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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领先世界,特别是那些符合能源供需状况的系统。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,以及使用在地方、区域或国家范围内整合能源生产和需求的智能系统。Atmos International Ltd(Atmos)是一家为石油、天然气、水和相关行业提供管道运营管理系统(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、“智能瞬态配气网络运营顾问”的目标是(该项目)是开发和评估一个新的软件解决方案,使用机器学习(ML)和人工智能算法,以优化天然气管道网络的运营,使其能够以最低的成本运营,同时满足客户的全套需求。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。该软件将使供应商能够在地方、区域和国家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:-该软件的用户将可以访问智能实时天然气网络专家咨询系统,就如何控制其天然气运输网络提供建议,以实现长期改善的网络性能。它将降低天然气运输成本,同时确保实现所有运输服务水平协议/要求;-更快和可靠的决策将有助于天然气网络运营商最大限度地减少中断的后果,例如计划外的站关闭或其他事件。这将意味着改善人员安全、保护环境和天然气运输设备以及节省财务成本。优化提供了减少燃料和能源消耗。此外,它在环境和经济上都具有吸引力;-最大限度地利用管道容量,同时在由于计划外事件导致供应短缺的情况下满足合同要求。这将使天然气运输公司能够保持或增加销售量,并避免支付罚款。
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: