(128d) An Integrated Demand and Supply Modeling Approach for the Energy System Design of a New Urban Area

Cities dominate energy demand. The world’s urban areas agglomerate 55% of the population (UN DESA, 2018), close to 2/3 of global primary energy consumption, and more than 70% of greenhouse gas emissions (World Bank, 2019). Large-scale energy use is causing severe energy problems, including local and regional pollution, global climate change, and energy security (Johansson et al., 2012). The urbanization trend is expected to continue, with world’s cities growing in both size and number (UN DESA, 2018). Energy systems in new urban areas can have a huge impact in reducing or even eliminating the negative environmental externality and at the same time satisfying the increasing energy demand.

Urban energy systems can be defined as the combined process of energy extraction, conversion, transmission and distribution, storage, and end-use to meet the energy service demand in a given urban area (Jaccard, 2006; Keirstead et al., 2012; Blok & Nieuwlaar, 2016). In energy system design studies, energy demand data are often inputted exogenously, while many studies focus on the retrofit of existing urban energy systems (Keirstead et al., 2012). However, for the development of a new urban area, the prediction of energy demand would be vital. Xiong’an is a new urban area under planning and construction in Hebei, China, and aims in developing safe, green, and efficient energy systems. An integrated model for urban energy systems design of new urban areas is needed to address the theoretical and practical problems and achieve the development goal.

In this work, we developed an urban energy system design tool that is able to provide the optimal energy system design and operation plan for the development of a new urban area. The urban area is divided into several clusters to grasp the demand and supply patterns in each subarea and to show energy flow inside the city. For the demand side, we implemented activity-based energy demand prediction, deriving building energy demand from observing occupants’ activity patterns. For the supply side, a superstructure framework is developed that contains different options for energy sources, energy conversion and storage technologies and energy networks. The resulting integrated supply and demand model is represented as a mixed-integer linear model that can be solved to global optimality. Furthermore, multi-objective optimization is implemented to reveal the trade-offs among economic costs, greenhouse gas emissions, and air pollution. The developed framework will be demonstrated through case studies, illustrating the capabilities of the proposed tool as a good test bed for technical decisions or policy scenarios in a newly developing urban area.

References:

Blok, K., Nieuwlaar, E., 2016. Introduction to energy analysis. Routledge.

Jaccard, M., 2006. Sustainable fossil fuels: the unusual suspect in the quest for clean and enduring energy. Cambridge University Press.

Johansson, T.B., Patwardhan, A., Nakićenović, L., Gómez-Echeverri, L., 2012. Global Energy Assessment: Toward a Sustainable Future. Cambridge University Press, Cambridge UK.

Keirstead, J., Jennings, M., Sivakumar, A., 2012. A review of urban energy system models: Approaches, challenges and opportunities. Renewable and Sustainable Energy Reviews, 16(6), 3847-3866.

United Nations, Department of Economic and Social Affairs, Population Divi­sion, 2018. The World’s Cities in 2018—Data Booklet (ST/ESA/ SER.A/417).

World Bank, 2019. Urban Development. Available at: https://www.worldbank.org/en/topic/urbandevelopment/overview (Accessed: 10 April 2019)