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  • 1.
    Dalton, Jacob
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Herre, Lars
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Söder, Lennart
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Exploring the Business Case of a Risk-Averse Electric Vehicle Aggregator in the Nordic Market2018Conference paper (Refereed)
    Abstract [en]

    The Nordic power system is facing the challenge of the ongoing decrease of synchronous generation along with increased penetration of inverter based renewable generation leading to reduced system inertia. Meanwhile, the electrification of the transport sector will result in a significant amount of additional electrical loads. However, the electrification of private transport is a technology of growing interest that can provide flexibility to the power system if adequately utilized. Electric vehicles (EV) can be considered as temporary energy storage with availability, energy and capacity constraints.

    In this paper, we use first hand data of a real EV fleet of Tesla vehicles and their historical driving patterns to develop a two-stage stochastic optimization problem. This model maximizes the profit of a risk-averse EV aggregator that aims to place optimal bids on the day ahead in both energy and Frequency Containment Reserve (FCR) markets. Only uni-directional charging is examined, while we take into account uncertainty from prices and vehicle utilization. Case studies are carried out modelling individual vehicle driving behavior in different Nordic price areas in both winter and summer.

    We identify a strong alignment of EV availability and periods of high FCR prices. Results show that consumption is shifted largely towards early hours of the morning. When compared to a  reference ”cost of charging case”, up to 50% of the cost of charging can be covered in Norway, while the entire cost is met in Sweden.

  • 2.
    Dimoulkas, Ilias
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
    Herre, Lars
    KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
    Khastieva, Dina
    KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
    Nycander, Elis
    KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
    Amelin, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
    Mazidi, P.
    A hybrid model based on symbolic regression and neural networks for electricity load forecasting2018In: International Conference on the European Energy Market, EEM, IEEE Computer Society, 2018, article id 8469901Conference paper (Refereed)
    Abstract [en]

    This paper proposes a hybrid model for electricity load forecasting. Symbolic regression is initially used to automatically create a regression model of the load. Then the explanatory variables and their transformations that have been selected in the model are used as input in an artificial neural network that is trained to predict the electricity load at the output. Therefore symbolic regression operates as a feature selection-creation method and forecasting is done by the artificial neural network. The proposed hybrid model has been successfully used in an electricity load forecasting competition.

  • 3.
    Dimoulkas, Ilias
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Mazidi, Peyman
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems. Comillas Pontifical University, Madrid,.
    Herre, Lars
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    EEM 2017 Forecast Competition: Wind power generation prediction using autoregressive models2017In: European Energy Market (EEM), 2017 14th International Conference on the, IEEE conference proceedings, 2017Conference paper (Refereed)
    Abstract [en]

    Energy forecasting provides essential contribution tointegrate renewable energy sources into power systems. Today,renewable energy from wind power is one of the fastest growingmeans of power generation. As wind power forecast accuracygains growing significance, the number of models used forforecasting is increasing as well. In this paper, we propose anautoregressive (AR) model that can be used as a benchmarkmodel to validate and rank different forecasting models andtheir accuracy. The presented paper and research was developedwithin the scope of the European energy market (EEM) 2017wind power forecasting competition.

  • 4.
    Herre, Lars
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
    Dalton, Jacob
    KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
    Söder, Lennart
    KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
    Optimal Day-Ahead Energy and Regulation Self-Scheduling of a Risk-Averse Electric vehicle Aggregator in the Nordic Market2019In: / [ed] IEEE, IEEE Xplore, 2019Conference paper (Refereed)
    Abstract [en]

    Electric vehicles (EV) can be considered as energy storage with availability, energy and capacity constraints that can provide flexibility to the power system in the form of balancing products when aggregated. In this paper, we develop a two-stage stochastic optimization problem that maximizes the profit of a risk-averse EV aggregator for bids on the day ahead in both energy and Frequency Containment Reserve (FCR) markets. Unidirectional charging is examined, while we take into account uncertainty from prices and vehicle availability. Case studies are carried out in different Nordic bidding areas based on historical EV charging data. We identify a strong temporal alignment of EV availability and high FCR-N prices. Results show that consumption is shifted largely towards early hours of the morning. When compared to a reference cost of charging case, up to 50% of the cost of charging can be recovered in Norway, and 100% in Sweden.

  • 5.
    Herre, Lars
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Kovala, Tommy
    Söder, Lennart
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Papahristodoulou, Christos
    A Study on the Flexibility of Electricity Consumers for the Swedish Context: Modelling, Quantification and Analysis of Notice Time2016Conference paper (Refereed)
    Abstract [en]

    Demand Side Management enables flexible electricity consumers to participate in services that contribute to reliable operation of the power system. The specific market, pricing scheme and demand response program decide in which way consumers receive incentives and provide services. The consumers’ response depends on the price and other parameters. Here, the impact of notice time on the flexibility of consumers is investigated. We summarize projects and literature on consumer elasticity and conduct a simulation study. The results show the significance of notice time dependent elasticity of consumers on power balancing in forward markets.

  • 6.
    Herre, Lars
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Matusevicius, Tadas
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Söder, Lennart
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Swedish Wind Power Forecasts: Procedure, ErrorDistribution and Spacio-Temporal Correlation2017In: 16th International Workshop on Large-Scale Integration of Wind Power into Power Systems as well as on Transmission Networks for Offshore Wind Power Plants, Berlin, 2017, article id WIW17-124Conference paper (Refereed)
    Abstract [en]

    The stochastic nature of wind imposes challengeson accurate predictions of wind power generation. A goodunderstanding of the errors that may occur is imperativefor greater penetration of wind power into the system, asit can facilitate planning and operation tasks. In this paper,Swedish wind power forecast accuracy over the forecasthorizon is analyzed and compared among different biddingzones. The root-mean-square error trajectory over the horizonis shown for Sweden and its individual bidding areas. Inaddition, a significant systematic wind power under-predictionis identified and discussed. The paper continues to analyzethe wind power forecast error distribution with respect tothe horizon. Furthermore, the spacio-temporal correlationbetween the errors at different horizons and bidding areasis presented. As expected, a stronger correlation between theforecast errors is identified in neighboring areas.

  • 7.
    Herre, Lars
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
    Matusevičius, Tadas
    KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
    Olauson, Jon
    KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
    Söder, Lennart
    KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
    Exploring Wind Power Prognosis Data on Nord Pool: The Case of Sweden and Denmark2019In: IET Renewable Power Generation, ISSN 1752-1416, E-ISSN 1752-1424, ISSN 1752-1416Article in journal (Refereed)
    Abstract [en]

    A good understanding of forecast errors is imperative for greater penetration of wind power, as it can facilitate planning and operation tasks. Oftentimes, public data is used for system studies without questioning or verifying its origin. In this paper, we propose a methodology to verify public data with the example of wind power prognosis published by Nord Pool. We focus on Swedish data and identify a significant bias that increases over the forecast horizon. In order to explore the origin of this bias, we first compare against Danish forecast and then describe the underlying structure behind the submission processes of this data. Based on the balance settlement structure, we reveal that Swedish "wind power prognoses" on Nord Pool are in fact rather wind production plans than technical forecasts. We conclude with the recommendation for improved communication and transparency with respect to terminology of public data on Nord Pool. We stress the importance for the research community to check publicly available input data before further use. Furthermore, the root-mean-square error and the spatio-temporal correlation between the errors in the bidding areas at different horizons is presented. Even with this compromised data, a stronger correlation is identified in neighbouring areas.

  • 8.
    Herre, Lars
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Söder, Lennart
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Enhancing market access of demand response through generation forecast updates2017In: 2017 IEEE Manchester PowerTech, Powertech 2017, IEEE, 2017, article id 7981023Conference paper (Refereed)
    Abstract [en]

    Advances in communication infrastructure and elec-tric appliances have enabled demand side participation in powersystem operation. However, the full potential of demand flexibilityis yet to be exploited. Existing demand response programs requireflexibility in a set time frame from the electricity consumers inreaction to economic incentives. For a more detailed qualitativeanalysis of consumer flexibility, not only price but also noticetime are imperative parameters. The former has been studied innumerous references whereas the impact of the latter has not yetbeen examined in depth. This paper presents a market modelof demand response that enhances an efficient use of flexibleconsumers by hourly updates. The consequences of flexibleelectricity consumers are studied in a Real Time Pricing modelwith continuous forecast updates, where elasticity is subject tonotice time. A case study is presented using data from Sweden.We conclude that current demand response programs are notoptimally designed to integrate consumer flexibility that changeswith the notice time. 

  • 9.
    Herre, Lars
    et al.
    KTH, School of Electrical Engineering (EES), Electric power and energy systems.
    Söder, Lennart
    KTH, School of Electrical Engineering (EES), Electric power and energy systems.
    On the flexibility of electricity consumers: Introducing notice time2016Conference paper (Refereed)
    Abstract [en]

    Power systems with a large share of inherently intermittent energy sources require new approaches to system operation. Demand side management is seen as one potential resource for maintaining power balance in a future energy system with large amounts of volatile renewable energy generation. Existing demand response programs require flexibility in a set time frame from the electricity consumers in reaction to economic incentives. For a more detailed qualitative analysis of consumer flexibility, not only price but also notice time are imperative parameters. Former has been studied in numerous references whereas the impact of the latter has not yet been examined in depth. This paper presents a review of existing demand response programs and reflects on consumers' flexibility with respect to notice time. While some schemes include fixed notification schedules, others allow for variable notice time, or even continuous updating. In this paper, the consequences of notice time and update intervals on flexible electricity consumers are studied in Demand Bidding model with continuous forecast updates.

  • 10.
    Herre, Lars
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
    Söder, Lennart
    KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
    Mathieu, Johanna L.
    University of Michigan Ann Arbor, MI 48109 USA.
    The Flexibility of Thermostatically Controlled Loads as a Function of Price Notice Time2018In: 2018 POWER SYSTEMS COMPUTATION CONFERENCE (PSCC), Dublin: IEEE conference proceedings, 2018Conference paper (Refereed)
    Abstract [en]

    Due to increased use of variable renewable energy sources, more capacity for balancing and ancillary services (AS) is required. Non-generating resources such as thermostatically controlled loads (TCLs) can arbitrage energy prices and provide AS due to their thermal energy storage capacity. This paper explores the impact of energy/AS price notice time, i.e. the time between when the price is announced and when it takes effect, on the TCL energy consumption and AS capacity bids, and quantifies trade-offs between notice time and flexibility. We first optimize the energy consumption and AS capacity offers at a given notice time, varied from 24 hours ahead to real-time. We then introduce uncertainty in TCL availability, formulate the stochastic optimization problem, and evaluate how the trade-offs change. We find that price notice time impacts TCL profits, but does not significantly affect the total AS capacity offered over the day. However, AS capacity offers are impacted by uncertainty, which is likely to increase with notice time.

  • 11.
    Herre, Lars
    et al.
    University of Technology Eindhoven, the Netherlands.
    Wouters, Peter
    Steennis, Fred
    de Graaff, Roald
    On the electromagnetic coupling of AC and DC circuits on hybrid transmission towers2016In: IEEE International Energy Conference (ENERGYCON), Leuven: IEEE , 2016, p. 1-6Conference paper (Refereed)
    Abstract [en]

    Transmission system limits, originating from right-of-way permission processes for new corridors, can be surpassed by erecting new circuits in close proximity, or even on common structures. Especially for long distance bulk power transfer, high voltage direct current technology promises superior features. Adding a circuit to a transmission corridor is one method of significantly increasing power transfer capability. Converting an existing AC circuit for DC operation is another method that additionally decreases investment in new lines and towers. Consequences of such application are various AC/DC interaction phenomena on either AC or DC lines for both steady and transient conditions. This paper presents a study on AC/DC transmission system interactions for a hybrid tower configuration. In normal operation DC voltage showed no significant fundamental AC frequency component, while induced transient overvoltages displayed notable levels.

1 - 11 of 11
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