4.8 Article

The multi-energy system co-planning of nearly zero-energy districts - Status-quo and future research potential

Journal

APPLIED ENERGY
Volume 267, Issue -, Pages -

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.apenergy.2020.114953

Keywords

Multi-Energy systems; Expansion; Operation; Modeling; Zero-Energy districts; Renewable energy

Funding

  1. M4_LAB
  2. Federal Ministry of Education and Research [03IHS032A]

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The deep-decarbonization of local energy systems is vital to achieving our climate protection obligations. To that effect, the existence of energy modeling and simulation tools that provide accurate planning insights is imperative. The coupling of multiple energy vectors increase the flexibility of the local energy system and increase the renewable energy hosting capacity. The added-benefits of multi-energy systems comprise the reliability of energy supply, improve the socio-economic value proposition of decentralized and renewable technologies, and reduce the environmental impacts of energy use. The simultaneous consideration of the expansion planning requirements and the operational details of the energy system becomes mandatory when the variable renewable energy generation significantly increases. This review focuses on the multi-energy system co-planning in nearly zero-energy districts. We discuss how the temporal representation of multi-energy system co-planning models influence the optimal sizing and scheduling of resources. We also look at the existing methods of representing distributed generators and energy network and their limitations. Thirdly, we discuss the significance of spatial resolution and how open data models, such as CityGML, can enable more comprehensive multi-energy scenario modeling. Above all, we highlight the limitations of the existing models to adequately represent and evaluate the addedvalue streams associated with multi-energy systems in a nearly zero-energy district. The review examines several research gaps, such as investigating the influence of temporal resolution in multi-energy system models, integration of spatial and topological details of districts, detailed distributed-technology models, accurate network models, and integrating the transportation sector.

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