奥兰多公用事业委员会（OUC）最近完成了一项最新技术的开发- 艺术设施自动化和信息管理（FAIM）系统- 带有控制和信息的时间监控和数据采集（SCADA） 管理系统，连接整个水系统。FAIM系统 最近获得了佛罗里达咨询工程师协会工程大奖 卓越，允许单个操作员监控整个系统的产水量 系统FAIM提供的全系统自动化和控制为OUC提供了 调查和实施实时分配泵和处理的机会 通过将FAIM SCADA连接到近实时运行的水力优化模型进行调度 时间 OUC希望调查实时决策支持工具，以允许操作员选择 最经济的设备组合，包括OUC的水处理和 分配设施，以满足任何给定条件下的系统压力和流量需求 时间点。人们希望决策支持工具能够考虑 操作设备和电力成本，在某些设施，这些成本现在或将来可能会有所不同 未来，取决于高峰需求或罚款。 OUC的FAIM顾问CH2M HILL协助OUC评估提供服务的方法 OUC水系统运行的持续能源优化，考虑以下因素: 维持服务的可靠性和质量，预测治疗和泵送成本，以及 提供工具，帮助运营商选择经济高效的治疗和优质服务 抽水策略。根据研究结果，详细的能源标准 建立了优化系统。 在回顾了包括人工神经网络、基于规则的 优化、遗传算法优化和自适应需求预测系统， OUC决定用一个 可与所提供的SCADA系统动态链接的泵调度模块 一种经济有效的方法，帮助运营商确定最有效的 各种条件下的操作场景（潮湿天气、干燥天气、异常天气） 需求、断线等。 ) 本文描述了OUC在评估和实现实时性方面的经验 供水系统优化建模，包括规划和评估、试点 测试和实现。包括表格、数字。

The Orlando Utilities Commission (OUC) recently completed development of a state-of-the- art Facility Automation and Information Management (FAIM) system, which integrates real- time Supervisory Control and Data Acquisition (SCADA) with control and information management systems, interconnecting the entire water system. The FAIM system, which recently won the Florida Institute of Consulting Engineers Grand Award for Engineering Excellence, allows a single operator to monitor and control water production for the entire system. The system wide automation and control provided by FAIM afforded OUC the opportunity to investigate and implement real time distribution pump and treatment scheduling by linking the FAIM SCADA to a hydraulic optimizing model running in near real time. OUC desired to investigate real time decision support tools to allow operators to select the most economical combination of equipment, amongst OUC's water treatment and distribution facilities, to meet system pressure and flow demand requirements at any given point in time. It was desired that the decision support tool should account for the cost to operate equipment and the cost of power, which, at some facilities may vary now, or in the future, depending upon peak demand or penalty charges. OUC's FAIM consultant, CH2M HILL, assisted OUC in evaluating approaches for providing ongoing energy optimization of OUC's water system operations with considerations for maintaining reliability and quality of service, forecasting treatment and pumping costs, and providing tools to assist operators in selecting cost effective treatment and high service pumping strategies. Based upon the results of the study, detailed criteria for an energy optimization system were established. After reviewing various options including Artificial Neural Networks, Rule Based Optimization, Genetic Algorithm Optimization and Adaptive Demand Predictive Systems, OUC determined that enhancing their existing water distribution hydraulic model with a pump scheduling module that could be dynamically linked to the SCADA system provided an economical and effective means to assisting operators in determining the most effective operating scenarios under a variety of conditions (wet weather, dry weather, unusual demand, line breaks, etc.) This paper describes OUC's experience in evaluating and implementing real time modeling for water distribution system optimization including planning and evaluation, pilot testing and implementation. Includes tables, figures.