Incorporating Power Transmission Bottlenecks into Aggregated Energy System Models

Cao, Karl‐Kiên; Metzdorf, Johannes; Birbalta, Sinan

doi:10.3390/su10061916

Cited by 21 publications

(13 citation statements)

References 42 publications

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“…The analyses for this study were conducted with two model setups which were partially extended. Although most of our analyses are performed for both of them, the results presented in Section 4 build on the REMix instance presented in [77]. The corresponding LP represents the German power system for an energy scenario of the year 2030.…”

Section: Modeling Setupmentioning

confidence: 99%

“…where: η e : fuel specific emissions and m: maximal emissions. In preliminary experiments resulting from a broad spectrum of REMix applications, ranging from country specific cross-sectoral energy systems [86,87] to multi-regional [85,[88][89][90] and spatially highly resolved power systems [77], for monolithic LPs, we observed the best performance in terms of computing time and RAM requirements with the following solver parameters when using CPLEX:…”

Section: Characteristic Constraintsmentioning

confidence: 99%

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

et al. 2019

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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.

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Section: Modeling Setupmentioning

confidence: 99%

Section: Characteristic Constraintsmentioning

confidence: 99%

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

et al. 2019

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“…More precisely, to plan energy systems, we use an advanced ESOM called the "Renewable Energy Mix for a sustainable energy supply" (REMix). Today's applications range from country-specific cross-sectoral energy system analyses (Gils et al, 2017b) to multi-regional powersystem analyses of high spatial resolution (Cao et al, 2018). The modeling approach and the essential functionalities of the model are described in Gils et al (2017a).…”

Section: Methodsmentioning

confidence: 99%

To Prevent or Promote Grid Expansion? Analyzing the Future Role of Power Transmission in the European Energy System

et al. 2021

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Future energy supply systems must become more flexible than they are today to accommodate the significant contributions expected from intermittent renewable power sources. Although numerous studies on planning flexibility options have emerged over the last few years, the uncertainties related to model-based studies have left the literature lacking a proper understanding of the investment strategy needed to ensure robust power grid expansion. To address this issue, we focus herein on two important aspects of these uncertainties: the first is the relevance of various social preferences for the use of certain technologies, and the second is how the available approaches affect the flexibility options for power transmission in energy system models. To address these uncertainties, we analyze a host of scenarios. We use an energy system optimization model to plan the transition of Europe’s energy system. In addition to interacting with the heating and transport sectors, the model integrates power flows in three different ways: as a transport model, as a direct current power flow model, and as a linearized alternating current power flow model based on profiles of power transfer distribution factors. The results show that deploying transmission systems contribute significantly to system adequacy. If investments in new power transmission infrastructure are restricted—for example, because of social opposition—additional power generation and storage technologies are an alternative option to reach the necessary level of adequacy at 2% greater system costs. The share of power transmission in total system costs remains widely stable around 1.5%, even if cost assumptions or the approaches for modeling power flows are varied. Thus, the results indicate the importance of promoting investments in infrastructure projects that support pan-European power transmission. However, a wide range of possibilities exists to put this strategy into practice.

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“…Kies et al [14] for instance found that insufficient transmission capacities might cause large amounts of renewable generation to be curtailed. Consequently, Cao et al * corresponding author: Bruno Schyska (bruno.schyska@dlr.de) [15] suggested to incorporate transmission bottlenecks directly into energy system models. Similar to the optimal mix of generation sources, there is a well-known interaction between transmission and storage [16].…”

Section: Introductionmentioning

confidence: 99%

How regional differences in cost of capital influence the optimal design of power systems

Schyska¹,

Kies

2020

Applied Energy

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In order to reduce greenhouse gas emissions of the power sector, high shares of renewable power sources need to be integrated into existing systems. This will require vast amounts of investments. Cost of the capital needed for these investments are unevenly distributed among European regions. They show a clear North-South and West-East divide, which has not exhibited significant signs of narrowing in recent years. Power system studies investigating a continent-wide European power system, however, usually assume homogeneous cost of capital.The objective of this paper is to investigate how regional differences in cost of capital affect the result of these studies with respect to the optimal power system design. Our analysis is based on power system optimization with inhomogeneous cost of capital in Europe. We find that assuming homogeneous cost of capital leads to estimates on the levelized costs of electricity in a highly renewable European power system, which are too conservative. The optimal system design is significantly affected compared to an inhomogeneous scenario. In particular, we show that inhomogeneous cost of capital favors overall wind power deployment in the case of Europe, while the investment in solar power decreases.

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Incorporating Power Transmission Bottlenecks into Aggregated Energy System Models

Cited by 21 publications

References 42 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

To Prevent or Promote Grid Expansion? Analyzing the Future Role of Power Transmission in the European Energy System

How regional differences in cost of capital influence the optimal design of power systems

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