Abstract
Integrated energy system modeling tools predominantly focus on the (inter)national or local scales. The intermediate level is important from the perspective of regional policy making, particularly for identifying the potentials and constraints of various renewable resources. Additionally, distribution variations of economic and social sectors, such as housing, agriculture, industries, and energy infrastructure, foster regional energy demand differences. We used an existing optimization-based national integrated energy system model, Options Portfolio for Emission Reduction Assessment or OPERA, for our analysis. The modeling framework was subdivided into four major blocks: the economic structure, the built environment and industries, renewable energy potentials, and energy infrastructure, including district heating. Our scenario emphasized extensive use of intermittent renewables to achieve low greenhouse gas emissions. Our multi-node, regionalized model revealed the significant impacts of spatial parameters on the outputs of different technology options. Our case study was the northern region of the Netherlands. The region generated a significant amount of hydrogen (H2) from offshore wind, i.e. 620 Peta Joule (PJ), and transmitted a substantial volume of H2 (390 PJ) to the rest of the Netherlands. Additionally, the total renewable share in the primary energy mix of almost every northern region is ∼90% or more compared to ∼70% for the rest of the Netherlands. The results confirm the added value of regionalized modeling from the perspective of regional policy making as opposed to relying solely on national energy system models. Furthermore, we suggest that the regionalization of national models is an appropriate method to analyze regional energy systems.
Highlights
Developing a low-carbon energy system necessitates attention to various spatial dimensions [1]
Our focus was on the northern part of the Netherlands (NNL), we considered the entire country because energy in frastructures are strongly interconnected at the national level, and other infrastructures, such as carbon, capture, and storage (CCS) are defined at this level
Our modeling was based on four themes: the regional economic structure, modeling mod ifications of the built environment and industries, regional potential or capacity allocation of renewables, and the creation of energy in frastructures
Summary
Developing a low-carbon energy system necessitates attention to various spatial dimensions [1]. Area-based and bottom-up strategies are crucial for improving regional environments and stakeholders’ interac tion in the pursuit of a low-carbon energy system [3]. Such strategies are especially critical in densely populated areas where high energy de mands and a lack of spaces can lead to serious competition over land use and instigate societal resistance. This situation applies to the Netherlands [4], which is the location of our study
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