Energy System Optimization including Carbon-Negative Technologies for a High-Density Mixed-Use Development

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Wesley Bowley
Ralph Evins



In this paper, we use the ‘energy hub’ optimization model to perform a multi-objective analysis on a high-density mixed-use development (termed the ‘mothership’) under different scenarios and compare these results to appropriate base cases. These scenarios explore how the optimal energy system changes under different assumptions, including a high carbon tax, net metering, net-zero emissions and negative emissions, as well as two different electrical grid carbon intensities. We also include ‘carbon negative’ technologies involving biochar production, to explore the role that such processes can play in reducing the net emissions of energy systems. The annualized cost and total emissions of the mothership with a simple energy system are 4 and 8.7 times lower respectively than a base case using single detached homes housing the same population, due to the more efficient form and hence lower energy demand. Of the scenarios examined, it is notable that the case with the lowest annualized cost was one with a net-zero carbon emissions restriction. This gave an annualized cost of CAD 2.98M, which 36% lower than the base case annualized cost of CAD 4.66M. This relied upon the carbon negative production and sale of biochar. All scenarios examined had lower annualized costs than the base cases with many of the cases having negative operating costs (generating profit) due to the sale of renewable energy or carbon credits. This illustrates that the integration of renewable energy technologies is not only beneficial for reducing emissions but can also provide an income stream. These results give hope that suitably optimized urban developments may be able to implement low cost solutions that have zero net emissions.

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Bowley, W., & Evins, R. (2021). Energy System Optimization including Carbon-Negative Technologies for a High-Density Mixed-Use Development. International Journal of Sustainable Energy Planning and Management, 31, 211–225.