Tomasgard, Asgeir
Overview
| Works: | 19 works in 27 publications in 1 language and 61 library holdings |
|---|---|
| Roles: | Contributor, Other, Opponent |
| Classifications: | HD30.23, 330 |
Publication Timeline
.
Most widely held works by
Asgeir Tomasgard
Facility location under economies of scale in the case of uncertain demand(
)
1 edition published in 2005 in English and held by 17 WorldCat member libraries worldwide
1 edition published in 2005 in English and held by 17 WorldCat member libraries worldwide
Modelling in distributed telecommunications networks(
Book
)
4 editions published in 1997 in English and held by 6 WorldCat member libraries worldwide
4 editions published in 1997 in English and held by 6 WorldCat member libraries worldwide
The stochastic single resource service-provision problem by
Shane Dye(
Book
)
2 editions published in 2003 in English and held by 4 WorldCat member libraries worldwide
2 editions published in 2003 in English and held by 4 WorldCat member libraries worldwide
Approximation algorithms and relaxations for a service provision problem on a telecommunication network by
S Dye(
Book
)
2 editions published in 1998 in English and held by 4 WorldCat member libraries worldwide
2 editions published in 1998 in English and held by 4 WorldCat member libraries worldwide
Stochastic facility location with general long-run costs and convex short-run costs by
P Schütz(
Book
)
2 editions published in 2006 in English and held by 4 WorldCat member libraries worldwide
2 editions published in 2006 in English and held by 4 WorldCat member libraries worldwide
Single node service provision with fixed charges by
Shanw Dye(
Book
)
2 editions published in 1999 in English and held by 4 WorldCat member libraries worldwide
2 editions published in 1999 in English and held by 4 WorldCat member libraries worldwide
The stochastic single node service provision problem by
Shane Dye(
Book
)
2 editions published in 1999 in English and held by 3 WorldCat member libraries worldwide
2 editions published in 1999 in English and held by 3 WorldCat member libraries worldwide
Decision-dependent probabilities in stochastic programs with recourse by
Lars Hellemo(
)
1 edition published in 2018 in English and held by 2 WorldCat member libraries worldwide
1 edition published in 2018 in English and held by 2 WorldCat member libraries worldwide
The stochastic single node service provision problem by
Shane Dye(
)
1 edition published in 2002 in English and held by 2 WorldCat member libraries worldwide
1 edition published in 2002 in English and held by 2 WorldCat member libraries worldwide
Combined ship routing and inventory management in the salmon farming industry by
Agostinho Agra(
)
1 edition published in 2016 in English and held by 2 WorldCat member libraries worldwide
1 edition published in 2016 in English and held by 2 WorldCat member libraries worldwide
Natural gas production network infrastructure development under uncertainty by Xiang Li(
)
1 edition published in 2016 in English and held by 2 WorldCat member libraries worldwide
1 edition published in 2016 in English and held by 2 WorldCat member libraries worldwide
Sample average approximation and stability tests applied to energy system design by
Pernille Seljom(
)
1 edition published in 2019 in English and held by 2 WorldCat member libraries worldwide
1 edition published in 2019 in English and held by 2 WorldCat member libraries worldwide
A generalized global optimization formulation of the pooling problem with processing facilities and composite quality constraints by
Lars Hellemo(
)
1 edition published in 2015 in English and held by 2 WorldCat member libraries worldwide
1 edition published in 2015 in English and held by 2 WorldCat member libraries worldwide
Bounds in multi-horizon stochastic programs by
Francesca Maggioni(
)
1 edition published in 2019 in English and held by 2 WorldCat member libraries worldwide
1 edition published in 2019 in English and held by 2 WorldCat member libraries worldwide
Multi market bidding strategies for demand side flexibility aggregators in electricity markets(
)
1 edition published in 2018 in English and held by 1 WorldCat member library worldwide
Abstract: Due to the electricity systems' increasing need for flexibility, demand side flexibility aggregation becomes more important. An issue is how to make such activities profitable, which may be obtained by selling flexibility in multiple markets. A challenge is to allocate volumes to the different markets in an optimal way, which motivates the need for advanced decision support models. In this paper, we propose a methodology for optimal bidding for a flexibility aggregator participating in three sequential markets. We demonstrate the approach in a generalized market design that includes an options market for flexibility reservation, a spot market for day-ahead or shorter and a flexibility market for near real-time dispatch. Since the bidding decisions are made sequentially and the price information is gradually revealed, we formulate the decision models as multi-stage stochastic programs and generate scenarios for the possible realizations of prices. We illustrate the application of the models in a realistic case study in cooperation with four industrial companies and one aggregator. We quantify and discuss the value of flexibility and find that our proposed models are able to capture most of the potential value, except for some extreme cases. The value of aggregation is quantified to 3%. Highlights: We propose bidding models for a flexibility aggregator. The flexibility aggregator participates in three, sequential markets. We use stochastic programming to handle that market prices are uncertain. We perform a realistic case-study. We quantify and discuss the value of flexibility and the value of aggregation
1 edition published in 2018 in English and held by 1 WorldCat member library worldwide
Abstract: Due to the electricity systems' increasing need for flexibility, demand side flexibility aggregation becomes more important. An issue is how to make such activities profitable, which may be obtained by selling flexibility in multiple markets. A challenge is to allocate volumes to the different markets in an optimal way, which motivates the need for advanced decision support models. In this paper, we propose a methodology for optimal bidding for a flexibility aggregator participating in three sequential markets. We demonstrate the approach in a generalized market design that includes an options market for flexibility reservation, a spot market for day-ahead or shorter and a flexibility market for near real-time dispatch. Since the bidding decisions are made sequentially and the price information is gradually revealed, we formulate the decision models as multi-stage stochastic programs and generate scenarios for the possible realizations of prices. We illustrate the application of the models in a realistic case study in cooperation with four industrial companies and one aggregator. We quantify and discuss the value of flexibility and find that our proposed models are able to capture most of the potential value, except for some extreme cases. The value of aggregation is quantified to 3%. Highlights: We propose bidding models for a flexibility aggregator. The flexibility aggregator participates in three, sequential markets. We use stochastic programming to handle that market prices are uncertain. We perform a realistic case-study. We quantify and discuss the value of flexibility and the value of aggregation
Stochastic electricity dispatch: A challenge for market design(
)
1 edition published in 2018 in English and held by 1 WorldCat member library worldwide
Abstract: We consider an energy-only electricity market where some generation and/or load is uncertain, and where there are flexibility costs, i.e. some conventional power plants have to be scheduled well before real time in order to participate in the dispatch, while for others, additional cost incurs if generation plans have to be adjusted close to real time. In practice, electricity markets are often organized with sequential market clearing, and in this paper, we consider two sequential markets, for instance representing a day-ahead and a real-time market. We compare the outcomes of 1) a stochastic market clearing model, i.e. an integrated model that takes into account both markets and the uncertainty, to 2) a myopic market clearing model, where the first market is cleared based only on given bids, and not taking into account neither the uncertainty nor the bids to the second market. Compared to previous literature, our main contribution is that we compare the two different market models with respect to both efficiency and allocation of surplus, and thus the incentives they imply for the market participants. We discuss what information is needed in market agent bids and how that information can be manipulated. While the stochastic market clearing gives a solution with a higher expected social welfare, it poses several challenges for market design. The stochastic dispatch may lead to a dispatch where the day-ahead prices deviate from the bid curves to the first market. This can lead to incentives for self-scheduling, in that it may require market participants to accept prices that deviate from the marginal costs or benefits corresponding to the scheduled quantities. Our analysis shows that the intermittent producer has an incentive to deviate from the system optimal plan in both the myopic and stochastic model, and this incentive is particularly strong under the myopic model. We also discuss how the expected social welfare of the market outcome under stochastic market clearing depends on the quality of the information that the system operator will base the market clearing on. In particular, we show that an intermittent producer may have an incentive to misreport the probability distribution for its generation. Highlights: Stochastic dispatch model for electricity networks with two sequential markets. The stochastic model gives a higher expected surplus than the myopic model. Discrepancies between what is optimal for the system and the intermittent producer. The intermittent producer may exercise market power by manipulating information
1 edition published in 2018 in English and held by 1 WorldCat member library worldwide
Abstract: We consider an energy-only electricity market where some generation and/or load is uncertain, and where there are flexibility costs, i.e. some conventional power plants have to be scheduled well before real time in order to participate in the dispatch, while for others, additional cost incurs if generation plans have to be adjusted close to real time. In practice, electricity markets are often organized with sequential market clearing, and in this paper, we consider two sequential markets, for instance representing a day-ahead and a real-time market. We compare the outcomes of 1) a stochastic market clearing model, i.e. an integrated model that takes into account both markets and the uncertainty, to 2) a myopic market clearing model, where the first market is cleared based only on given bids, and not taking into account neither the uncertainty nor the bids to the second market. Compared to previous literature, our main contribution is that we compare the two different market models with respect to both efficiency and allocation of surplus, and thus the incentives they imply for the market participants. We discuss what information is needed in market agent bids and how that information can be manipulated. While the stochastic market clearing gives a solution with a higher expected social welfare, it poses several challenges for market design. The stochastic dispatch may lead to a dispatch where the day-ahead prices deviate from the bid curves to the first market. This can lead to incentives for self-scheduling, in that it may require market participants to accept prices that deviate from the marginal costs or benefits corresponding to the scheduled quantities. Our analysis shows that the intermittent producer has an incentive to deviate from the system optimal plan in both the myopic and stochastic model, and this incentive is particularly strong under the myopic model. We also discuss how the expected social welfare of the market outcome under stochastic market clearing depends on the quality of the information that the system operator will base the market clearing on. In particular, we show that an intermittent producer may have an incentive to misreport the probability distribution for its generation. Highlights: Stochastic dispatch model for electricity networks with two sequential markets. The stochastic model gives a higher expected surplus than the myopic model. Discrepancies between what is optimal for the system and the intermittent producer. The intermittent producer may exercise market power by manipulating information
Stochastic electricity dispatch a challenge for market design by
Endre Bjørndal(
)
1 edition published in 2016 in English and held by 1 WorldCat member library worldwide
1 edition published in 2016 in English and held by 1 WorldCat member library worldwide
Hydrogen systems : what contribution to the energy system? Findings from multiple modelling approaches by
Olfa Tlili(
)
1 edition published in 2019 in English and held by 1 WorldCat member library worldwide
Hydrogen... This simple, very abundant element holds great promise to contribute to the transition towards a cleaner future energy system, but under which techno-economic and political conditions? This thesis is a contribution to the assessment of the hydrogen penetration feasibility into the energy system, using a multi-model approach. The focus is put on low-carbon hydrogen, obtained by electrolysis.Our multi-regional analysis on the European, American, Chinese and Japanese energy context (presenting contrasted energy challenges) show that, with the current energy policies implemented which result in a modest penetration of hydrogen into the energy system, hydrogen may achieve approximately 3% of the effort that needs to be done by the four regions, in order to limit the increase of the temperature to 2°C, compared to preindustrial levels. We highlight in this thesis that blending hydrogen with natural gas, and thereby avoiding methane leakages to a certain extent, may represent a significant contribution in achieving the carbon mitigation goals.The hydrogen market analysis has been carried out following two steps. First, each market (industrial and energy-related) was tackled aside in order to propose market entry costs considering the four energy contexts and investigate the timeframe of the market penetration potential. Then, the different hydrogen applications were examined within the overall energy system through the TIMES-PT model (for a Portugal case study), allowing to investigate the hydrogen potential for energy sector coupling. Based on this work, the markets attractiveness was evaluated: mobility (using fuel cell vehicles) appears to be the most favourable.Then, we tackled the required costs over the whole hydrogen supply chain in order to enter the mobility market.To do so, we used temporally and spatially resolved models (GLAES, EuroPower and InfraGis) starting with the production side where we studied the hydrogen potential role in providing the electricity system with flexibility and the impact of such electrolysis operation on the hydrogen generation costs in the context of high shares of renewable energies in France. Our results show that hydrogen can contribute to improve the flexibility of the electric system by allowing avoiding renewable curtailment (between 1.4 and 7.9 TWh depending on the interconnection capacity scenario) but also by taking advantage of nuclear plant available energy (thereby avoiding nuclear ramping), the latter ensuring a low carbon and low cost electricity provision. However, a special attention needs to be dedicated to the utilisation rate of the electrolyser, to keep the hydrogen production costs low enough.Last but not least, we focused on how to link the hydrogen production sites and its final use for mobility applications, the delivery infrastructure being a major issue hampering the hydrogen investments. Five transport and delivery pathways were geographically designed and economically assessed, for the French case. According to our findings, during the very first market penetration phases (1% scenario), it is more interesting to start with decentralised production that proved to be less expensive for the whole pathway at this stage
1 edition published in 2019 in English and held by 1 WorldCat member library worldwide
Hydrogen... This simple, very abundant element holds great promise to contribute to the transition towards a cleaner future energy system, but under which techno-economic and political conditions? This thesis is a contribution to the assessment of the hydrogen penetration feasibility into the energy system, using a multi-model approach. The focus is put on low-carbon hydrogen, obtained by electrolysis.Our multi-regional analysis on the European, American, Chinese and Japanese energy context (presenting contrasted energy challenges) show that, with the current energy policies implemented which result in a modest penetration of hydrogen into the energy system, hydrogen may achieve approximately 3% of the effort that needs to be done by the four regions, in order to limit the increase of the temperature to 2°C, compared to preindustrial levels. We highlight in this thesis that blending hydrogen with natural gas, and thereby avoiding methane leakages to a certain extent, may represent a significant contribution in achieving the carbon mitigation goals.The hydrogen market analysis has been carried out following two steps. First, each market (industrial and energy-related) was tackled aside in order to propose market entry costs considering the four energy contexts and investigate the timeframe of the market penetration potential. Then, the different hydrogen applications were examined within the overall energy system through the TIMES-PT model (for a Portugal case study), allowing to investigate the hydrogen potential for energy sector coupling. Based on this work, the markets attractiveness was evaluated: mobility (using fuel cell vehicles) appears to be the most favourable.Then, we tackled the required costs over the whole hydrogen supply chain in order to enter the mobility market.To do so, we used temporally and spatially resolved models (GLAES, EuroPower and InfraGis) starting with the production side where we studied the hydrogen potential role in providing the electricity system with flexibility and the impact of such electrolysis operation on the hydrogen generation costs in the context of high shares of renewable energies in France. Our results show that hydrogen can contribute to improve the flexibility of the electric system by allowing avoiding renewable curtailment (between 1.4 and 7.9 TWh depending on the interconnection capacity scenario) but also by taking advantage of nuclear plant available energy (thereby avoiding nuclear ramping), the latter ensuring a low carbon and low cost electricity provision. However, a special attention needs to be dedicated to the utilisation rate of the electrolyser, to keep the hydrogen production costs low enough.Last but not least, we focused on how to link the hydrogen production sites and its final use for mobility applications, the delivery infrastructure being a major issue hampering the hydrogen investments. Five transport and delivery pathways were geographically designed and economically assessed, for the French case. According to our findings, during the very first market penetration phases (1% scenario), it is more interesting to start with decentralised production that proved to be less expensive for the whole pathway at this stage
Modelling in distributed telecommunications networks(
)
1 edition published in 1997 in English and held by 1 WorldCat member library worldwide
The purpose of this paper is to formally describe new optimization models for distributed telecommunication networks.Modern distributed networks put more focus on the processing of information and less on the actual transportation of datathan we are traditionally used to in telecommunications. This paper introduces new approaches for modelling decisionsupport at operational, tactical and strategic levels. This is done by first defining the technological framework we areworking within. One of the main advantages of this framework is its inherent flexibility, which enables us to do dynamicplanning and consider uncertainty when decisions are made. When we present the models, emphasis is placed on themodelling discussions around the shift of focus towards processing, the new technological aspects, and how to utilizeflexibility to cope with uncertainty
1 edition published in 1997 in English and held by 1 WorldCat member library worldwide
The purpose of this paper is to formally describe new optimization models for distributed telecommunication networks.Modern distributed networks put more focus on the processing of information and less on the actual transportation of datathan we are traditionally used to in telecommunications. This paper introduces new approaches for modelling decisionsupport at operational, tactical and strategic levels. This is done by first defining the technological framework we areworking within. One of the main advantages of this framework is its inherent flexibility, which enables us to do dynamicplanning and consider uncertainty when decisions are made. When we present the models, emphasis is placed on themodelling discussions around the shift of focus towards processing, the new technological aspects, and how to utilizeflexibility to cope with uncertainty
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Related Identities
- Stougie, Leen Contributor
- Schütz, Peter Author Contributor
- Dye, S. (Shane) Author
- SpringerLink (Online service) Other
- Hellemo, Lars Author
- Barton, Paul I. Other Contributor
- Tinbergen Institute
- Solhaug, Ida Elise Other
- Bjørndal, Endre Author
- Christiansen, Marielle Other