Abstract
In this paper, we explore how effectively renewable generation can be used to meet a country’s electricity demands. We consider a range of different generation mixes and capacities, as well as the use of energy storage. First, we introduce a new open-source model that uses hourly wind speed and solar irradiance data to estimate the output of a renewable electricity generator at a specific location. Then, we construct a case study of the Great Britain (GB) electricity system as an example using historic hourly demand and weather data. Three specific sources of renewable generation are considered: offshore wind, onshore wind, and solar PV. Li-ion batteries are considered as the form of electricity storage. We demonstrate that the ability of a renewables-based electricity system to meet expected demand profiles can be increased by optimising the ratio of onshore wind, offshore wind and solar PV. Additionally, we show how including Li-ion battery storage can reduce overall generation needs, therefore lowering system costs. For the GB system, we explore how the residual load that would need to be met with other forms of flexibility, such as dispatchable generation sources or demand-side response, varies for different ratios of renewable generation and storage.
Highlights
Many countries, including the United Kingdom (UK), are moving towards net carbon dioxide neutrality by 2050, where any emissions of man-made CO2 are compensated for by negative emissions from greenhouse gas removal technologies
At the same time, increased use of electricity in transport and heating to displace existing fossil fuel alternatives is increasing demand for electricity generation and transmission, requiring more low-carbon electricity to be produced in a way that is balanced with consumer demand [2,3]
This paper looks at the requirements to balance generation and load in a UK based fully renewable electricity generation system using a mixture of both renewables and electricity storage
Summary
Many countries, including the United Kingdom (UK), are moving towards net carbon dioxide neutrality by 2050, where any emissions of man-made CO2 are compensated for by negative emissions from greenhouse gas removal technologies. The profiles generated are compared to a one-hour resolution demand model to get a reliability metric of the system for meeting overall consumer demand This model allows us to be uniquely able to answer the question ’what percentage of time can demand be met with a mix of renewables and storage at certain deployment levels?’. The Electricity System Model is still in development, but is intended to include various other functions to provide overall system analysis This will include modelling technology costs, and a system optimiser, which will seek the combination of generation and storage installed capacities that achieves the lowest overall system cost while still meeting required reliability levels. Details of this will be published in future work
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