Potential of demand side integration to maximize use of renewable energy sources in Germany

Stötzer, Martin; Hauer, Ines; Richter, Marc; Styczynski, Zbigniew A.

doi:10.1016/j.apenergy.2015.02.015

Cited by 50 publications

(21 citation statements)

References 26 publications

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“…A genetic algorithm for DR modelling is presented in [19]. It is applied to an assessment of theoretical DR potentials of residential and commercial loads in a representative model region in Germany.…”

Section: State Of Knowledgementioning

confidence: 99%

Economic potential for future demand response in Germany – Modeling approach and case study

Gils

2016

Applied Energy

133

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The activation of demand response (DR) potentials offered by electricity consumer flexibility is one promising option for providing balancing power and energy in supply systems with high share of variable renewable energy (VRE) power generation. In this paper, a model-based assessment of the economic DR potential in Germany is presented. It relies on the extension of the REMix energy system model by flexible electric loads. In a case study considering a future German power supply system with a VRE share of 70%, possible cost reductions achieved by investment in DR are quantified. The sensitivity of the results to changes in the assumed DR costs and characteristics are analysed in additional simulations. The results show that the major benefit of employing DR is its ability to substitute peak power generation capacity, whereas the impact on the integration of VRE power generation is lower. This implies that the focus of DR is on the provision of power, not energy. Even at rather pessimistic cost DR assumptions, more than 5 GW of power plant capacity can be substituted. Consumer flexibility furthermore triggers an increase in the operation of backup power plants, whereas it decreases the utilization of pumped storage hydro stations. In the model results, the reductions in annual power supply costs achieved by DR add up to several hundreds of millions of Euros.

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Section: State Of Knowledgementioning

confidence: 99%

Economic potential for future demand response in Germany – Modeling approach and case study

Gils

2016

Applied Energy

133

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“…GA-based method is used for single and multiple objective optimization to match distribution system's controlled resources with the operator's objectives based on controlled resources sensitivities and operational costs [26]. Furthermore, GA is applied to identify the optimum shifting of a load block (part of the load profile) to reduce peak load while ensuring the minimum disruption to the commercial and residential loads [27]. GA is also used to optimize three objective functions, namely, minimized operational cost, minimized operational unsafely, and minimized operational delays using an energy management system [28].…”

Section: Introductionmentioning

confidence: 99%

Coordinated Operation of the Constituent Components of a Community Energy System to Maximize Benefits While considering the Network Constraints

Wijethunge

Wijayakulasooriya

Ekanayake

et al. 2019

Journal of Electrical and Computer Engineering

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Smart community with locally generated renewable energy is a new paradigm that leads to a system that is more sustainable, secure, and cost-effective to the community while enabling connection of more distributed energy resources. In this paper, a method to maximize the utilization of the renewables while maximizing the profit of a smart community within system constraints was suggested by introducing an optimum schedule of smart appliances in the community. Further dynamic line rating of the network connection is considered to investigate the advantage of using the dynamic rating against static rating. Different operating modes based on the variations of available renewable energy generation, wind speed, tariff, grid curtailment, and user preferences were investigated. A modified genetic algorithm-based optimization was implemented to obtain the optimum smart community’s appliance schedule. The optimum appliance schedules were obtained considering different case studies representing possible operating modes of the system. The simulations show that the use of dynamic line rating and optimum appliance schedule provide higher profit to the community. The algorithm managed to run the optimization with 12,500 controllable entities within an average execution time of 2000s.

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“…Many of these works consider real-time or hourly pricing: e.g. analysing heating and cooling in Texas [24], household appliances in Ireland [25] and Germany [26,27] or storage-like loads under German [28] and Danish [29] conditions. Static prices simplify the analysis of different retail pricing structures, which might be the reason that besides real-time pricing also many analyses of simpler rate structures have been performed.…”

Section: Introductionmentioning

confidence: 99%

Load-shift incentives for household demand response: Evaluation of hourly dynamic pricing and rebate schemes in a wind-based electricity system

Katz

Andersen

Morthorst

2016

Energy

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Potential of demand side integration to maximize use of renewable energy sources in Germany

Cited by 50 publications

References 26 publications

Economic potential for future demand response in Germany – Modeling approach and case study

Economic potential for future demand response in Germany – Modeling approach and case study

Coordinated Operation of the Constituent Components of a Community Energy System to Maximize Benefits While considering the Network Constraints

Load-shift incentives for household demand response: Evaluation of hourly dynamic pricing and rebate schemes in a wind-based electricity system

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