469837","DOIUrl":"https://doi.org/10.1109/EEM.2018.8469837","url":null,"abstract":"The installation of new smart grid technologies brings additional possibilities for power system operation. Among those technologies, energy storage promises to support energy transition towards a system with a high share of renewable energy sources. The paper outlines the results of the large-scale simulation in the distribution grid obtained within Horizon 2020 project STORY. Due to the characteristics of the modelled network, a stochastic Monte Carlo simulation approach is used for the network simulation with Matlab and OpenDSS software. The real-world database was tuned for Central European region and daily power flow simulations were performed for all four seasons. The impact of the storage was compared, based on the installed capacity in the network and in combination with different technology drivers. The results confirmed that the integration of battery storage devices has a considerable positive impact on the power system but there are still many challenges awaiting in the near future.","PeriodicalId":334674,"journal":{"name":"2018 15th International Conference on the European Energy Market (EEM)","volume":"324 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133831763","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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