Performance optimization of CHP systems with co-simulation and intelligent control systems

利用协同仿真和智能控制系统优化热电联产系统的性能

• 批准号: 479473-2015
• 负责人: Gaber, Hossam
• 金额: $ 1.82万
• 依托单位: University of Ontario Institute of Technology
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=580093
• 关键词: Performance; optimization; CHP; systems; co

A well designed and maintained combined heat and power (CHP) plant can deliver significant economic and environmental benefits by reducing energy bills and CO2 emission. CHP can provide high performance energy supply with considerable return on investment (ROI) by investors, government, industries, as well as utilities and energy generation companies. In order to maximize the benefits of implementing CHP as a cogeneration energy supply system, it is important to monitor CHP performance, and optimize its operation and control. In order to achieve such a target, it is important to monitor CHP and evaluate its performance using a set of key performance indicators (KPIs) including costs, quality, environment, safety, and other performance criteria. The evaluation of KPIs can be used to evaluate design and operation scenarios to maximize the overall performance of CHP networks within industrial and commercial facilities and infrastructures. The concept of co-simulation will support the evaluation and tuning of CHP models so that it can be used along with real time data to optimize CHP performance as integrated with industrial systems from heat and power grids. CHP performance optimization can be achieved via adaptive control of variable demand of heat and power loads and map to the generation capabilities of CHP plants. The proposed CHP network infrastructure will be implemented using AC/DC micro energy grid with storage and distributed energy generation and resources that will be achieved. Intelligent control and fault tolerant control system design will be developed and evaluated to ensure high performance CHP systems along with high performance control systems. The proposed solution will consider performance degradation issues during the peak and off peak hours, and demand forecasting and demand side management of the integrated CHP-based micro energy grids. The overall system performance will be monitored and optimized.

一个设计和维护良好的热电联产（CHP）工厂可以通过减少能源费用和二氧化碳排放来提供显着的经济和环境效益。热电联产可以提供高性能的能源供应，投资者、政府、工业以及公用事业和能源发电公司的投资回报率（ROI）相当高。为了最大限度地发挥热电联产供能系统的效益，监测热电联产的性能，优化其运行和控制是非常重要的。为了实现这一目标，重要的是要使用一套关键绩效指标（KPI）来监控热电联产并评估其绩效，包括成本、质量、环境、安全和其他绩效标准。KPI的评估可用于评估设计和运行场景，以最大限度地提高工业和商业设施和基础设施内CHP网络的整体性能。协同仿真的概念将支持热电联产模型的评估和调整，以便它可以与真实的时间数据一起沿着使用，以优化热电联产性能，并与来自热和电网的工业系统集成。热电联产性能优化可以通过自适应控制热电负荷的变化需求来实现，并映射到热电联产工厂的发电能力。拟议的热电联产网络基础设施将使用具有存储和分布式能源发电的AC/DC微能源电网实施。智能控制和容错控制系统设计将被开发和评估，以确保高性能热电联产系统沿着高性能控制系统。拟议的解决方案将考虑高峰和非高峰时段的性能下降问题，以及基于CHP的集成微电网的需求预测和需求侧管理。将监测和优化整个系统的性能。