(717d) A Flexible Clustering Approach for Large-Scale Urban Energy-Water Nexus Optimization

With the background of continuous urbanization and global transformation of energy systems towards decentralized, smart and low carbon manners, the traditional supply-side oriented single-direction urban energy supply paradigm is out of date. The integrated urban energy system emerges, which integrates multiple energy sectors to satisfy the urban electricity, heating, cooling and gas demands simultaneously [1]. In addition, energy and water are recognized as two critical resources to maintain human livelihood, the energy-water nexus (EWN) system is increasingly important for urban planning and management. However, to determine the best design, with high accuracy solution, of the complicated energy-water nexus system is a challenge in the energy system research field. Hence, this study establishes an optimization model for the EWN system with a particular focus on the multi-scale modelling and optimization perspective. Efficient problem-solving strategies are proposed and comprehensive analysis is conducted for such a system to explore the best system design and dispatch strategies, so as to improve system’s economic performance.

The study tackles the key problem of modelling large-scale EWN by proposing an efficient problem-solving framework. A novel flexible clustering approach, which increases the flexibility of spatial decomposition, is proposed and further combined with multiple index assessments. By considering the complementarity effect and controlling the computational time, the proposed approach provides more flexible clustering options than conventional spatial decomposition approaches and can also balance the trade-off between accurate modeling and computational cost. Meanwhile, two efficient modelling and solving techniques are embedded to further improve the efficiency of the optimization process for the large-scale problem. Combined with domain knowledge, the redundant conditions can be removed and the solution space is also tightened. Therefore, solving efficiency of the optimization procedure can be significantly improved.

Through a case study, the proposed approach is verified that it can efficiently model and solve the optimization problem for the large-scale EWN. The whole district, in Shanghai, China, is re-clustered by the proposed flexible clustering procedure. Overall, 286 feasible clustering maps are generated that can meet the density and Coefficient of Variation (CV) value assessment and 45 clustering maps are selected after the computational time evaluation. Besides, based on the distributed energy system design mode, 6.74% cost savings can be further achieved compared to the design by conventional clustering approach with energy hub mode, and 3.2% savings compared to the conventional clustering approach with distributed mode.

Overall, the proposed approach with the results from the case study of this study is intended to be an efficient decision-support tool for EWN planning and sustainable development. Lower cost and more computationally efficient optimal system designs can be further achieved. Besides, by considering water usage of energy supply system, the study could release the pressure of ensuring urban energy security and increase the sustainability and comprehensiveness of city planning and management.

Reference:

[1] Ehsan A, Yang Q. Optimal integration and planning of renewable distributed generation in the power distribution networks: A review of analytical techniques. Applied Energy 2018;210:44–59.