Najibi, F.; Najibi, F.
Harvested from ORCID Public Data FileNajibi, F. in OpenAIRE Alonso, E.; Alonso, E.
Harvested from ORCID Public Data FileAlonso, E. in OpenAIRE
Apostolopoulou, D.; Apostolopoulou, D.
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesApostolopoulou, D. in OpenAIREIn this paper, we propose an optimal dispatch scheme for a pumped storage hydro cascade that maximizes the energy per cubic meter of water in the system taking into account uncertainty in the net load variations. To this end, we introduce a model to describe the behaviour of a pumped storage hydro cascade and formulate its optimal dispatch. We then incorporate forecast scenarios in the optimal dispatch, and define a robust variant of the developed system. The resulting optimization problem is intractable due to the infinite number of constraints. Using tools from robust optimization, we reformulate the resulting problem in a tractable form that is amenable to existing numerical tools and show that the computed dispatch is immunised against uncertainty. The efficacy of the proposed approach is demonstrated by means of a realistic case study based on the Seven Forks system located in Kenya.
Access RoutesGreen 2 citations 2 popularity Average influence Average impulse Average 
Powered by BIP!add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.<script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1109/control.2018.8516823&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu- Najibi, F.;
Najibi, F.
Harvested from ORCID Public Data FileNajibi, F. in OpenAIRE Alonso, E.; Alonso, E.
Harvested from ORCID Public Data FileAlonso, E. in OpenAIRE Apostolopoulou, D.; Apostolopoulou, D.
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesApostolopoulou, D. in OpenAIREIn this paper, we propose an optimal dispatch scheme for a pumped storage hydro cascade that maximizes the energy per cubic meter of water in the system taking into account uncertainty in the net load variations. To this end, we introduce a model to describe the behaviour of a pumped storage hydro cascade and formulate its optimal dispatch. We then incorporate forecast scenarios in the optimal dispatch, and define a robust variant of the developed system. The resulting optimization problem is intractable due to the infinite number of constraints. Using tools from robust optimization, we reformulate the resulting problem in a tractable form that is amenable to existing numerical tools and show that the computed dispatch is immunised against uncertainty. The efficacy of the proposed approach is demonstrated by means of a realistic case study based on the Seven Forks system located in Kenya.
Access RoutesGreen 2 citations 2 popularity Average influence Average impulse Average Powered by BIP!add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.<script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1109/control.2018.8516823&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu - Matthew Deakin;
Matthew Deakin
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesMatthew Deakin in OpenAIRE Thomas Morstyn; Thomas Morstyn
Harvested from ORCID Public Data FileThomas Morstyn in OpenAIRE Dimitra Apostolopoulou; Malcolm D McCulloch;Dimitra Apostolopoulou
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesDimitra Apostolopoulou in OpenAIREAbstractDistributed Generators that use reactive power for voltage control in distribution networks reduce renewable curtailment but can significantly increase network losses, undermining the effectiveness of this control. This paper proposes Voltage Control Loss Factors (VCLFs) as a means of understanding the interactions between reactive power flows, losses and curtailment, focusing on commercial‐scale generators in radial systems. The metric uses a substitution‐based method, whereby a system with voltage control is compared against a counterfactual with no such control. The proposed method studies this metric by coupling numerically precise black‐box simulations with analytic results from a Two‐Bus network representation. The latter provides a physical explanation for the numerical simulation results in terms of power, voltage and impedance parameters, providing clear explainability which is absent in traditional approaches for determining distribution loss factors. The whole solution space of the Two‐Bus system is explored, and VCLFs are calculated for six cases on three unbalanced test networks to illustrate the approach. Relative losses as high as 30% are found in a system with high branch resistance‐reactance ratio and large voltage rise. The results have implications for the design of loss allocation algorithms in distribution networks, and the optimal sizing of power‐electronic interfaced Distributed Generators.
Access RoutesGreen gold Published in a Diamond OA journal 6 citations 6 popularity Top 10% influence Average impulse Top 10% Powered by BIP!add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.<script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1049/gtd2.12413&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu - Matthew Deakin;
Matthew Deakin
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesMatthew Deakin in OpenAIRE Thomas Morstyn; Thomas Morstyn
Harvested from ORCID Public Data FileThomas Morstyn in OpenAIRE Dimitra Apostolopoulou; Malcolm D McCulloch;Dimitra Apostolopoulou
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesDimitra Apostolopoulou in OpenAIREAbstractDistributed Generators that use reactive power for voltage control in distribution networks reduce renewable curtailment but can significantly increase network losses, undermining the effectiveness of this control. This paper proposes Voltage Control Loss Factors (VCLFs) as a means of understanding the interactions between reactive power flows, losses and curtailment, focusing on commercial‐scale generators in radial systems. The metric uses a substitution‐based method, whereby a system with voltage control is compared against a counterfactual with no such control. The proposed method studies this metric by coupling numerically precise black‐box simulations with analytic results from a Two‐Bus network representation. The latter provides a physical explanation for the numerical simulation results in terms of power, voltage and impedance parameters, providing clear explainability which is absent in traditional approaches for determining distribution loss factors. The whole solution space of the Two‐Bus system is explored, and VCLFs are calculated for six cases on three unbalanced test networks to illustrate the approach. Relative losses as high as 30% are found in a system with high branch resistance‐reactance ratio and large voltage rise. The results have implications for the design of loss allocation algorithms in distribution networks, and the optimal sizing of power‐electronic interfaced Distributed Generators.
Access RoutesGreen gold Published in a Diamond OA journal 6 citations 6 popularity Top 10% influence Average impulse Top 10% Powered by BIP!add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.<script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1049/gtd2.12413&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu - Crozier, C;
Crozier, C
Harvested from ORCID Public Data FileCrozier, C in OpenAIRE Apostolopoulou, D; Apostolopoulou, D
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesApostolopoulou, D in OpenAIRE McCulloch, M; McCulloch, M
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesMcCulloch, M in OpenAIREThe number of electric vehicles on the road in the UK is expected to rise quickly in the coming years, and this is likely to have an impact on the operation of the power grid. This paper first quantifies the consequences of allowing a completely electric fleet to charge freely, then considers whether there is a practical way in which the impacts can be mitigated. We predict that, with an entirely electric fleet, the UK power generation capacity would need to increase by 1/3. We show that it is possible to completely mitigate this with controlled charging, although substantial infrastructure would be required. However, we propose a simple scheme which could largely avoid the negative effect and does not require the creation of new infrastructure. We show that this reduces the projected increase in peak electricity demand by 80-99%.
Access RoutesGreen bronze 19 citations 19 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.<script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.enpol.2018.03.056&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu - Crozier, C;
Crozier, C
Harvested from ORCID Public Data FileCrozier, C in OpenAIRE Apostolopoulou, D; Apostolopoulou, D
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesApostolopoulou, D in OpenAIRE McCulloch, M; McCulloch, M
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesMcCulloch, M in OpenAIREThe number of electric vehicles on the road in the UK is expected to rise quickly in the coming years, and this is likely to have an impact on the operation of the power grid. This paper first quantifies the consequences of allowing a completely electric fleet to charge freely, then considers whether there is a practical way in which the impacts can be mitigated. We predict that, with an entirely electric fleet, the UK power generation capacity would need to increase by 1/3. We show that it is possible to completely mitigate this with controlled charging, although substantial infrastructure would be required. However, we propose a simple scheme which could largely avoid the negative effect and does not require the creation of new infrastructure. We show that this reduces the projected increase in peak electricity demand by 80-99%.
Access RoutesGreen bronze 19 citations 19 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.<script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.enpol.2018.03.056&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu - Apostolopoulou, D;
Apostolopoulou, D
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesApostolopoulou, D in OpenAIRE McCulloch, M; McCulloch, M
Harvested from ORCID Public Data FileMcCulloch, M in OpenAIREIn this paper we propose an optimal dispatch scheme for a cascaded hybrid hydro-solar power system, i.e., a hydroelectric system coupled with solar generation, that maximises the head levels of each dam, and minimises the spillage effects. As a result more water is stored in the dams to meet a given amount of energy providing more flexibility to the system in dry months. This dispatch scheme is based on the development of a simplified hydroelectric power system model which has low computational burden and may be implemented for the short-term operation of a cascaded hydro-solar hybrid power system. To this end, the nonconvex relationships that describe the system physical constraints, e.g., hydroelectric power output, are transformed into affine relationships; thus reducing the computational complexity. The transformations are based on the construction of convex envelopes around bilinear functions, piecewise affine functions, and exploitation of optimisation properties. We validate the proposed framework and quantify the benefits of coupling hydroelectric and solar resources in terms of live water volume in dams and amount of solar a system may withstand with the Tana river cascade located in Kenya through an analysis of incorporating actual system data.
Access RoutesGreen bronze 48 citations 48 popularity Top 1% influence Top 10% impulse Top 10% Powered by BIP!add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.<script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1109/tste.2018.2874810&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu - Apostolopoulou, D;
Apostolopoulou, D
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesApostolopoulou, D in OpenAIRE McCulloch, M; McCulloch, M
Harvested from ORCID Public Data FileMcCulloch, M in OpenAIREIn this paper we propose an optimal dispatch scheme for a cascaded hybrid hydro-solar power system, i.e., a hydroelectric system coupled with solar generation, that maximises the head levels of each dam, and minimises the spillage effects. As a result more water is stored in the dams to meet a given amount of energy providing more flexibility to the system in dry months. This dispatch scheme is based on the development of a simplified hydroelectric power system model which has low computational burden and may be implemented for the short-term operation of a cascaded hydro-solar hybrid power system. To this end, the nonconvex relationships that describe the system physical constraints, e.g., hydroelectric power output, are transformed into affine relationships; thus reducing the computational complexity. The transformations are based on the construction of convex envelopes around bilinear functions, piecewise affine functions, and exploitation of optimisation properties. We validate the proposed framework and quantify the benefits of coupling hydroelectric and solar resources in terms of live water volume in dams and amount of solar a system may withstand with the Tana river cascade located in Kenya through an analysis of incorporating actual system data.
Access RoutesGreen bronze 48 citations 48 popularity Top 1% influence Top 10% impulse Top 10% Powered by BIP!add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.<script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1109/tste.2018.2874810&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu - Apostolopoulou, D; De Grève, Z;
Apostolopoulou, D
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesApostolopoulou, D in OpenAIRE McCulloch, M; McCulloch, M
Harvested from ORCID Public Data FileMcCulloch, M in OpenAIREIn this paper, we propose an optimal dispatch scheme for a cascade hydroelectric power system that maximises the head levels of each dam, and minimises the spillage effects taking into account uncertainty in the net load variations, i.e., the difference between the load and the renewable resources, and inflows to the cascade. By maximising the head levels of each dam the volume of water stored, which is a metric of system resiliency, is maximised. In this regard, the operation of the cascade hydroelectric power system is robust to the variability and intermittency of renewable resources and increases system resilience to variations in climatic conditions. Thus, we demon- strate the benefits of coupling hydroelectric and photovoltaic resources. To this end, we introduce an approximate model for a cascade hydroelectric power system. We then develop correlated probabilistic forecasts for the uncertain output of renewable resources, e.g., solar generation, using historical data based on clustering and Markov chain techniques. We incorporate the gen- erated forecast scenarios in the optimal dispatch of the cascade hydroelectric power system, and define a robust variant of the developed system. However, the robust variant is intractable due to the infinite number of constraints. Using tools from robust optimisation, we reformulate the resulting problem in a tractable form that is amenable to existing numerical tools and show that the computed dispatch is immunised against uncertainty. The efficacy of the proposed approach is demonstrated by means of an actual case study involving the Seven Forks system located in Kenya, which consists of five cascaded hydroelectric power systems. With the case study we demonstrate that the Seven Forks system may be coupled with solar generation since the “price of robustness” is small; thus demonstrating the benefits of coupling hydroelectric systems with solar generation
Access RoutesGreen bronze 37 citations 37 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.<script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1109/tpwrs.2018.2807794&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu - Apostolopoulou, D; De Grève, Z;
Apostolopoulou, D
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesApostolopoulou, D in OpenAIRE McCulloch, M; McCulloch, M
Harvested from ORCID Public Data FileMcCulloch, M in OpenAIREIn this paper, we propose an optimal dispatch scheme for a cascade hydroelectric power system that maximises the head levels of each dam, and minimises the spillage effects taking into account uncertainty in the net load variations, i.e., the difference between the load and the renewable resources, and inflows to the cascade. By maximising the head levels of each dam the volume of water stored, which is a metric of system resiliency, is maximised. In this regard, the operation of the cascade hydroelectric power system is robust to the variability and intermittency of renewable resources and increases system resilience to variations in climatic conditions. Thus, we demon- strate the benefits of coupling hydroelectric and photovoltaic resources. To this end, we introduce an approximate model for a cascade hydroelectric power system. We then develop correlated probabilistic forecasts for the uncertain output of renewable resources, e.g., solar generation, using historical data based on clustering and Markov chain techniques. We incorporate the gen- erated forecast scenarios in the optimal dispatch of the cascade hydroelectric power system, and define a robust variant of the developed system. However, the robust variant is intractable due to the infinite number of constraints. Using tools from robust optimisation, we reformulate the resulting problem in a tractable form that is amenable to existing numerical tools and show that the computed dispatch is immunised against uncertainty. The efficacy of the proposed approach is demonstrated by means of an actual case study involving the Seven Forks system located in Kenya, which consists of five cascaded hydroelectric power systems. With the case study we demonstrate that the Seven Forks system may be coupled with solar generation since the “price of robustness” is small; thus demonstrating the benefits of coupling hydroelectric systems with solar generation
Access RoutesGreen bronze 37 citations 37 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.<script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1109/tpwrs.2018.2807794&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu - NSF| CPS:Medium:Collaborative Research: Smart Power Systems of the Future: Foundations for Understanding Volatility and Improving Operational Reliability ,NSF| CAREER: Reliability Engineering for Electrical Energy Systems 2020: Smart Grid Applications and Beyond Apostolopoulou, D.; Sauer, P. W.; Dominguez-Garcia, A. D.;
Apostolopoulou, D.
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesApostolopoulou, D. in OpenAIREIn this paper, we develop a reduced-order model for synchronous generator dynamics via selective modal analysis. Then, we use this reduced-order model to formulate a balancing authority (BA) area dynamic model. Next, we use the BA area model to design an adaptive automatic generation control (AGC) scheme, with self-tuning gain, that decreases the amount of regulation needed and potentially reduces the associated costs. In particular, we use the BA area model to derive a relationship between the actual frequency response characteristic (AFRC) of the BA area, the area control error, the system frequency, and the total generation. We make use of this relationship to estimate the AFRC online, and set the frequency bias factor equal to the online estimation. As a result, the AGC system is driven by the exact number of MW needed to restore the system frequency and the real power interchange to the desired values. We demonstrate the proposed ideas with a single machine infinite bus, the 9-bus 3-machine Western Electricity Coordinating Council (WECC), and a 140-bus 48-machine systems.
Access RoutesGreen bronze 29 citations 29 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.<script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1109/tpwrs.2015.2506181&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu - NSF| CPS:Medium:Collaborative Research: Smart Power Systems of the Future: Foundations for Understanding Volatility and Improving Operational Reliability ,NSF| CAREER: Reliability Engineering for Electrical Energy Systems 2020: Smart Grid Applications and Beyond Apostolopoulou, D.; Sauer, P. W.; Dominguez-Garcia, A. D.;
Apostolopoulou, D.
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesApostolopoulou, D. in OpenAIREIn this paper, we develop a reduced-order model for synchronous generator dynamics via selective modal analysis. Then, we use this reduced-order model to formulate a balancing authority (BA) area dynamic model. Next, we use the BA area model to design an adaptive automatic generation control (AGC) scheme, with self-tuning gain, that decreases the amount of regulation needed and potentially reduces the associated costs. In particular, we use the BA area model to derive a relationship between the actual frequency response characteristic (AFRC) of the BA area, the area control error, the system frequency, and the total generation. We make use of this relationship to estimate the AFRC online, and set the frequency bias factor equal to the online estimation. As a result, the AGC system is driven by the exact number of MW needed to restore the system frequency and the real power interchange to the desired values. We demonstrate the proposed ideas with a single machine infinite bus, the 9-bus 3-machine Western Electricity Coordinating Council (WECC), and a 140-bus 48-machine systems.
Access RoutesGreen bronze 29 citations 29 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.<script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1109/tpwrs.2015.2506181&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu - Najibi, F.;
Najibi, F.
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesNajibi, F. in OpenAIRE Apostolopoulou, D.; Apostolopoulou, D.
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesApostolopoulou, D. in OpenAIRE Alonso, E.; Alonso, E.
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesAlonso, E. in OpenAIREWith increasing concerns of climate change, renewable resources such as photovoltaic (PV) have gained popularity as a means of energy generation. The smooth integration of such resources in power system operations is enabled by accurate forecasting mechanisms that address their inherent intermittency and variability. This paper proposes a probabilistic framework to predict short-term PV output taking into account the uncertainty of weather. To this end, we make use of datasets that comprise of power output and meteorological data such as irradiance, temperature, zenith, and azimuth. First, we categorise the data into four groups based on solar output and time by using k-means clustering. Next, a correlation study is performed to choose the weather features which affect solar output to a greater extent. Finally, we determine a function that relates the aforementioned selected features with solar output by using Gaussian Process Regression and Matern 5/2 as a kernel function. We validate our method with five solar generation plants in different locations and compare the results with existing methodologies. More specifically, in order to test the proposed model, two different methods are used: (i) 5-fold cross-validation; and (ii) holding out 30 random days as test data. To confirm the model accuracy, we apply our framework 30 independent times on each of the four clusters. The average error follows a normal distribution, and with 95% confidence level, it takes values between -1.6% to 1.4%.
Access RoutesGreen 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.<script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.48550/arxiv.2002.10878&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu - Najibi, F.;
Najibi, F.
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesNajibi, F. in OpenAIRE Apostolopoulou, D.; Apostolopoulou, D.
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesApostolopoulou, D. in OpenAIRE Alonso, E.; Alonso, E.
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesAlonso, E. in OpenAIREWith increasing concerns of climate change, renewable resources such as photovoltaic (PV) have gained popularity as a means of energy generation. The smooth integration of such resources in power system operations is enabled by accurate forecasting mechanisms that address their inherent intermittency and variability. This paper proposes a probabilistic framework to predict short-term PV output taking into account the uncertainty of weather. To this end, we make use of datasets that comprise of power output and meteorological data such as irradiance, temperature, zenith, and azimuth. First, we categorise the data into four groups based on solar output and time by using k-means clustering. Next, a correlation study is performed to choose the weather features which affect solar output to a greater extent. Finally, we determine a function that relates the aforementioned selected features with solar output by using Gaussian Process Regression and Matern 5/2 as a kernel function. We validate our method with five solar generation plants in different locations and compare the results with existing methodologies. More specifically, in order to test the proposed model, two different methods are used: (i) 5-fold cross-validation; and (ii) holding out 30 random days as test data. To confirm the model accuracy, we apply our framework 30 independent times on each of the four clusters. The average error follows a normal distribution, and with 95% confidence level, it takes values between -1.6% to 1.4%.
Access RoutesGreen 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.<script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.48550/arxiv.2002.10878&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu - Crozier, C.;
Crozier, C.
Harvested from ORCID Public Data FileCrozier, C. in OpenAIRE Apostolopoulou, D.; McCulloch, M.;Apostolopoulou, D.
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesApostolopoulou, D. in OpenAIREAccurately predicting the behaviour of electric vehicles is going to be imperative for network operators. In order for vehicles to participate in either smart charging schemes or providing grid services, their availability and charge requirements must be forecasted. Their relative novelty means that data concerning electric vehicles is scarce and biased, however we have been collecting data on conventional vehicles for many years. This paper uses cluster analysis of travel survey data from the UK to identify typical conventional vehicle usage profiles. To this end, we determine the feature vector, introduce an appropriate distance metric, and choose a number of clusters. Five clusters are identified, and their suitability for electrification is discussed. A smaller data set of electric vehicles is then used to compare the current electric fleet behaviour with the conventional one.
Access RoutesGreen 16 citations 16 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.<script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1109/isgteurope.2018.8571707&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu - Crozier, C.;
Crozier, C.
Harvested from ORCID Public Data FileCrozier, C. in OpenAIRE Apostolopoulou, D.; McCulloch, M.;Apostolopoulou, D.
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesApostolopoulou, D. in OpenAIREAccurately predicting the behaviour of electric vehicles is going to be imperative for network operators. In order for vehicles to participate in either smart charging schemes or providing grid services, their availability and charge requirements must be forecasted. Their relative novelty means that data concerning electric vehicles is scarce and biased, however we have been collecting data on conventional vehicles for many years. This paper uses cluster analysis of travel survey data from the UK to identify typical conventional vehicle usage profiles. To this end, we determine the feature vector, introduce an appropriate distance metric, and choose a number of clusters. Five clusters are identified, and their suitability for electrification is discussed. A smaller data set of electric vehicles is then used to compare the current electric fleet behaviour with the conventional one.
Access RoutesGreen 16 citations 16 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.<script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1109/isgteurope.2018.8571707&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu - EC| SmartNet Najibi, F.;
Najibi, F.
Harvested from ORCID Public Data FileNajibi, F. in OpenAIRE Apostolopoulou, D.; Apostolopoulou, D.
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesApostolopoulou, D. in OpenAIRE Alonso, E.; Alonso, E.
Harvested from ORCID Public Data FileAlonso, E. in OpenAIREThe incorporation of renewable energy into power systems poses serious challenges to the transmission and distribution power system operators (TSOs and DSOs). To fully leverage these resources there is a need for a new market design with improved coordination between TSOs and DSOs. In this paper we propose two coordination schemes between TSOs and DSOs: one centralised and another decentralised that facilitate the integration of distributed based generation; minimise operational cost; relieve congestion; and promote a sustainable system. In order to achieve this, we approximate the power equations with linearised equations so that the resulting optimal power flows (OPFs) in both the TSO and DSO become convex optimisation problems. In the resulting decentralised scheme, the TSO and DSO collaborate to optimally allocate all resources in the system. In particular, we propose an iterative bi-level optimisation technique where the upper level is the TSO that solves its own OPF and determines the locational marginal prices at substations. We demonstrate numerically that the algorithm converges to a near optimal solution. We study the interaction of TSOs and DSOs and the existence of any conflicting objectives with the centralised scheme. More specifically, we approximate the Pareto front of the multi-objective optimal power flow problem where the entire system, i.e., transmission and distribution systems, is modelled. The proposed ideas are illustrated through a five bus transmission system connected with distribution systems, represented by the IEEE 33 and 69 bus feeders.
Access RoutesGreen gold 18 citations 18 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.<script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su13147832&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu - EC| SmartNet Najibi, F.;
Najibi, F.
Harvested from ORCID Public Data FileNajibi, F. in OpenAIRE Apostolopoulou, D.; Apostolopoulou, D.
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesApostolopoulou, D. in OpenAIRE Alonso, E.; Alonso, E.
Harvested from ORCID Public Data FileAlonso, E. in OpenAIREThe incorporation of renewable energy into power systems poses serious challenges to the transmission and distribution power system operators (TSOs and DSOs). To fully leverage these resources there is a need for a new market design with improved coordination between TSOs and DSOs. In this paper we propose two coordination schemes between TSOs and DSOs: one centralised and another decentralised that facilitate the integration of distributed based generation; minimise operational cost; relieve congestion; and promote a sustainable system. In order to achieve this, we approximate the power equations with linearised equations so that the resulting optimal power flows (OPFs) in both the TSO and DSO become convex optimisation problems. In the resulting decentralised scheme, the TSO and DSO collaborate to optimally allocate all resources in the system. In particular, we propose an iterative bi-level optimisation technique where the upper level is the TSO that solves its own OPF and determines the locational marginal prices at substations. We demonstrate numerically that the algorithm converges to a near optimal solution. We study the interaction of TSOs and DSOs and the existence of any conflicting objectives with the centralised scheme. More specifically, we approximate the Pareto front of the multi-objective optimal power flow problem where the entire system, i.e., transmission and distribution systems, is modelled. The proposed ideas are illustrated through a five bus transmission system connected with distribution systems, represented by the IEEE 33 and 69 bus feeders.
Access RoutesGreen gold 18 citations 18 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.<script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su13147832&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu - Mello, F.; Apostolopoulou, D.;
Apostolopoulou, D.
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesApostolopoulou, D. in OpenAIRE Alonso, E.; Alonso, E.
Harvested from ORCID Public Data FileAlonso, E. in OpenAIREThe introduction of new technologies and increased penetration of renewable resources is altering the power distribution landscape which now includes a larger numbers of micro-generators. The centralized strategies currently employed for performing frequency control in a cost efficient way need to be revisited and decentralized to conform with the increase of distributed generation in the grid. In this paper, the use of Multi-Agent and Multi-Objective Reinforcement Learning techniques to train models to perform cost efficient frequency control through decentralized decision making is proposed. More specifically, we cast the frequency control problem as a Markov Decision Process and propose the use of reward composition and action composition multi-objective techniques and compare the results between the two. Reward composition is achieved by increasing the dimensionality of the reward function, while action composition is achieved through linear combination of actions produced by multiple single objective models. The proposed framework is validated through comparing the observed dynamics with the acceptable limits enforced in the industry and the cost optimal setups.
Access RoutesGreen gold 4 citations 4 popularity Top 10% influence Average impulse Average Powered by BIP!add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.<script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.ifacol.2020.12.2236&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu - Mello, F.; Apostolopoulou, D.;
Apostolopoulou, D.
Derived by OpenAIRE algorithms or harvested from 3rd party repositoriesApostolopoulou, D. in OpenAIRE Alonso, E.; Alonso, E.
Harvested from ORCID Public Data FileAlonso, E. in OpenAIREThe introduction of new technologies and increased penetration of renewable resources is altering the power distribution landscape which now includes a larger numbers of micro-generators. The centralized strategies currently employed for performing frequency control in a cost efficient way need to be revisited and decentralized to conform with the increase of distributed generation in the grid. In this paper, the use of Multi-Agent and Multi-Objective Reinforcement Learning techniques to train models to perform cost efficient frequency control through decentralized decision making is proposed. More specifically, we cast the frequency control problem as a Markov Decision Process and propose the use of reward composition and action composition multi-objective techniques and compare the results between the two. Reward composition is achieved by increasing the dimensionality of the reward function, while action composition is achieved through linear combination of actions produced by multiple single objective models. The proposed framework is validated through comparing the observed dynamics with the acceptable limits enforced in the industry and the cost optimal setups.
Access RoutesGreen gold 4 citations 4 popularity Top 10% influence Average impulse Average Powered by BIP!add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.<script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.ifacol.2020.12.2236&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu
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