Requirements for Integrated Planning of Multi-Energy Systems

Thie, Nicolas; Franken, Marco; Schwaeppe, Henrik; Böttcher, Luis; Muller, Christoph; Moser, Albert; Schumann, Klemens; Vigo, Daniele; Monaci, Michele; Paronuzzi, Paolo; Punzo, Antonio; Pozzi, M.; Gordini, Angelo; Cakirer, Kemal Burak; Acan, Burcin; Desideri, Umberto; Bischi, Aldo

doi:10.1109/energycon48941.2020.9236466

Cited by 6 publications

(2 citation statements)

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“…Required scenario assumptions have been derived from the Agora study Towards a Climate-Neutral Germany by 2045 [39] and Germany's grid development plan ("Netzentwicklungsplan") for the year 2040 [40]. Data preparation has been designed in line with the requirements explained in [41] and prepared according to the scenario framework outlined in [42]. Data processing has been carried out in the workflow described in [43] and offers the integration of additional datasets, if required later.…”

Section: Datamentioning

confidence: 99%

Analyzing Intersectoral Benefits of District Heating in an Integrated Generation and Transmission Expansion Planning Model

et al. 2022

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In the field of sector integration, the expansion of district heating (DH) is traditionally discussed with regard to the efficient integration of renewable energy sources (RES) and excess heat. But does DH exclusively benefit from other sectors or does it offer advantages in return? So far, studies have investigated DH only as a closed system or determined intersectoral benefits in a highly aggregated approach. We use and expand an integrated generation and transmission expansion planning model to analyze how the flexibility of DH benefits the energy system and the power transmission grid in particular. First of all, the results confirm former investigations that show DH can be used for efficient RES integration. Total annual system cost can be decreased by expanding DH, due to low investment cost and added flexibility, especially from large-scale heat storage. The high short-term efficiency of heat storage—in combination with electric heating technologie —can be exploited to shift heat demand temporally and, using multiple distributed units, locally to solve electric grid congestion. Although it is unclear whether these results can be replicated in the real world, due to the aggregation and detail of the model, further research in this direction is justified.

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Section: Datamentioning

confidence: 99%

Analyzing Intersectoral Benefits of District Heating in an Integrated Generation and Transmission Expansion Planning Model

et al. 2022

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“…For this purpose, multi-energy systems usually consist of many components. Due to the resulting complexity, the optimal design and operation of multi-energy systems are best addressed by optimization models (Mancarella, 2014;Andiappan, 2017;Thie et al, 2020). Optimization models represent the input-output relationship of each component to capture its operation.…”

Section: Introductionmentioning

confidence: 99%

AutoMoG 3D: Automated Data-Driven Model Generation of Multi-Energy Systems Using Hinging Hyperplanes

et al. 2021

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The optimal operation of multi-energy systems requires optimization models that are accurate and computationally efficient. In practice, models are mostly generated manually. However, manual model generation is time-consuming, and model quality depends on the expertise of the modeler. Thus, reliable and automated model generation is highly desirable. Automated data-driven model generation seems promising due to the increasing availability of measurement data from cheap sensors and data storage. Here, we propose the method AutoMoG 3D (Automated Model Generation) to decrease the effort for data-driven generation of computationally efficient models while retaining high model quality. AutoMoG 3D automatically yields Mixed-Integer Linear Programming models of multi-energy systems enabling efficient operational optimization to global optimality using established solvers. For each component, AutoMoG 3D performs a piecewise-affine regression using hinging-hyperplane trees. Thereby, components can be modeled with an arbitrary number of independent variables. AutoMoG 3D iteratively increases the number of affine regions. Thereby, AutoMoG 3D balances the errors caused by each component in the overall model of the multi-energy system. AutoMoG 3D is applied to model a real-world pump system. Here, AutoMoG 3D drastically decreases the effort for data-driven model generation and provides an accurate and computationally efficient optimization model.

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Digital Energy: Towards Comprehensive Digital Support for a Renewable-Based Energy Sector

Jarke

Andres

Mirz

et al. 2022

Communications in Computer and Information Science

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Requirements for Integrated Planning of Multi-Energy Systems

Cited by 6 publications

References 5 publications

Analyzing Intersectoral Benefits of District Heating in an Integrated Generation and Transmission Expansion Planning Model

Analyzing Intersectoral Benefits of District Heating in an Integrated Generation and Transmission Expansion Planning Model

AutoMoG 3D: Automated Data-Driven Model Generation of Multi-Energy Systems Using Hinging Hyperplanes

Digital Energy: Towards Comprehensive Digital Support for a Renewable-Based Energy Sector

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