Optimization of low-carbon multi-energy systems with seasonal geothermal energy storage: The Anergy Grid of ETH Zurich

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Optimization of low-carbon multi-energy systems with seasonal geothermal energy storage: The Anergy Grid of ETH Zurich

© 2020 The Author(s) We investigate the optimal operation of multi-energy systems deploying geothermal energy storage to deal with the seasonal variability of heating and cooling demands. We do this by developing an optimization model that improves on the state-of-the-art by accounting for the nonlinearities of the physical system, and by capturing both the short- and long-term dynamics of energy conversion, storage and consumption. The algorithm aims at minimizing the CO2 emissions of the system while satisfying the heating and cooling demands of given end-users, and it determines the optimal operation of the system, i.e. the mass flow rate and temperature of the water circulating through the network, accounting for the time evolution of the temperature of the geothermal fields. This optimization model is developed with reference to a real-world application, namely the Anergy Grid installed at ETH Zurich, in Switzerland. Here, centralized heating and cooling provision based on fossil fuels is complemented by a dynamic underground network connecting geothermal fields, acting as energy source and storage, and demand end-users requiring heating and cooling energy. The proposed optimization algorithm allows reducing the CO2 emissions of the university campus by up to 87% with respect to the use of a conventional system based on centralized heating and cooling. This improves on the 72% emissions reduction achieved with the current operation strategies. Furthermore, the analysis of the system allows to derive design guidelines and to explain the rationale behind the operation of the system. The study highlights the importance of coupling daily and seasonal energy storage towards the achievement of low-carbon energy systems.ISSN:0196-8904ISSN:1879-222

Carbon dioxide capture, transport and storage supply chains: Optimal economic and environmental performance of infrastructure rollout

This work presents a novel optimization framework for the optimal design of carbon capture, transport, and storage supply chains in terms of installation, sizing and operation of carbon dioxide (CO2) capture and transport technologies. The optimal design problem is formulated as a mixed-integer linear program that minimizes the total costs of the supply chains while complying with different emissions reduction pathways over a deployment time horizon of 25 years. All design decisions are time-dependent and are taken with a yearly resolution. Whereas the model is general, here its features are illustrated by designing optimal supply chains to decarbonize the Swiss waste-to-energy sector, for various emission reduction pathways, when up to two storage sites are considered, namely one in the North Sea assumed to be already available and a hypothetical one in Switzerland assumed to be possibly available in the future. Findings show that, unless a domestic storage site becomes available soon, the transport cost is the greatest contribution to the overall costs, followed by the capture cost, while the storage cost plays only a minor role. Pipelines are the most cost-effective mode of transport for large volumes of transported CO2, especially when considering multi-year time horizons for the planning of the supply chains. Ship and barge connections are competitive with pipeline connections, whereas rail and truck connections are cost-optimal only when considering shortsighted time horizons or small volumes of CO2 transported.ISSN:1750-5836ISSN:1878-014

Design and Multi-Objective Optimization of Co2 Value Chains for a Net-Negative Waste To Energy Sector: A Swiss Case Study

This study investigates the optimal design of CO2 value chains aimed at decarbonizing the waste to energy (WtE) sector on a national scale and presents the case study of Switzerland. Switzerland has 30 WtE plants that generate a total of 4.2 million tons of CO2 emissions per year. Half of these emissions are from biogenic sources and half are fossil-based, corresponding to 4.5% of the overall Swiss emissions. On the one hand, this indicates the relevance of decarbonizing the WtE sector. On the other hand, it implies that a net-negative-emissions WtE sector can be achieved by adopting carbon capture and storage (CCS) technologies. The CO2 value chains considered here consist in capturing CO2 at the WtE production sites, transporting it to the storage site, and permanently storing it underground. An optimization problem is formulated to determine the optimal design of the CO2 value chains in terms of size and location of carbon capture technologies, and structure of the network transporting the CO2 from the capture to the storage sites. The optimization algorithm is a mixed integer linear program that minimizes the total annual cost and CO2 emissions of the overall system. Several transport options are assessed, namely truck, train, pipeline and ship, as well as different transport paths