Asgeir Tomasgard - Profile on Academia.edu (original) (raw)

Papers by Asgeir Tomasgard

Research Square (Research Square), Aug 17, 2023

Multi-horizon stochastic programming includes short-term and long-term uncertainty in investment ... more Multi-horizon stochastic programming includes short-term and long-term uncertainty in investment planning problems more efficiently than traditional multi-stage stochastic programming. In this paper, we exploit the block separable structure of multi-horizon stochastic linear programming, and establish that it can be decomposed by Benders decomposition and Lagrangean decomposition. In addition, we propose parallel Lagrangean decomposition with primal reduction that, (1) solves the scenario subproblems in parallel, (2) reduces the primal problem by keeping one copy for each scenario group at each stage, and (3) solves the reduced primal problem in parallel. We apply the parallel Lagrangean decomposition with primal reduction, Lagrangean decomposition and Benders decomposition to solve a stochastic energy system investment planning problem. The computational results show that: (a) the Lagrangean type decomposition algorithms have better convergence at the first iterations to Benders decomposition, and (b) parallel Lagrangean decomposition with primal reduction is very efficient for solving multi-horizon stochastic programming problems. Based on the computational results, the choice of algorithms for multi-horizon stochastic programming is discussed.

Energy, Dec 1, 2022

Clean, multi-carrier Offshore Energy Hubs (OEHs) may become pivotal for efficient offshore wind p... more Clean, multi-carrier Offshore Energy Hubs (OEHs) may become pivotal for efficient offshore wind power generation and distribution. In addition, OEHs may provide decarbonised energy supply for maritime transport, oil and gas recovery, and offshore farming while also enabling conversion and temporary storage of liquefied decarbonised energy carriers for export. Here, we investigate the role of OEHs in the transition of the Norwegian continental shelf energy system towards zero-emission energy supply. We develop a mixedinteger linear programming model for investment planning and operational optimisation to achieve decarbonisation at minimum costs. We consider clean technologies, including offshore wind, offshore solar, OEHs and subsea cables. We conduct sensitivity analysis on CO 2 tax, CO 2 budget and the capacity of power from shore. The results show that (a) a hard carbon cap is necessary for stimulating a zero-emission offshore energy system; (b) offshore wind integration and power from shore can more than halve current emissions, but OEHs with storage are necessary for zero-emission production and (c) at certain CO 2 tax levels, the system with OEHs can potentially reduce CO 2 emissions by 50% and energy losses by 10%, compared to a system with only offshore renewables, gas turbines and power from shore.

This paper investigates the development of neighbourhoods with ambitious emission targets in the ... more This paper investigates the development of neighbourhoods with ambitious emission targets in the Nordic countries and their value for the power system. The targets relate to compensating for emissions in neighbourhoods through local low-carbon electricity and heat production. The first part of our analysis investigates local generation expansion with a neighbourhood perspective using a mixed integer linear programming model. The second part investigates the value of representative neighbourhoods with a country perspective using a generation and transmission capacity expansion model. When coupling the models, results indicate that neighbourhoods with co-generation of electricity and heat are most attractive for the power system in the Nordics, while neighbourhoods with solar PV provide most emission reduction.

Computers & Chemical Engineering, Aug 1, 2020

The ability of pipelines to store gas by increasing their operating pressure, or linepacking, is ... more The ability of pipelines to store gas by increasing their operating pressure, or linepacking, is a common operational practice used to mitigate future operational uncertainty. The optimal operation of a gas pipeline network considering linepacking is determined by weighing the trade-off between storing linepack and compressor power consumption. Existing compressor performance models do not accurately capture the rigorous nonlinear operating relationships, and the more accurate widely-used models are computationally complex. This paper develops a novel integer-linear data-driven compressor performance model which is shown to be both more accurate than the best existing model, and less computationally complex. An integer-linear gas transportation model that captures future operational uncertainty using a two-stage multi-period stochastic framework is introduced and solved in a case study on a subnetwork of the Norwegian natural gas network. The case study demonstrates the novel model is highly accurate and can be optimized quickly enough for real-time decision support.

Current sustainable/renewable energy reports, Feb 2, 2023

Purpose of Review Balancing a large share of solar and wind power generation in the power system ... more Purpose of Review Balancing a large share of solar and wind power generation in the power system will require a well synchronized coordination of all possible flexibility sources. This entails developing market designs that incentivize flexibility providers, and define new flexibility products. To this end, the paper reviews latest trends in the characterization of flexibility by understanding its dimensions in terms of time, spatiality, resource type, and associated risks. Also, as aggregators have emerged as important actors to deliver, and to reward end-user flexibility, the paper reviews latest trends in the topic. The review reports latest trends and discussions on power system flexibility and their relations to market design. The current academic literature indicates that there are open question and limited research on how to reward shortterm flexibility while considering its long-term economic viability. Demand-side flexibility through aggregation holds great potential to integrate renewables. Summary Research in power system flexibility has to put effort on analysing new time-structures of electricity markets and define new marketplaces that consider the integration of new flexibility products, actors (e.g. aggregators, end-users), and mechanisms (e.g. TSO-DSO coordination). Flexibility • Market designs • Decentralization • balancing • Aggregators • Renewables This article is part of the Topical Collection on Zero-Marginal-Cost Market Design Jayaprakash Rajasekharan

arXiv (Cornell University), Sep 7, 2021

The authors provide a comprehensive overview of flexibility characterization along the dimensions... more The authors provide a comprehensive overview of flexibility characterization along the dimensions of time, spatiality, resource, and risk in power systems. These dimensions are discussed in relation to flexibility assets, products, and services, as well as new and existing flexibility market designs. The authors argue that flexibility should be evaluated based on the dimensions under discussion. Flexibility products and services can increase the efficiency of power systems and markets if flexibility assets and related services are taken into consideration and used along the time, geography, technology, and risk dimensions. Although it is possible to evaluate flexibility in existing market designs, a local flexibility market may be needed to exploit the value of the flexibility, depending on the dimensions of the flexibility products and services. To locate flexibility in power grids and prevent incorrect valuations, the authors also discuss TSO-DSO coordination along the four dimensions, and they present interrelations between flexibility dimensions, products, services, and related market designs for productive usage of flexible electricity.

arXiv (Cornell University), Sep 21, 2022

Hydrogen will be a central cross-sectoral energy carrier in the decarbonization of the European e... more Hydrogen will be a central cross-sectoral energy carrier in the decarbonization of the European energy system. This paper investigates how a large-scale deployment of green hydrogen production affects the investments in transmission and generation towards 2060, analyzes the North Sea area with the main offshore wind projects, and assesses the development of an offshore energy hub. Results indicate that the hydrogen deployment has a tremendous impact on the grid development in Europe and in the North Sea. Findings indicate that total power generation capacity increases around 50%. The offshore energy hub acts mainly as a power transmission asset, leads to a reduction in total generation capacity, and is central to unlock the offshore wind potential in the North Sea. The effect of hydrogen deployment on power prices is multifaceted. In regions where power prices have typically been lower than elsewhere in Europe, it is observed that hydrogen increases the power price considerably. However, as hydrogen flexibility relieves stress in high-demand periods for the grid, power prices decrease in average for some countries. This suggests that while the deployment of green hydrogen will lead to a significant increase in power demand, power prices will not necessarily experience a large increase.

Energy Systems

European CO2 reduction goals have led to an increase in variable energy sources such as wind and ... more European CO2 reduction goals have led to an increase in variable energy sources such as wind and solar, and consequently to an energy system that will need more flexibility in the future. In Norway, the hydropower reservoirs will enable the country to play a crucial role in European electrification by delivering flexibility to countries in Northern Europe. A further source of flexibility is demand response (DR) accumulated in residential, commercial, and industrial sectors. The paper discusses DR, load shifting, and load shedding based on the application of a stochastic TIMES model and it evaluates the role of DR in the Norwegian energy system towards 2050. The analysis shows that cost-efficient DR operation primarily comes from space heating in residential buildings. The use of DR, which is season-dependent, increases the volume of electricity trade, including electricity export and import to neighboring countries, and it smooths electricity prices. The implementation of DR in Norw...

2018 15th International Conference on the European Energy Market (EEM)

arXiv (Cornell University), Sep 7, 2022

Benders decomposition with adaptive oracles was proposed to solve large-scale optimisation proble... more Benders decomposition with adaptive oracles was proposed to solve large-scale optimisation problems with a column bounded block-diagonal structure, where subproblems differ on the right-hand side and cost coefficients. Adaptive Benders reduces computational effort significantly by iteratively building inexact cutting planes and valid upper and lower bounds. However, Adaptive Benders and standard Benders may suffer severe oscillation when solving a multi-region investment planning problem. Therefore, we propose stabilising Adaptive Benders with the level set method and adaptively selecting the subproblems to solve per iteration for more accurate information. Furthermore, we propose a dynamic level set method to improve the robustness of stabilised Adaptive Benders by adjusting the level set per iteration. We compare stabilised Adaptive Benders with the unstabilised versions of Adaptive Benders with one subproblem solved per iteration and standard Benders on a multi-region long-term power system investment planning problem with short-term and long-term uncertainty. The problem is formulated as multi-horizon stochastic programming. Four algorithms were implemented to solve linear programming with up to 1 billion variables and 4.5 billion constraints. The computational results show that: a) for a 1.00% convergence tolerance, the proposed stabilised method is up to 113.7 times faster than standard Benders and 2.14 times faster than unstabilised Adaptive Benders ; b) for a 0.10% convergence tolerance, the proposed stabilised method is up to 45.5 times faster than standard Benders and unstabilised Adaptive Benders cannot solve the largest instance to convergence tolerance due to severe oscillation and c) dynamic level set method makes stabilisation more robust.

IEEE Access

The authors focus on a model for system operators that uses centralized scheduling of multiple fl... more The authors focus on a model for system operators that uses centralized scheduling of multiple flexibility assets and services to minimize the cost of managing problems with grid congestion, voltages, and losses. The model schedules flexibility assets using stochastic optimization for AC optimal power flow in an active distribution network. The novelty of the contribution lies in its focus on how the dynamic capabilities of the flexibility resources are defined with regard to how uncertainty is resolved in the model. The impact of uncertainty is studied by using well-known quality measures from stochastic programming, such as the value of the stochastic solution. Moreover, the authors introduce a new measure related to the impact of representing uncertainty and flexibility when considering reactive power. By changing the time attributes of 82966

arXiv (Cornell University), May 12, 2022

This paper presents the stochastic power system investment model EMPIRE. Formulated as a multi-ho... more This paper presents the stochastic power system investment model EMPIRE. Formulated as a multi-horizon stochastic program EMPIRE incorporates long-term and short-term system dynamics, while optimizing investments under operational uncertainty. By decoupling the optimization of system operation at each investment period from future investment and operation periods, a computationally tractable optimization problem is produced. The use of EMPIRE is illustrated in a decarbonization study of the European power system for two cases, one with transmission infrastructure investments, and one without. A combination of onshore wind and thermal generation with carbon capture and storage (CCS) is shown to provide significant CO2 emission reductions from 2010 to 2050, 85 % in the transmission expansion case and 82 % in the no expansion case.

International Journal of Electrical Power & Energy Systems, 2021

This paper investigates sector coupling between the central power system and local energy communi... more This paper investigates sector coupling between the central power system and local energy communities, including heat supply for buildings and charging of electric vehicles. We propose a stochastic linear programming framework to study long-term investments under uncertain short-term operations of nationally aggregated assets. We apply the model to a case study assuming European power sector decarbonization towards 2060 according to a 1.5 degree scenario, and we investigate the impact of coupling building heat systems and electric vehicle charging in Norway with the European power market. The case study focuses on the role of Norway in a European perspective because: (1) Norwegian electricity production is mainly based on flexible and renewable hydropower, (2) Norwegian building heating systems are currently mainly electric, and (3) Norway is already introducing electric vehicles at large. We focus on the European power market to test our hypothesis that it is more cost-efficient to decarbonize when the central power system is coordinated with building heat systems and electric vehicle charging. For Europe as a whole, results show that the average European electricity cost reduces by 3% and transmission expansion decreases by 0.4% when Norwegian heat systems are developed in co- ordination with the European power system. The average Norwegian electricity cost decreases by 19%. The strategy includes supplying up to 20% of Norwegian buildings with district heating fueled by waste and biomass, and the remaining electric heating supply is dominated by heat pumps.

Computers & Chemical Engineering, 2020

European Journal of Operational Research, 2020

The approach of choice to analyze markets with oligopolistic competition has traditionally been c... more The approach of choice to analyze markets with oligopolistic competition has traditionally been complementarity modeling. In this paper we show that the majority of partial equilibrium models under imperfect competition in the (energy-)economic literature can in fact be cast as optimization models, not requiring the derivation and implementation of Karush-Kuhn-Tucker conditions. This is achieved by adding appropriate terms accounting for market power exertion to the well-known social welfare maximization objective. The method is applicable to both spatial Cournot oligopoly models and hybrid competition forms often implemented using conjectural variation approaches. We show how optimization and complementarity problems are equivalent, and provide a rationale for the terms accounting for market power exertion. Resulting models are solved orders of magnitude faster using off-the-shelf optimization software, compared to solving complementarity problems. Large problem instances take minutes rather than hours, and one instance solves 640 times faster. The drastically reduced solution times greatly enhance modeling capabilities as they allow increased geographical scope and represent economic, technical and other characteristics in much more detail in equilibrium problems with imperfect competition. We present practical implications for the partial and multi-level equilibrium modeling community.

Energy Systems, 2019

This paper uses confidence intervals from sample average approximation (SAA) and stability tests ... more This paper uses confidence intervals from sample average approximation (SAA) and stability tests to evaluate the quality of the solution of a long-term energy system model with stochastic wind power production. Using poorly designed scenarios can give stochastic model results that depend on the scenario representation rather than the actual underlying uncertainty. Nevertheless, there is little focus on the quality of the solutions of stochastic energy models in the applied literature. Our results demonstrate how too small a sample size can give a poor energy system design and misrepresent the value of the stochastic solution (VSS). We demonstrate how to evaluate the number of scenarios needed to ensure in-sample and out-of-sample stability. We also show how replication and testing of many candidate solutions using SAA iterations can provide a solution with a satisfactory confidence interval, including when the samples contain fewer scenarios than required for stability. An important observation, though, is that if SAA repeatedly solves the model with a sample size that satisfies in-sample and out-of-sample stability, the confidence interval is narrow, and the solutions are of high quality in terms of providing a tight bound for the optimal solution.

Annals of Operations Research, 2019

In this paper, we present bounds for multi-horizon stochastic optimization problems, a class of p... more In this paper, we present bounds for multi-horizon stochastic optimization problems, a class of problems introduced in [16] relevant in many industry-life applications tipically involving strategic and operational decisions on two different time scales. After providing three general mathematical formulations of a multi-horizon stochastic program, we extend the definition of the traditional Expected Value problem and Wait-and-See problem from stochastic programming in a multihorizon framework. New measures are introduced allowing to quantify the importance of the uncertainty at both strategic and operational levels. Relations among the solution approaches are then determined and chain of inequalities provided. Numerical experiments on a real-life application from energy planning are finally presented.

Energy Economics, 2018

We investigate the economic impacts of introducing tradable green certificates to promote electri... more We investigate the economic impacts of introducing tradable green certificates to promote electricity produced from renewable energy sources. We formulate a mixed complementarity, multi-region, partial equilibrium model, clearing both the electricity and green certificate markets under the assumption of Nash-Cournot market competition. We introduce a mixed complementarity formulation of the tradable green certificate policy scheme. The main contribution of this paper is to combine a public support scheme for electricity production with a power market model in which strategic generators compete and exercise market power in a capacitated transmission network with spatial energy exchange. Any policy instrument interfering with the free market solution in a partial equilibrium model will reduce social welfare as a result of deadweight losses from the policy. These welfare losses may be substantial. We show that losses from tradable green certificates influence different market actors depending on the market conditions, but existing firms are likely to bear most of these losses. In markets with Cournot competition, where producers act strategically, green certificates help to increase market competition if new firms are able to enter the market. Existing firms will not be motivated to compete with new generation capacity. The consumer surplus from introducing tradable green certificates under Cournot competition may increase, despite the deadweight losses the policy incurs.