Preliminary estimation of long-term storage needs in a system with electrified demands and 100% wind and solar electricity supply

Mark Barrett, Tiziano Gallo Cassarino and Ed Sharp

Introduction

This report was produced following a request for data and text input to the Royal Society report (2023) on long-term electricity storage.

This report describes modelling, mostly conducted 2017-2018, aimed at initially exploring the impact of long-term meteorology data on energy demands and renewable supply (here wind and solar), and thence on the need for energy storage.  The report first introduces the issue, a simple energy system, and storage theory and meteorology. Then a simple model is applied to this simple system. Simulation results are given and discussed. Finally, more complex modelling – a simple model has 100s of lines of code as compared to 1000s of lines- by the authors of more realistic systems is introduced, such as is required to resolve some of the limitations of the simple energy system and model. In particular, this more complex modelling includes interconnector trade which reduces storage need substantially.

A key problem faced by any energy system is to match variable demands and supplies at different locations hour by hour across the year. While fossil fuels dominate the energy supply mix, meeting variable demands is relatively straightforward because fossil fuels are stored energy. A more demanding problem for future UK low emission energy systems is to match variable demands and supplies over periods ranging from seconds to years, particularly where supply is dominated by renewables without integral storage such as solar and wind, or inflexible nuclear. In this report we are concerned with energy storage needed to accommodate long term (weeks to years) demand and renewable variations. There are three non-exclusive options for managing energy surpluses and deficits arising from variable renewable and inflexible nuclear generation:

1. Storage of primary energy (biomass, geothermal, etc.), or secondary energy (heat, cool, electricity, hydrogen, ammonia, etc.), or services (washed dishes, etc.) and products (e.g. iron).
2. Trade over long distance transmission lines to average demands and renewable outputs by dynamically exchanging local surpluses and deficits.
3. Deployment of increased renewable capacity enabling demands to be met at lower levels of incident resource (wind, solar radiation), but with increased renewable energy spillage and lower capacity factors.

In general, increasing one of these options allows a reduction one or two of the others. An objective is to find good designs with near optimal, least cost combination of these options such that constraints such as greenhouse gas emission targets are met – this is difficult to do and is not attempted here, but is in a paper by Gallo Cassarino and Barrett (Gallo Cassarino and Barrett, 2021). In this report, a simple model is used to start to explore the magnitude and drivers of energy flows and storage needs. There is no cost analysis here.

Banner photo credit: Alireza Attari on Unsplash