Analyzing Demand Response in a Dynamic Capacity Expansion Model for the European Power Market

Marañón-Ledesma, Héctor; Tomasgård, Asgeir

doi:10.3390/en12152976

Cited by 24 publications

(7 citation statements)

References 43 publications

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“…EMPIRE is a capacity expansion model with one investment stage and one operational stage. EMPIRE has been used in several different publications [28]- [31] and in European and national research projects [27]. The model represents the EU-27 plus Switzerland, Norway, the UK, Bosnia and Herzegovina, Serbia, and North Macedonia.…”

Section: A the Empire Modelmentioning

confidence: 99%

Consequences of Uncertainty from Intraday Operations to a Capacity Expansion Model of the European Power System

Wendelborg,

Backe,

del Granado

et al. 2023

2023 19th International Conference on the European Energy Market (EEM)

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The European Energy Transition envisions a high deployment of variable renewable energy sources (VRES) by 2050. Some estimates expect that 60-to-70% of power generation will be entirely covered by VRES technologies (i.e., solar and wind). This creates challenges for balancing VRES with conventional, flexible generation (e.g., gas and storage). Consequently, VRES are transforming how electricity markets will operate and how balancing needs between day-ahead (DA) and intraday (ID) electricity markets are coordinated. The importance of the ID market increases due to the uncertain short-term nature of VRES. However, there is limited research on how forecasting errors in between market stages affect investment decisions in capacity expansion problems. In this paper, we investigate how an increased amount of uncertainty from forecasting errors between a DA and an ID market affects investment decisions in the power system. We have developed a multi-horizon stochastic capacity expansion model containing both DA and ID markets under uncertainty. The model emulates the European power system developments under given emission targets of EU policies towards 2050. In the comparison of the standard single market approach to the market sequencing, the results indicate: 1.) Forecasting errors significantly impact investment decisions, resulting in 10% lower VRES investments and 40% higher flexible capacity investments, 2.) Cross-border transmission is a crucial contributor to flexibility and volume increases by 10-20% when accounting for forecasting errors, 3.) investment needs for storage capacity decrease significantly compared to an over-valuation in the standard method of capacity expansion models.

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Section: A the Empire Modelmentioning

confidence: 99%

Consequences of Uncertainty from Intraday Operations to a Capacity Expansion Model of the European Power System

Wendelborg,

Backe,

del Granado

et al. 2023

2023 19th International Conference on the European Energy Market (EEM)

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“…The detailed analyses of DSF are of particular interest in the present context (Mishra et al, 2016;Andersen et al, 2006;Matar, 2017;Ali et al, 2015;Li and Pye, 2018;Grohnheit and Klavs, 2000;Tveten et al, 2016;Katz et al, 2016;Marañón-Ledesma and Tomasgard, 2019). They consider load shifting (reducing demand at a given price level) or peak clipping (reducing peak demand where the demand appears later on), or both, for either the electricity sector alone, or for both the electricity and heating sectors.…”

Section: Previous Studies Of Demand-side Flexibilitymentioning

confidence: 99%

Analyzing the energy system impacts of price-induced demand-side-flexibility with empirical data

McKenna

Hernando

Brahim

et al. 2021

Journal of Cleaner Production

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This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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“…4. Breakpoints in the cost function, as well as other details, are defined based on studies of variable costs of enduser appliances [33,34].…”

Section: ) Costs Of Flexibility Assetsmentioning

confidence: 99%

The Impact of Uncertainty and Time Structure on Optimal Flexibility Scheduling in Active Distribution Networks

et al. 2021

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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 flexibility assets, the authors show the impact of uncertainty and time structure on a scheduling problem. The uncertainties considered are price and load levels. The findings reveal that the quality of the scheduling of each flexibility resource depends on using a stochastic model with a rigorous consideration of time and uncertainty.INDEX TERMS Flexibility, active distribution networks, optimal power flow, scheduling, stochastic programming, uncertainty. NOMENCLATURE

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Analyzing Demand Response in a Dynamic Capacity Expansion Model for the European Power Market

Cited by 24 publications

References 43 publications

Consequences of Uncertainty from Intraday Operations to a Capacity Expansion Model of the European Power System

Consequences of Uncertainty from Intraday Operations to a Capacity Expansion Model of the European Power System

Analyzing the energy system impacts of price-induced demand-side-flexibility with empirical data

The Impact of Uncertainty and Time Structure on Optimal Flexibility Scheduling in Active Distribution Networks

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