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西安市污水再生利用系统的优化与发展趋势分析
徐志嫱1, 魏 红1, 黄廷林2
1.西安理工大学 西北水资源与环境生态教育部重点实验室;2.西安建筑科技大学 环境与市政工程学院
摘要:
[目的]探讨污水再生利用系统的发展趋势和投资需求.[方法]以污水再生利用系统为研究对象,建立了一个考虑技术、经济和政策因素的系统动力学(SD)与非线性优化(NLP)相结合的SD-NLP模型,对西安市污水再生利用系统的发展趋势进行了预测和优化分析.[结果]应按照城市发展的不同需求,在不同阶段对污水回用规划目标进行调整.西安市污水的回用率应达到45%左右,才能在不依靠远距离调水的情况下基本解决缺水问题.近期污水再生利用工程的投资需求较大,但也只占到同期GDP的0.035%左右,与西安市经济发展状况相比还是能够承受的.[结论]应用SD-NLP模型不仅能真实地模拟污水再生利用系统,对系统的发展势态进行分析和预测,而且可融入专家的经验,使预测结果具有较强的可行性,并提高了污水再生利用规划的科学性、合理性和经济性.
关键词:  污水再生利用系统  系统动力学  非线性优化  西安市
DOI:
分类号:
基金项目:国家自然科学基金项目(50138020)
System optimization and future trend analysis for wastewater reclamation and reuse in Xi'an
Abstract:
【Objective】 The city of Xi'an was selected as investigation area to discuss future trend and investment demand of wastewater reclamation and reuse. 【Method】 A SD-NLP model of system dynamics (SD) integrating with nonlinear programming with technological,economic and political constraints was established to carry out prediction and optimal analysis on future trend of wastewater reclamation and reuse in the city of Xi'an,based on wastewater reclamation and reuse system. 【Result】 The planning aims of wastewater reclamation and reuse should be adjusted according to local development in different phases.The problem of the water shortage would be solved without long distance water transfer when rate of wastewater reuse reaches about 45%.It would be the period with the greatest investment increase on wastewater reuse facilities in the near future.But the investment requirement only accounts for 0.035% of local GDP,and it is an acceptable number considering local economic development.【Conclusion】 The SD-NLP model not only could really simulate wastewater reclamation and reuse system and analysis the trend of system, but also fuse with the experience of experts,making the predicted conclusion feasible.Research results could be enhanced scientifically and reasonably and economically for wastewater reclamation and reuse planning. 
Key words:  wastewater reclamation and reuse system  system dynamics  nonlinear programming  Xi'an city