A regional energy system transition modeling tool for decision support:a case study of the Groningen province in the Northern Netherlands

Regionalized national models are uncommon in energy system modeling and analysis. The regional level is vital because this scale assists in identifying the spatial and energy potentials of renewable energy sources. In addition, spatial planning is crucial for energy system transition and typically occurs on a local to regional level. This study created a regional decision-supporting energy system modeling tool using an existing national integrated energy system model named OPERA. The case study was the Dutch province of Groningen. Four systematic methodological steps were followed. First, a crude regionalization framework was created within OPERA. Second, renewable spatial potential was analyzed by modeling with geographic information system-based tools. Third, a regional decision-support tool was developed by adding a spatial interface to the energy system modeling framework. Fourth, this tool was tested and validated by developing stakeholder-informed scenarios and discussing the outcomes in a stakeholder workshop. Important quantitative outcomes of the tool are regional primary energy supply mixes, secondary energy demand balances, interregional energy flows, and related cost structures. The results showed that energy infrastructure is a crucial component of the total system cost. Onshore wind and biomass can play a significant role in the future regional energy system of Groningen, subject to regional and national policies and public perception. The framework can analyze trade-offs, conflicts, and complementarity between stakeholder opinions and perspectives. The stakeholder interaction process highlighted the importance of the science-policy interface. The method is universal and can be applied to other regional contexts, subject to data availability

Process design of cryogenic system using ASPENHYSYS simulation

The thermodynamic efficiency of any process is dependant upon following factors: (a) The efficiency of independent components used. (b) Operating condition i.e. variation of input parameter(like temperature, Pressure etc) To improve the efficiency of any process, efficiency of component is fixed (it is dependant upon level of technology available and cost of equipment), thus we are left with optimizing operating condition which is under our control. This paper presents analysis of thermodynamic cycle commonly used for liquefaction of Nitrogen (N2) under given set of operating condition and efficiencies. The liquefying temperature of Nitrogen being 77.36K is taken into consideration. The cycles considered are: (a) Simple LINDE-HAMPSON cycle (b) CLAUDE cycle Computer-aided process design programs, often referred to as process simulators, flow sheet simulators, or flow sheeting packages, are widely used in process design. Aspen HYSYS by Aspen Technology is one of the major process simulators that are widely used in chemical and thermodynamic process industries today. It specializes on steadystate analysis. System simulation is the calculation of operating variables such as pressure, temperature and flow rates of energy and fluids in a thermal system operating in a steady state. The equations for performance characteristics of the components and thermodynamic properties along with energy and mass balance form a set of simultaneous equations relating the operating variables. The mathematical description of system simulation is that of solving these set of simultaneous equations which may be non-linear in nature. Cryogenics is the branch of engineering that is applied to very low temperature refrigeration applications such as in liquefaction of gases and in the study of physical phenomenon at temperature of absolute zero. The various cryogenic cycles as LINDE cycle, CLAUDE cycle etc govern the liquefaction of various industrial gases as Nitrogen,Helium etc. The following work aims to simulate the cryogenic cycles with the help of the simulation tool ASPEN HYSYS where all calculations are done at steady state and the results hence obtained

Detailed spatial analysis of renewables’ potential and heat:A study of Groningen Province in the northern Netherlands

Spatially sensitive regional renewables’ potentials are greatly influenced by existing land-use claims and related spatial and environmental policies. Similarly, heat particularly related to low-temperature demand applications in the built environment (BE) is highly spatially explicit. This study developed an analytical approach for a detailed spatial analysis of future solar PV, onshore wind, biomass, and geothermal and industrial waste heat potentials at a regional level and applied in the Dutch Province of Groningen. We included spatial policies, various spatial claims, and other land-use constraints in developing renewable scenarios for 2030 and 2050. We simultaneously considered major spatial claims and multiple renewable energy sources. Claims considered are the BE, agriculture, forest, nature, and network and energy infrastructure, with each connected to social, ecological, environmental, technical, economic, and policy-related constraints. Heat demand was further analyzed by creating highly granular demand density maps, comparing them with regional heat supply potential, and identifying the economic feasibility of heat networks. We analyzed the possibilities of combining multiple renewables on the same land. The 2050 renewable scenarios results ranged 2–66 PJ for solar PV and 0–48 PJ for onshore wind and biomass ranged 3.5–25 PJ for both 2030 and 2050. These large ranges of potentials show the significant impact of spatial constraints and underline the need for understanding how they shape future energy policies. The heat demand density map shows that future heat networks are feasible in large population centers. Our approach is pragmatic and replicable in other regions, subject to data availability

Regionalization of a national integrated energy system model:A case study of the northern Netherlands

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

Detailed spatial analysis of renewables’ potential and heat: A study of Groningen Province in the northern Netherlands

Spatially sensitive regional renewables’ potentials are greatly influenced by existing land-use claims and related spatial and environmental policies. Similarly, heat particularly related to low-temperature demand applications in the built environment (BE) is highly spatially explicit. This study developed an analytical approach for a detailed spatial analysis of future solar PV, onshore wind, biomass, and geothermal and industrial waste heat potentials at a regional level and applied in the Dutch Province of Groningen. We included spatial policies, various spatial claims, and other land-use constraints in developing renewable scenarios for 2030 and 2050. We simultaneously considered major spatial claims and multiple renewable energy sources. Claims considered are the BE, agriculture, forest, nature, and network and energy infrastructure, with each connected to social, ecological, environmental, technical, economic, and policy-related constraints. Heat demand was further analyzed by creating highly granular demand density maps, comparing them with regional heat supply potential, and identifying the economic feasibility of heat networks. We analyzed the possibilities of combining multiple renewables on the same land. The 2050 renewable scenarios results ranged 2–66 PJ for solar PV and 0–48 PJ for onshore wind and biomass ranged 3.5–25 PJ for both 2030 and 2050. These large ranges of potentials show the significant impact of spatial constraints and underline the need for understanding how they shape future energy policies. The heat demand density map shows that future heat networks are feasible in large population centers. Our approach is pragmatic and replicable in other regions, subject to data availability

Regionally integrated energy system detailed spatial analysis: Groningen Province case study in the northern Netherlands

Regional level energy system analyses and corresponding integrated modeling is necessary to analyze the impact of national energy policies on a regional level, while considering regional constraints related to energy infrastructure, energy supply potentials, sectoral energy demands, and their interactions. Nevertheless, current literature on energy system analysis largely overlooks the regional level. In response, this study provided a systematic approach to refining and improving the spatial resolution of an existing regional energy system modeling framework. The methodology involved creating regions and nodes within the modeling framework under categories corresponding to land use (cities and other regions), energy supply, and energy infrastructure. We established a unidirectional soft linking with geographical information system-based modeling results allocating spatially sensitive elements, such as renewable resources or heat demand. We provided a detailed breakdown of sectoral energy demand, supply options, and energy infrastructure for electricity and heat, including district heating (DH). This framework explicated regional differences in terms of demand–supply mismatch, supply options, and energy infrastructure. Our case study of the Dutch province of Groningen demonstrated clear differences compared to the previous crude regional model, with, e.g., an increased role of biomass (+460 % change) and decreased role of solar (−59 %), while cities with high heat demand densities and/or compact structures exhibited serious DH penetration, ranging from 11 to 21 %. The systematic steps allow for the replication of the model in other regional analyses. Our framework is complementary for energy system analysis at the national and pan-European levels and can assist regional policymakers in decision-making

Geographical Information System-based detailed spatial analysis of onshore renewable space source potentials and heat demand: a regional case study of Groningen province in the northern Netherlands: Datasets and Supplementary materials

These data are used in the model. Input data include current land use, electricity, network infrastructure, protected areas, and other infrastructure (airport, inland water, and the built environment). Output layers include future land use, geothermal, and other infrastructure (grid structure heat demand (100 m X 100 m)). Input data include all the important layers that are used for identifying renewable potentials for all the scenarios. For future analysis, future land use data is also used as input

Regionally integrated energy system detailed spatial analysis: Groningen Province case study in the northern Netherlands

Regional level energy system analyses and corresponding integrated modeling is necessary to analyze the impact of national energy policies on a regional level, while considering regional constraints related to energy infrastructure, energy supply potentials, sectoral energy demands, and their interactions. Nevertheless, current literature on energy system analysis largely overlooks the regional level. In response, this study provided a systematic approach to refining and improving the spatial resolution of an existing regional energy system modeling framework. The methodology involved creating regions and nodes within the modeling framework under categories corresponding to land use (cities and other regions), energy supply, and energy infrastructure. We established a unidirectional soft linking with geographical information system-based modeling results allocating spatially sensitive elements, such as renewable resources or heat demand. We provided a detailed breakdown of sectoral energy demand, supply options, and energy infrastructure for electricity and heat, including district heating (DH). This framework explicated regional differences in terms of demand–supply mismatch, supply options, and energy infrastructure. Our case study of the Dutch province of Groningen demonstrated clear differences compared to the previous crude regional model, with, e.g., an increased role of biomass (+460 % change) and decreased role of solar (−59 %), while cities with high heat demand densities and/or compact structures exhibited serious DH penetration, ranging from 11 to 21 %. The systematic steps allow for the replication of the model in other regional analyses. Our framework is complementary for energy system analysis at the national and pan-European levels and can assist regional policymakers in decision-making

Regionalization of a national integrated energy system: A case study of the northern Netherlands

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

Detailed spatial analysis of renewables’ potential and heat: A study of Groningen Province in the northern Netherlands

Spatially sensitive regional renewables’ potentials are greatly influenced by existing land-use claims and related spatial and environmental policies. Similarly, heat particularly related to low-temperature demand applications in the built environment (BE) is highly spatially explicit. This study developed an analytical approach for a detailed spatial analysis of future solar PV, onshore wind, biomass, and geothermal and industrial waste heat potentials at a regional level and applied in the Dutch Province of Groningen. We included spatial policies, various spatial claims, and other land-use constraints in developing renewable scenarios for 2030 and 2050. We simultaneously considered major spatial claims and multiple renewable energy sources. Claims considered are the BE, agriculture, forest, nature, and network and energy infrastructure, with each connected to social, ecological, environmental, technical, economic, and policy-related constraints. Heat demand was further analyzed by creating highly granular demand density maps, comparing them with regional heat supply potential, and identifying the economic feasibility of heat networks. We analyzed the possibilities of combining multiple renewables on the same land. The 2050 renewable scenarios results ranged 2–66 PJ for solar PV and 0–48 PJ for onshore wind and biomass ranged 3.5–25 PJ for both 2030 and 2050. These large ranges of potentials show the significant impact of spatial constraints and underline the need for understanding how they shape future energy policies. The heat demand density map shows that future heat networks are feasible in large population centers. Our approach is pragmatic and replicable in other regions, subject to data availability