Network constraints in techno-economic energy system models: towards more accurate modeling of power flows in long-term energy system models

Nolden, Christoph; Schönfelder, Martin; Eßer-Frey, Anke; Bertsch, Valentin; Fïchtner, Wolf

doi:10.1007/s12667-013-0078-0

Cited by 20 publications

(16 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Also technological classifications can be made for different voltage levels or objectives of grid operation (e.g., transmission or distribution). Regarding mathematical models, resolutions range from detailed, nonlinear AC-power flow over decoupled and linear DC-power flow to simple transshipment or transport models [50].…”

Section: Technological Aggregationmentioning

confidence: 99%

Classification and Evaluation of Concepts for Improving the Performance of Applied Energy System Optimization Models

et al. 2019

View full text Add to dashboard Cite

Energy system optimization models used for capacity expansion and dispatch planning are established tools for decision-making support in both energy industry and energy politics. The ever-increasing complexity of the systems under consideration leads to an increase in mathematical problem size of the models. This implies limitations of today’s common solution approaches especially with regard to required computing times. To tackle this challenge many model-based speed-up approaches exist which, however, are typically only demonstrated on small generic test cases. In addition, in applied energy systems analysis the effects of such approaches are often not well understood. The novelty of this study is the systematic evaluation of several model reduction and heuristic decomposition techniques for a large applied energy system model using real data and particularly focusing on reachable speed-up. The applied model is typically used for examining German energy scenarios and allows expansion of storage and electricity transmission capacities. We find that initial computing times of more than two days can be reduced up to a factor of ten while having acceptable loss of accuracy. Moreover, we explain what we mean by “effectiveness of model reduction” which limits the possible speed-up with shared memory computers used in this study.

show abstract

Section: Technological Aggregationmentioning

confidence: 99%

Classification and Evaluation of Concepts for Improving the Performance of Applied Energy System Optimization Models

et al. 2019

View full text Add to dashboard Cite

show abstract

“…These balancing and technical restrictions are complemented by equations regarding the transmission grid [20], which is represented in the model by 560 transmission lines that connect all power stations and grid nodes. Each neighbouring country is depict via one grid node through which the electricity exchange to and from Germany can be set.…”

Section: Processmentioning

confidence: 99%

“…However, even so that it is a linear optimization model with only 46 timeslots representing a year the computing time of the model is still as long as a few days [19]. Furthermore, the growing feed-in of volatile renewable electricity leads to the need for a more detailed time structure and/or a better representation of the electricity grid [20], which would drastically increase computing time.…”

Section: Processmentioning

confidence: 99%

Reducing computing time of energy system models by a myopic approach

et al. 2013

Self Cite

View full text Add to dashboard Cite

In this paper, the performance of the existing energy system model PERSEUS-NET is improved in terms of computing time. Therefore, the possibility of switching from a perfect foresight to a myopic approach has been implemented. PERSEUS-NET is a linear optimization model generating scenarios of the future German electricity generation system until 2030, whilst considering exogenous regional characteristics such as electricity demand and existing power plants as well as electricity transmission network restrictions. Up to now, the model has been based on a perfect foresight approach, optimizing all variables over the whole time frame in a single run, thus determining the global optimum. However, this approach results in long computing times due to the high complexity of the problem. The new myopic approach splits the optimization into multiple, individually smaller, optimization problems each representing a 5 year period. The change within the generation system in each period is determined by optimizing the subproblem, whilst taking into account only the restrictions of that particular period. It was found that the optimization over the whole time frame with the myopic approach takes less than one tenth of the computing time of the perfect foresight approach. Therefore, we analyse in this paper the advantages and draw-backs of a change in the foresight as a way of reducing the complexity of energy system models. For PERSEUS-NET it is found that the myopic approach with stable input parameters is as suitable as the perfect foresight approach to generate consistent scenarios, with the advantage of significantly less computing time.

show abstract

“…national) energy system analyses (e.g. [407][408][409]). However, at the regional and municipal scale, as demonstrated by this review, they are typically not included.…”

Section: 21)mentioning

confidence: 99%

Reviewing energy system modelling of decentralized energy autonomy

Weinand

Scheller

McKenna

2020

Energy

View full text Add to dashboard Cite

Research attention on decentralized autonomous energy systems has increased exponentially in the past three decades, as demonstrated by the absolute number of publications and the share of these studies in the corpus of energy system modelling literature. This paper shows the status quo and future modelling needs for research on local autonomous energy systems. A total of 359 studies are roughly investigated, of which a subset of 123 in detail. The studies are assessed with respect to the characteristics of their methodology and applications, in order to derive common trends and insights. Most case studies apply to middle-income countries and only focus on the supply of electricity in the residential sector. Furthermore, many of the studies are comparable regarding objectives and applied methods. Local energy autonomy is associated with high costs, leading to levelized costs of electricity of 0.41 $/kWh on average. By analysing the studies, many improvements for future studies could be identified: the studies lack an analysis of the impact of autonomous energy systems on surrounding energy systems. In addition, the robust design of autonomous energy systems requires higher time resolutions and extreme conditions. Future research should also develop methodologies to consider local stakeholders and their preferences for energy systems.

show abstract

Network constraints in techno-economic energy system models: towards more accurate modeling of power flows in long-term energy system models

Cited by 20 publications

References 18 publications

Classification and Evaluation of Concepts for Improving the Performance of Applied Energy System Optimization Models

Classification and Evaluation of Concepts for Improving the Performance of Applied Energy System Optimization Models

Reducing computing time of energy system models by a myopic approach

Reviewing energy system modelling of decentralized energy autonomy

Contact Info

Product

Resources

About