highRES-Europe: The high spatial and temporal Resolution Electricity System model for Europe

The high spatial and temporal resolution electricity system model, highRES, is used to design cost-effective, flexible and weather resilient electricity systems for Great Britain and Europe. The model is specifically designed to analyse the effects of high shares of variable renewables and explore integration/flexibility options. As the proportion of renewables in electricity generation increases, there will be increasing imbalances between electricity demand and supply. highRES is a high-resolution electricity system model that simultaneously considers infrastructure planning (investment) and operational (dispatch) decisions to identify the most cost-effective strategies to cope with growing shares of intermittent renewables. It does this by comparing and trading off potential options to integrate renewables into the system including the extension of the transmission grid, interconnection with other countries, building flexible generation (e.g. gas power stations), renewable curtailment and energy storage. highRES is written in GAMS and its objective is to minimise power system investment and operational costs to meet hourly demand, subject to a number of unit and system constraints. It can model a variety of technical characteristics of thermal generators (e.g. ramping restrictions, minimum stable generation, startup costs, minimum up and down times) depending on the requirements of the research question, their CO2 emissions, and the technical characteristics of a variety of energy storage options. The transmission grid is represented using a linear transport model

Intersecting near-optimal spaces: European power systems with more resilience to weather variability

We suggest a new methodology for designing robust energy systems. For this, we investigate so-called near-optimal solutions to energy system optimisation models; solutions whose objective values deviate only marginally from the optimum. Using a refined method for obtaining explicit geometric descriptions of these near-optimal feasible spaces, we find designs that are as robust as possible to perturbations. This contributes to the ongoing debate on how to define and work with robustness in energy systems modelling. We apply our methods in an investigation using multiple decades of weather data. For the first time, we run a capacity expansion model of the European power system (one node per country) with a three-hourly temporal resolution and 41 years of weather data. While an optimisation with 41 weather years is at the limits of computational feasibility, we use the near-optimal feasible spaces of single years to gain an understanding of the design space over the full time period. Specifically, we intersect all near-optimal feasible spaces for the individual years in order to get designs that are likely to be feasible over the entire time period. We find significant potential for investment flexibility, and verify the feasibility of these designs by simulating the resulting dispatch problem with four decades of weather data. They are characterised by a shift towards more onshore wind and solar power, while emitting more than 50% less CO2 than a cost-optimal solution over that period. Our work builds on recent developments in the field, including techniques such as Modelling to Generate Alternatives (MGA) and Modelling All Alternatives (MAA), and provides new insights into the geometry of near-optimal feasible spaces and the importance of multi-decade weather variability for energy systems design. We also provide an effective way of working with a multi-decade time frame in a highly parallelised manner. Our implementation is open-sourced, adaptable and is based on PyPSA-Eur

A renewable power system for an off-grid sustainable telescope fueled by solar power, batteries and green hydrogen

A large portion of astronomy's carbon footprint stems from fossil fuels supplying the power demand of astronomical observatories. Here, we explore various isolated low-carbon power system setups for the newly planned Atacama Large Aperture Submillimeter Telescope, and compare them to a business-as-usual diesel power generated system. Technologies included in the designed systems are photovoltaics, concentrated solar power, diesel generators, batteries, and hydrogen storage. We adapt the electricity system optimization model highRES to this case study and feed it with the telescope's projected energy demand, cost assumptions for the year 2030 and site-specific capacity factors. Our results show that the lowest-cost system with LCOEs of $116/MWh majorly uses photovoltaics paired with batteries and fuel cells running on imported and on-site produced green hydrogen. Some diesel generators run for backup. This solution would reduce the telescope's power-side carbon footprint by 95% compared to the business-as-usual case.Comment: 16 pages, 10 figure

Machine Learning of Public Sentiments toward Wind Energy in Norway

Across Europe negative public opinion has and may continue to limit the deployment of renewable energy infrastructure required for the transition to net-zero energy systems. Understanding public sentiment and its spatio-temporal variations is as such important for decision-making and socially accepted energy systems. In this study, we apply a sentiment classification model based on a machine learning framework for natural language processing, NorBERT, on data collected from Twitter between 2006 and 2022 to analyse the case of wind power opposition in Norway. From the 68828 tweets with geospatial information, we show how discussions about wind power intensified in 2018/2019 together with a trend of more negative tweets up until 2020, both on a regional level and for Norway as a whole. Furthermore, we find weak geographical clustering in our data, indicating that discussions are country wide and not dominated by specific regional events or developments. Twitter data allows for detailed insight into the temporal nature of public sentiments and extending this research to additional case studies of technologies, countries and sources of data (e.g. newspapers, other social media) may prove important to complement traditional survey research and the understanding of public sentiment.Comment: 31 pages, 36 figures, 2 table

The direct interconnection of the UK and Nordic power market – Impact on social welfare and renewable energy integration

United Kingdom and the Nordic power market have plans to interlink directly through a sub-sea power transmission line in The North Sea. Such power market couplings have complicated implications for the interconnected energy systems and for different agents in the common power market. We analyse this case by modelling the hourly operation of the Nordic-UK power market coupling, considering the local district heating (DH) system in each country as well. According to the results, after the operation of the new interconnection between Norway and the UK (North Sea Link), the overall socio-economic benefits (social welfare) in the region will likely improve by 220–230 million euro per year, without considering the cost of the interconnector itself. The UK-Nordic market coupling enhances the flexibility of the UK power system in wind integration, irrespective of the share of wind in the Nordic countries. However, increasing wind capacity in the UK will diminish the expected economic benefits of the link. The merit order effect of wind integration in the UK will reduce the price gap between UK and Norway, and so the congestion income of the link in many hours a year when the link is congested from Norway towards the UK

Spatially and Temporally Explicit Energy System Modelling to Support the Transition to a Low Carbon Energy Infrastructure -Case Study for Wind Energy in the UK

ABSTRACT Renewable energy sources and electricity demand vary with time and space and the energy system is constrained by the location of the current infrastructure in place. The transitioning to a low carbon energy society can be facilitated by combining long term planning of infrastructure with taking spatial and temporal characteristics of the energy system into account. There is a lack of studies addressing this systemic view. We soft-link two models in order to analyse long term investment decisions in generation, transmission and storage capacities and the effects of short-term fluctuation of renewable supply: The national energy system model UKTM (UK TIMES model) and a dispatch model. The modelling approach combines the benefits of two models: an energy system model to analyse decarbonisation pathways and a power dispatch model that can evaluate the technical feasibility of those pathways and the impact of intermittent renewable energy sources on the power market. Results give us the technical feasibility of the UKTM solution from 2010 until 2050. This allows us to determine lower bounds of flexible elements and feeding them back in an iterative process (e.g. storage, demand side control, balancing). We apply the methodology to study the long-term investments of wind infrastructure in the United Kingdom

Sustainable Astronomy: A comparative Life Cycle Assessment of Off-grid Hybrid Energy Systems to supply large Telescopes

Purpose Supplying off-grid facilities such as astronomical observatories with renewable energy-based systems (RES) instead of diesel generators can considerably reduce their environmental impact. However, RES require oversized capacities to counter intermittency and comply with reliability requirements, hence shifting the environmental impact from operation to construction phase. We assess whether 100% RES scenarios are favorable from an environmental point of view, and discuss the trade-offs in systems with backup fossil generators versus 100% renewable ones. Methods In this comparative life cycle assessment (LCA), we study various RES supply systems to power a new telescope in the Atacama desert, Chile. We compare six setups, including 100% RES scenarios, namely photovoltaics (PV) with batteries and hydrogen energy storage; high-renewable scenarios, with fossil fuel power generation next to RES and storage; and a system combining PV with diesel generation. We base system sizing on a techno-economical optimization for the start of operation in 2030. Foreground data stem from recent life cycle inventories of RES components and 2030 electricity mix assumptions of production places. We assess environmental impact in the categories climate change, mineral resource depletion and water use. Results and discussion We find that 100% RES and high-renewable scenarios result in emissions of 0.077-0.115kg CO2e/kWh supplied, compared to 0.917kg CO2e/kWh in the reference case with solely diesel generation. 100% RES scenarios have a lower CO2e impact than high-renewable scenarios. However, the latter lower the mineral resource depletion and water use by about 27% compared to 100% RES scenarios. Applying hybrid energy storage systems increases the water use impact, while reducing the mineral resource depletion. Conclusions None of the six energy systems we compared was clearly the best in all environmental impacts considered. Trade-offs must be taken when choosing an energy system to supply the prospective off-grid telescope in Chile. We find high-renewable systems with some fossil generation as the better option regarding power reliability, mineral resource depletion and water use, while inducing slightly higher greenhouse gas emissions than the 100% RES scenarios. As remote research facilities and off-grid settlements today are mainly supplied by fossil fuels, we expect to motivate more multifaceted decisions for implementing larger shares of RES for these areas. To advance the LCA community in the field of energy systems, we should strive to incorporate temporal and regional realities into our life cycle inventories. To ease the path for upcoming studies, we publish this work’s inventories as detailed activity level datasets

Exploring urban metabolism—Towards an interdisciplinary perspective

© 2017 The Author(s) The discussion on urban metabolism has been long dominated by natural scientists focussing on natural forces shaping the energy and material flows in urban systems. However, in the anthropocene human forces such as industrialization and urbanization are mobilizing people, goods and information at an increasing pace and as such have a large impact on urban energy and material flows. In this white paper, we develop a combined natural and social science perspective on urban metabolism. More specifically, innovative conceptual and methodological interdisciplinary approaches are identified and discussed to enhance the understanding of the forces that shape urban metabolism, and how these forces affect urban living and the environment. A challenging research agenda on urban metabolism is also presented