Optimal design of multi-utility complex for a low carbon city in China integrating renewable energy

Pan, Yiqun and Li, Yunming and Shi, Jie and Wang, Chunxiang and Jeong, Kwan Seok and Kim, Jaemin and Lee, Ji Young and Johnstone, Cameron and Hong, Jun and Park, Ji Young and Park, Gyoung Min; (2010) Optimal design of multi-utility complex for a low carbon city in China integrating renewable energy. In: Energy Systems Analysis, Thermodynamics and Sustainability; NanoEngineering for Energy; Engineering to Address Climate Change, Parts A and B. ASME 2010 International Mechanical Engineering Congress and Exposition, 5 . American Society of Mechanical Engineers (ASME), pp. 533-540. ISBN 9780791844298 (https://doi.org/10.1115/IMECE2010-40354)

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Abstract

There are many new city and district development projects ongoing in China, which are aimed at developing and building the low carbon emission cities of the future. The Energy Utilities sector is also facing new challenges from policy and regulations aimed at improving energy efficiency, adopting clean energy and mitigating environmental impact. As such, energy supply systems are becoming increasingly complex due to the installation and operation of multiple renewable energy systems. A Multi Utility Complex (MUC) has been proposed as a new and more effective way of constructing urban utility systems, in which facilities for utility services (e.g. energy supplies, water/sewage treatment and waste management plants) are physically installed at one site and managed by an integrated operating centre. When designing a MUC to be ‘cleaner’, more efficient and economical, determining an appropriate capacity of each component constituting the MUC is an essential and not trivial task due to the complexity of resource /energy flows and constraints associated with energy policy and regulations. To address this, an optimization design methodology has been adopted on the basis of a population-base optimization algorithm in support of cost-effective investment. The methodology is implemented in a software tool, ‘Plant Optimizer’, equipped with an urban utility demand profile modeller, the MUC package with different installation scenarios, analysis modules and reporting facility. This paper describes the optimizing methodology and functions of the software tool, and presents a case study to demonstrate the applicability.

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