The strong effect of network resolution on electricity system models with high shares of wind and solar

Martha Maria Frysztacki,Jonas Hörsch,Veit Hagenmeyer,Tom Brown

doi:10.1016/j.apenergy.2021.116726

Martha Maria Frysztacki, Jonas Hörsch + Show 2 more

Open Access

https://doi.org/10.1016/j.apenergy.2021.116726

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Abstract

Energy system modellers typically choose a low spatial resolution for their models based on administrative boundaries such as countries, which eases data collection and reduces computation times. However, a low spatial resolution can lead to sub-optimal investment decisions for wind and solar generation. Ignoring power grid bottlenecks within regions tends to underestimate system costs, while combining locations with different wind and solar capacity factors in the same resource class tends to overestimate costs. We investigate these two competing effects in a capacity expansion model for Europe’s power system with a high share of renewables, taking advantage of newly-available high-resolution datasets as well as computational advances. We vary the number of nodes, interpolating between a 37-node model based on country and synchronous zone boundaries, and a 1024-node model based on the location of electricity substations. If we focus on the effect of renewable resource resolution and ignore network restrictions, we find that a higher resolution allows the optimal solution to concentrate wind and solar capacity at sites with better capacity factors and thus reduces system costs by up to 10% compared to a low resolution model. This results in a big swing from offshore to onshore wind investment. However, if we introduce grid bottlenecks by raising the network resolution, costs increase by up to 23% as generation has to be sourced more locally at sites with worse capacity factors. These effects are most pronounced in scenarios where grid expansion is limited, for example, by low local acceptance. We show that allowing grid expansion mitigates some of the effects of the low grid resolution, and lowers overall costs by around 16%.

Highlights

Electricity systems with high shares of wind and solar photovoltaic generation require a fundamentally different kind of modelling to conventional power systems with only dispatchable generation [63]
If we focus on the effect of renewable resource resolution and ignore network restrictions, we find that a higher resolution allows the optimal solution to concentrate wind and solar capacity at sites with better capacity factors and reduces system costs by up to 10% compared to a low resolution model
We demonstrate the methodology by running simulations in a model of the future European electricity system with a higher spatial resolution than has Martha Maria et al.: Preprint submitted to Elsevier

Summary

Introduction

Electricity systems with high shares of wind and solar photovoltaic generation require a fundamentally different kind of modelling to conventional power systems with only dispatchable generation [63]. While investments in conventional power plants can be dimensioned according to simple heuristics like screening curves [10], the assessment of wind and solar resources requires a high temporal and spatial resolution to capture their weather-driven variability. It has been recognized that integrating renewable resources on a continental scale can smooth large-scale weather variations, from wind [23], and avoid the need for temporal balancing. This smoothing effect has been found in studies of the benefits of grid expansion both in Europe, where the impact on balancing needs [53] and storage requirements [55] has been analysed,

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