Pub Date : 2017-06-01DOI: 10.1109/EEM.2017.7981871
Gilles Bertrand, A. Papavasiliou
At present, wind power producers (WPP) are paid following feed-in tariffs in Belgium. This system will come to an end soon due to its high cost and the producers will have to bid in the day-ahead market. As wind owners cannot forecast their production perfectly, they will face imbalance costs or revenues. Imbalance price forecasting is therefore a critical problem. In this paper, we implement a machine learning model to assess the usefulness of introducing exogenous variables in imbalance price forecasting. This method shows improved results compared to classical methods. Since the imbalance price is obtained by the marginal cost of producing the missing energy, the strategic behaviour of a WPP will influence the imbalance price. In this paper, we propose a way to represent this influence as well as a formulation of a model to obtain the optimal bidding strategy in that situation. This model has been cast as a convex quadratic program that can readily be solved using a commercial solver.
{"title":"Optimal dispatch of wind farms facing market prices","authors":"Gilles Bertrand, A. Papavasiliou","doi":"10.1109/EEM.2017.7981871","DOIUrl":"https://doi.org/10.1109/EEM.2017.7981871","url":null,"abstract":"At present, wind power producers (WPP) are paid following feed-in tariffs in Belgium. This system will come to an end soon due to its high cost and the producers will have to bid in the day-ahead market. As wind owners cannot forecast their production perfectly, they will face imbalance costs or revenues. Imbalance price forecasting is therefore a critical problem. In this paper, we implement a machine learning model to assess the usefulness of introducing exogenous variables in imbalance price forecasting. This method shows improved results compared to classical methods. Since the imbalance price is obtained by the marginal cost of producing the missing energy, the strategic behaviour of a WPP will influence the imbalance price. In this paper, we propose a way to represent this influence as well as a formulation of a model to obtain the optimal bidding strategy in that situation. This model has been cast as a convex quadratic program that can readily be solved using a commercial solver.","PeriodicalId":416082,"journal":{"name":"2017 14th International Conference on the European Energy Market (EEM)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114143126","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 : 2017-06-01DOI: 10.1109/EEM.2017.7981985
Smita Lokhande, Vishnu P. Menon, Y. Bichpuriya
In the new era of electrical power industry with more emphasis on green energy resources and active customer participation, the distribution utilities (DISCOMs) are being challenged. Being an important link between wholesale and retail electricity markets, these DISCOMs are exposed to risks on both sides. Under such circumstances, they are looking for new analytics to optimize operations and maximize profits. Load forecasting is one such predictive analytics used by DISCOMs to minimize risks. With increasing level of penetration of intermittent wind and solar energy in the generation at bulk as well as distributed level, both supply and demand have become uncertain. With certain benefits and incentives offered to the customers, demand can be made flexible and controllable in nature. Such flexible demand can help in minimizing the demand supply gap. Also the response of load is faster than the conventional generation resources which have machine inertia. Flexible demand is thus one of vital feature of future grid. Demand Response (DR) can be considered as a way to utilize this flexibility of load by adjusting the consumption profile thus assisting in dealing with the increased uncertainty and improving the power system operational efficiency. With the DR programs implemented, the DISCOMs will now have to forecast not only the demand of electricity but the net demand adjusted after accommodating demand response. In this paper, we analyse the impact of DR on the net demand profile of DISCOM considering the end consumers with varying demand profiles and varying preferences. We propose a new approach to forecast demand with modelling of the DR. The proposed approach gives a Probability Density Forecast (PDF) of demand using a non-parametric approach based on Kernel Density Estimation (KDE). The proposed model will help DISCOMs for developing demand bidding strategies in a market where DR programs are being implemented.
{"title":"Modelling of demand response for utility's loac forecasting","authors":"Smita Lokhande, Vishnu P. Menon, Y. Bichpuriya","doi":"10.1109/EEM.2017.7981985","DOIUrl":"https://doi.org/10.1109/EEM.2017.7981985","url":null,"abstract":"In the new era of electrical power industry with more emphasis on green energy resources and active customer participation, the distribution utilities (DISCOMs) are being challenged. Being an important link between wholesale and retail electricity markets, these DISCOMs are exposed to risks on both sides. Under such circumstances, they are looking for new analytics to optimize operations and maximize profits. Load forecasting is one such predictive analytics used by DISCOMs to minimize risks. With increasing level of penetration of intermittent wind and solar energy in the generation at bulk as well as distributed level, both supply and demand have become uncertain. With certain benefits and incentives offered to the customers, demand can be made flexible and controllable in nature. Such flexible demand can help in minimizing the demand supply gap. Also the response of load is faster than the conventional generation resources which have machine inertia. Flexible demand is thus one of vital feature of future grid. Demand Response (DR) can be considered as a way to utilize this flexibility of load by adjusting the consumption profile thus assisting in dealing with the increased uncertainty and improving the power system operational efficiency. With the DR programs implemented, the DISCOMs will now have to forecast not only the demand of electricity but the net demand adjusted after accommodating demand response. In this paper, we analyse the impact of DR on the net demand profile of DISCOM considering the end consumers with varying demand profiles and varying preferences. We propose a new approach to forecast demand with modelling of the DR. The proposed approach gives a Probability Density Forecast (PDF) of demand using a non-parametric approach based on Kernel Density Estimation (KDE). The proposed model will help DISCOMs for developing demand bidding strategies in a market where DR programs are being implemented.","PeriodicalId":416082,"journal":{"name":"2017 14th International Conference on the European Energy Market (EEM)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134647056","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 : 2017-06-01DOI: 10.1109/EEM.2017.7981965
Judith Litzenburger
In an energy system where the share of renewable energies is increasing, the shape of Ancillary Service needs to change. Due to the weather dependency of wind and solar power the system has to be able to react in two ways. Fast, in cases of unforeseen changes on the supply side and long-term in times where there is not enough wind and sun available to cover the load during a period. So the value of flexibility as an Ancillary Service rises. Today the Energy Only Market (EOM) hardly provides a market for flexibility, but business cases for such Ancillary Services will be crucial for the upcoming system. Focusing on Demand Side Management the essay analyses how a market for this kind of Ancillary Service could be designed. It is based on the study “Demand Side Management in North Rhine-Westphalia: Potentials, Obstacles and Options for Action” [1].
{"title":"Ancillary services: Between the need for a market and decentral business cases","authors":"Judith Litzenburger","doi":"10.1109/EEM.2017.7981965","DOIUrl":"https://doi.org/10.1109/EEM.2017.7981965","url":null,"abstract":"In an energy system where the share of renewable energies is increasing, the shape of Ancillary Service needs to change. Due to the weather dependency of wind and solar power the system has to be able to react in two ways. Fast, in cases of unforeseen changes on the supply side and long-term in times where there is not enough wind and sun available to cover the load during a period. So the value of flexibility as an Ancillary Service rises. Today the Energy Only Market (EOM) hardly provides a market for flexibility, but business cases for such Ancillary Services will be crucial for the upcoming system. Focusing on Demand Side Management the essay analyses how a market for this kind of Ancillary Service could be designed. It is based on the study “Demand Side Management in North Rhine-Westphalia: Potentials, Obstacles and Options for Action” [1].","PeriodicalId":416082,"journal":{"name":"2017 14th International Conference on the European Energy Market (EEM)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133928266","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 : 2017-06-01DOI: 10.1109/EEM.2017.7981939
D. Scholz, F. Müsgens
Currently, most distribution system operators in Germany estimate non-real-time metered consumption profiles based on “Standard Load Profiles” developed in the late 1990s by the German Association of Energy and Water Industries. However, as both consumption behavior and consumer structure change over time, their predictive power may have deteriorated. In addition, they do not account for regional differences within Germany. Therefore, we compared their forecasting accuracy with two newly developed alternative standard load profiles, differentiating between households and commercial enterprises. We calculated the new profiles based on regional, more up-to-date aggregated consumption data and a limited set of smart meter data. Furthermore, we varied the number of seasons and day types included in the profiles. A comparison of our new load profiles with the existing Standard Load Profiles revealed significant improvements in forecasting accuracy. Improvements are mainly resulting from improved input data (regional and more recent data set), but the utilization of smart meter data as well as variations in day types and seasons also reduced forecast errors.
{"title":"How to improve standard load profiles: Updating, regionalization and smart meter data","authors":"D. Scholz, F. Müsgens","doi":"10.1109/EEM.2017.7981939","DOIUrl":"https://doi.org/10.1109/EEM.2017.7981939","url":null,"abstract":"Currently, most distribution system operators in Germany estimate non-real-time metered consumption profiles based on “Standard Load Profiles” developed in the late 1990s by the German Association of Energy and Water Industries. However, as both consumption behavior and consumer structure change over time, their predictive power may have deteriorated. In addition, they do not account for regional differences within Germany. Therefore, we compared their forecasting accuracy with two newly developed alternative standard load profiles, differentiating between households and commercial enterprises. We calculated the new profiles based on regional, more up-to-date aggregated consumption data and a limited set of smart meter data. Furthermore, we varied the number of seasons and day types included in the profiles. A comparison of our new load profiles with the existing Standard Load Profiles revealed significant improvements in forecasting accuracy. Improvements are mainly resulting from improved input data (regional and more recent data set), but the utilization of smart meter data as well as variations in day types and seasons also reduced forecast errors.","PeriodicalId":416082,"journal":{"name":"2017 14th International Conference on the European Energy Market (EEM)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122246594","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 : 2017-06-01DOI: 10.1109/EEM.2017.7981919
B. Burgholzer
High shares of renewable electricity generation requires robust balancing measures and procedures in the electricity system. There are several electricity balancing pilot projects having already been started or will start in the near future. The work presented in this paper focuses on projects with the geographic scope of Central Europe. This includes the common activation of automatic Frequency Restoration Reserve (aFRR) in Austria and Germany as well as the common procurement of aFRR in the above-mentioned area, which is planned to start mid-2017. The start for common procurement and activation of manually activated Frequency Restoration Reserve (mFRR) has not yet been published, but will also be analysed within this work. In addition, the impact of a further extension of the common balancing area to Belgium and The Netherlands is analysed. The focus of the study is on how common procurement of aFRR and mFRR influences wholesale electricity market clearings and how it interferes each other. The quantitative results confirm that common procurement of balancing capacity (aFRR and mFRR) in the simulated region has significant advantages in terms of cost reduction, CO2 emissions and increased flexibility in the electricity system. Furthermore, the common procurement of mFRR interferes the procurement costs of aFRR in a positive way, meaning that further reductions can be achieved.
{"title":"Interdependencies of harmonised procurement of manually and automatically activated FRR in selected Central European balancing markets","authors":"B. Burgholzer","doi":"10.1109/EEM.2017.7981919","DOIUrl":"https://doi.org/10.1109/EEM.2017.7981919","url":null,"abstract":"High shares of renewable electricity generation requires robust balancing measures and procedures in the electricity system. There are several electricity balancing pilot projects having already been started or will start in the near future. The work presented in this paper focuses on projects with the geographic scope of Central Europe. This includes the common activation of automatic Frequency Restoration Reserve (aFRR) in Austria and Germany as well as the common procurement of aFRR in the above-mentioned area, which is planned to start mid-2017. The start for common procurement and activation of manually activated Frequency Restoration Reserve (mFRR) has not yet been published, but will also be analysed within this work. In addition, the impact of a further extension of the common balancing area to Belgium and The Netherlands is analysed. The focus of the study is on how common procurement of aFRR and mFRR influences wholesale electricity market clearings and how it interferes each other. The quantitative results confirm that common procurement of balancing capacity (aFRR and mFRR) in the simulated region has significant advantages in terms of cost reduction, CO2 emissions and increased flexibility in the electricity system. Furthermore, the common procurement of mFRR interferes the procurement costs of aFRR in a positive way, meaning that further reductions can be achieved.","PeriodicalId":416082,"journal":{"name":"2017 14th International Conference on the European Energy Market (EEM)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124173389","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 : 2017-06-01DOI: 10.1109/EEM.2017.7982013
E. F. B⊘dal, M. Korpås
Some of the best wind and natural gas resources in Norway are located in rural areas. Hydrogen can be produced from natural gas in combination with carbon capture and storage to utilize the natural gas resources without significant CO2-emissions. The hydrogen can be liquefied and transported to regions with energy deficits. This creates a demand for hydrogen produced from electrolysis of water, which facilitates wind power development without requiring large investments in new transmission capacity. A regional optimization model is developed and used to investigate sizing of the electrolyser capacity and hydrogen storage, as well as regional effects of producing hydrogen from electrolysis. In the model, the transmission grid is represented by dc power flow equations and opportunities for wind power investments in the region are included. The model is used in a case study which shows that hydrogen storage contributes to significantly increase grid utilization, even with small amounts of storage. Increased regional transmission capacity results in more wind power development compared to increased capacity towards the central grid. Hydrogen storage is only profitable to reduce congestion in this deterministic model, thus using hydrogen storage to reduce the costs in the spot market is not profitable.
{"title":"Regional effects of hydrogen production in congested transmission grids with wind and hydro power","authors":"E. F. B⊘dal, M. Korpås","doi":"10.1109/EEM.2017.7982013","DOIUrl":"https://doi.org/10.1109/EEM.2017.7982013","url":null,"abstract":"Some of the best wind and natural gas resources in Norway are located in rural areas. Hydrogen can be produced from natural gas in combination with carbon capture and storage to utilize the natural gas resources without significant CO2-emissions. The hydrogen can be liquefied and transported to regions with energy deficits. This creates a demand for hydrogen produced from electrolysis of water, which facilitates wind power development without requiring large investments in new transmission capacity. A regional optimization model is developed and used to investigate sizing of the electrolyser capacity and hydrogen storage, as well as regional effects of producing hydrogen from electrolysis. In the model, the transmission grid is represented by dc power flow equations and opportunities for wind power investments in the region are included. The model is used in a case study which shows that hydrogen storage contributes to significantly increase grid utilization, even with small amounts of storage. Increased regional transmission capacity results in more wind power development compared to increased capacity towards the central grid. Hydrogen storage is only profitable to reduce congestion in this deterministic model, thus using hydrogen storage to reduce the costs in the spot market is not profitable.","PeriodicalId":416082,"journal":{"name":"2017 14th International Conference on the European Energy Market (EEM)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130242734","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 : 2017-06-01DOI: 10.1109/EEM.2017.7981943
A. Kowalska-Pyzalska
In the paper the consumers' willingness to pay (WTP) for green energy is discussed. Based on the literature review and the findings from the pilot study a simple agent-based model in Netlogo is created to examine the development of the WTP towards renewables (RES) among consumers. The model shows that to increase positive appraisal of green energy and hence encourage consumers to support the development of RES, some external incentives are necessary. Hence, promoting advantages of renewables and making consumers more familiar with them, as well as offering some financial support may play a great role.
{"title":"Willingess to pay for green energy: An agent-based model in NetLogo platform","authors":"A. Kowalska-Pyzalska","doi":"10.1109/EEM.2017.7981943","DOIUrl":"https://doi.org/10.1109/EEM.2017.7981943","url":null,"abstract":"In the paper the consumers' willingness to pay (WTP) for green energy is discussed. Based on the literature review and the findings from the pilot study a simple agent-based model in Netlogo is created to examine the development of the WTP towards renewables (RES) among consumers. The model shows that to increase positive appraisal of green energy and hence encourage consumers to support the development of RES, some external incentives are necessary. Hence, promoting advantages of renewables and making consumers more familiar with them, as well as offering some financial support may play a great role.","PeriodicalId":416082,"journal":{"name":"2017 14th International Conference on the European Energy Market (EEM)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127924881","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 : 2017-06-01DOI: 10.1109/EEM.2017.7981983
J. Michaelis, T. Müller, U. Reiter, F. Fermi, A. Wyrwa, Yi-kuang Chen, Christoph Zöphel, Nicolas Kronthaler, Rainer Elsland
The electricity supply will become more volatile in energy systems with increasing shares of Renewable Energy Sources (RES). Since electricity demand varies as does the supply by RES, the remaining residual load must be covered by flexible technologies that are required to balance the different types of fluctuations. In this study, these flexibility options are divided into three categories: increasing the residual load, decreasing the residual load and shifting the electricity demand / supply temporally or spatially. Furthermore, typical technological options are discussed for each category, and four flexibility criteria are used to compare their technical and economic characteristics. These include the activation time, duration of flexibility provision, number of activations and activation costs. The study reveals that various options exist and no one technology dominates. However, within the flexibility categories, it can be shown that some appliances have advantages in three of the four categories compared to the other options. Ultimately, the choice of the most appropriate flexibility option depends on the requirements of the energy system. It can be concluded that a mix of technologies will be needed to cover the future flexible demand that may include short-term changes of the residual load as well as long-term downturns of RES generation.
{"title":"Comparison of the techno-economic characteristics of different flexibility options in the European energy system","authors":"J. Michaelis, T. Müller, U. Reiter, F. Fermi, A. Wyrwa, Yi-kuang Chen, Christoph Zöphel, Nicolas Kronthaler, Rainer Elsland","doi":"10.1109/EEM.2017.7981983","DOIUrl":"https://doi.org/10.1109/EEM.2017.7981983","url":null,"abstract":"The electricity supply will become more volatile in energy systems with increasing shares of Renewable Energy Sources (RES). Since electricity demand varies as does the supply by RES, the remaining residual load must be covered by flexible technologies that are required to balance the different types of fluctuations. In this study, these flexibility options are divided into three categories: increasing the residual load, decreasing the residual load and shifting the electricity demand / supply temporally or spatially. Furthermore, typical technological options are discussed for each category, and four flexibility criteria are used to compare their technical and economic characteristics. These include the activation time, duration of flexibility provision, number of activations and activation costs. The study reveals that various options exist and no one technology dominates. However, within the flexibility categories, it can be shown that some appliances have advantages in three of the four categories compared to the other options. Ultimately, the choice of the most appropriate flexibility option depends on the requirements of the energy system. It can be concluded that a mix of technologies will be needed to cover the future flexible demand that may include short-term changes of the residual load as well as long-term downturns of RES generation.","PeriodicalId":416082,"journal":{"name":"2017 14th International Conference on the European Energy Market (EEM)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117172288","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 : 2017-06-01DOI: 10.1109/EEM.2017.7981872
V. V. Vadlamudi, G. Doorman
In countries with Capacity Mechanisms in place, where Explicit Interconnector Participation model is to be used, one of the key market design questions to be answered is how the amount of interconnector capacity that is allowed to participate in the auctions should be determined. This paper argues for an interconnector capacity de-rating approach. In order for the de-rating factor to be representative of stochasticity inherent in the system, the concept of Interconnector Effective Load Carrying Capability is postulated in this paper. A method with probabilistic basis that allows for converting the name-plate capacity of a transmission line connecting two areas into a de-rated capacity is proposed. The proposed probabilistic methodology takes into account the technical availability of the line and captures the impact of simultaneous or co-incident scarcity. A simple case-study is presented to exemplify the proposed principle and methodology.
{"title":"Interconnector participation in capacity mechanisms: A new de-rating approach","authors":"V. V. Vadlamudi, G. Doorman","doi":"10.1109/EEM.2017.7981872","DOIUrl":"https://doi.org/10.1109/EEM.2017.7981872","url":null,"abstract":"In countries with Capacity Mechanisms in place, where Explicit Interconnector Participation model is to be used, one of the key market design questions to be answered is how the amount of interconnector capacity that is allowed to participate in the auctions should be determined. This paper argues for an interconnector capacity de-rating approach. In order for the de-rating factor to be representative of stochasticity inherent in the system, the concept of Interconnector Effective Load Carrying Capability is postulated in this paper. A method with probabilistic basis that allows for converting the name-plate capacity of a transmission line connecting two areas into a de-rated capacity is proposed. The proposed probabilistic methodology takes into account the technical availability of the line and captures the impact of simultaneous or co-incident scarcity. A simple case-study is presented to exemplify the proposed principle and methodology.","PeriodicalId":416082,"journal":{"name":"2017 14th International Conference on the European Energy Market (EEM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115075207","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 : 2017-06-01DOI: 10.1109/EEM.2017.7982008
Samuel Glismann, F. Nobel
In a fast changing electrical power sector the design of ancillary services is challenged and policy makers are required to take decisions on the adjustment of current ancillary services practices and on the introduction of new ancillary services. Even though ancillary services are crucial for the reliability of unbundled power systems, current literature does not provide a structured approach to describe and compare the design of different ancillary services. We propose a generic framework for ancillary service designs that allows for a comparative ancillary service assessment as a first step towards a comprehensive evaluation framework. Applicability of the framework and its generic design variables is shown by comparing ancillary services of different objectives and different regulatory areas.
{"title":"A framework for ancillary services design","authors":"Samuel Glismann, F. Nobel","doi":"10.1109/EEM.2017.7982008","DOIUrl":"https://doi.org/10.1109/EEM.2017.7982008","url":null,"abstract":"In a fast changing electrical power sector the design of ancillary services is challenged and policy makers are required to take decisions on the adjustment of current ancillary services practices and on the introduction of new ancillary services. Even though ancillary services are crucial for the reliability of unbundled power systems, current literature does not provide a structured approach to describe and compare the design of different ancillary services. We propose a generic framework for ancillary service designs that allows for a comparative ancillary service assessment as a first step towards a comprehensive evaluation framework. Applicability of the framework and its generic design variables is shown by comparing ancillary services of different objectives and different regulatory areas.","PeriodicalId":416082,"journal":{"name":"2017 14th International Conference on the European Energy Market (EEM)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127506968","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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