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

Abstract

Primary and secondary energy mixes at regional and national scales vary greatly. • Some regional building types and industrial activities potentially save energy.• Interregional secondary energy flows, notably hydrogen, are massive.• System costs and energy infrastructure investments differ vastly across regions.

Impact analysis of COVID-19 pandemic on the future green power sector: A case study in the Netherlands

“…The investment costs are listed in Table 4 . The future fuel costs were based on projections calculated in previous studies [ 53 , 54 ]; they are presented in Table 5 . The CO 2 price was obtained from [ 55 ].…”

A data‐driven time‐step determination approach for dynamic simulation of heat‐electric coupled system

“…Power and temperature equation: the temperature of the water supply pipe will decrease (increase) at the load (source) node. The relationships can be represented by Equation (6).…”

“…FIGURE 6 Step of stepwise regression analysis Table 3 summarises the evaluation of results from the SR analysis model. The root mean square error (RMSE) of the fitted model is 13.6807 and the determination coefficient of model R-square is 0.934.…”

“…At present, the scale of HECS is gradually expanding all over the world and a number of countries and regions including China have introduced policies to promote HECS to replace the conventional system with the multi‐coupled energy system [5]. However, the rapid development also poses a greater challenge to the system stability and security, since a small parameter fluctuation can be widely spread due to the high coupling of the system [6]. Therefore, the simulation of HECS, which can provide a precise operational analysis, is essential for the development of HECS [7].…”

Quantifying energy transition pathways: an integrated framework approach

“…For instance, after identifying spatially sensitive parameters of the energy system, such as heat supply location, renewable power production, transmission capacity expansion, and storage infrastructure, Sahoo et al provide a framework to integrate them into an ESM (i.e. the OPERA model) [88]. Focusing on infrastructure, Van den Broek et al cluster the CO2 source regions using the ArcGIS software and then incorporate the spatially resolved data into the MARKAL-NL-UU as the optimization-based ESM [89].…”