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Smart Transient Gas Distribution Network Operations Advisor

Smart Transient Gas Distribution Network Operations Advisor
智能瞬态燃气分配网络运营顾问
批准号:
10004467
负责人:
金额:
$32.72万
依托单位:
依托单位国家:
英国
项目类别:
Collaborative R&D
财政年份:
2021
资助国家:
英国
项目状态:
已结题
起止时间:
2021 至 --

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中文摘要
翻译
英国政府已经确定,英国有潜力在提供智能能源供应系统方面引领世界,特别是那些与能源供需相匹配的系统。两个特别重要的领域是提高分布式发电一体化的便利性和成本,以及在地方、区域或全国范围内使用集成能源生产和需求的智能系统。Atmos国际有限公司(Atmos)是一家为石油、天然气、水和相关行业提供管道运行管理系统(包括模拟、气体管理和泄漏检测技术)的供应商。该公司总部位于英国曼彻斯特,已在60多个国家的数千条管道上实施了这些技术,其中包括壳牌、BP、埃克森美孚和道达尔等主要石油和天然气公司。“智能瞬态燃气分配网络运营顾问”(该项目)的目的是开发和评估一种新的软件解决方案,该解决方案使用机器学习(ML)和人工智能算法来优化天然气管道网络的运行,使其能够以最低成本运行,同时满足客户的全部需求。机器学习技术将包括处理意外情况,例如设备故障、泄漏、破坏等。这种方法将匹配天然气的供需状况。该软件将使供应商能够在地方、区域和全国范围内整合能源生产和需求。这种新方法带来的主要好处是:软件用户将可以访问智能实时燃气网络专家咨询系统,该系统就如何控制燃气输送网络提供建议,以实现长期改善的网络性能。它将降低天然气运输成本,同时确保达到所有运输服务水平协议/要求;-更快速和可靠的决策将有助天然气网络营办商尽量减少中断的后果,例如意外的气站关闭或其他事故。这将意味着提高人员安全,保护环境和天然气运输设备,节省财务成本。这种优化减少了燃料和能源消耗。此外,它在环境和经济上都很有吸引力;-最大限度地利用管道容量,同时在因意外事件导致供应短缺时满足合同要求。这将使天然气运输公司能够维持或增加销售,并避免罚款。
英文摘要
The UK Government has identified that the UK has the potential to lead the World in the provision of smart energy supply systems and specifically those that match energy supply and demand profiles. Two areas of particular significance are improving the ease and cost of integration of distributed generation and the use of smart systems that integrate energy generation and demand at local, regional or national scale. Atmos International Ltd (Atmos) is a supplier of pipeline operation management systems (including simulation, gas management and leak detection technology) to the oil, gas, water and associated industries. Headquartered in Manchester UK, the company has implemented these technologies on thousands of pipelines in over 60 countries, including major oil and gas companies such as Shell, BP, ExxonMobil, and Total.The aim of the 'Smart Transient Gas Distribution Network Operations Advisor' (the Project) is to develop and evaluate a new software solution that uses Machine Learning (ML) and Artificial Intelligence algorithms to optimise the operation of gas pipeline networks so that they can operate at minimum cost while meeting the full set of demands of their customers. The machine learning technology will include the handling of unexpected conditions e.g. equipment failure, leaks, sabotage, etc. This approach will match gas supply and demand profiles. The software will enable a supplier to integrate energy generation and demand at local, regional and national scale.The key benefits that accrue from this new approach are:- Users of the software will have access to a smart real-time gas network expert advisory system to provide recommendations on how to control their gas transport network to achieve long term improved network performance. It will reduce gas transportation costs whilst ensuring all transport service level agreements/requirements are achieved;- Faster and reliable decision making will help gas network operators minimise the consequences of interruptions e.g. unplanned station shutdowns or other incidents. This will mean improved safety of people, protection of the environment and gas transport equipment and saving of financial cost. The optimisation provides reduction of fuel and energy consumption. Also, it is both environmentally and economically attractive;- Maximised utilisation of the pipeline capacity whilst meeting the contractual requirements in event of supply shortages due to unplanned events. This would enable the gas transport companies to maintain or increase sales and avoid penalty payment.
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Transient Receptor Potential 通道 A1在膀胱过度活动症发病机制中的作用
  • 批准号:
    30801141
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    28.0万元
  • 批准年份:
    2008
  • 负责人:
    都书琪
  • 依托单位: