Delivering power system decision support tools over the web
Delivering power system decision support tools over the web
复制标题
通过网络提供电力系统决策支持工具
DOI：
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发表时间：
2010
期刊：
影响因子：
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通讯作者：
K. V. Prasad
中科院分区：
文献类型：
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作者：
Mehul Shah;R. Vaishnav;Narayanan Rajagopal;K. V. Prasad
世界各地的公用事业公司都使用基于独立架构的内部部署软件的决策支持工具，当需要扩展其应用程序以满足新的业务需求时，这些工具会受到攻击。这些应用程序的可访问性仅限于特定的操作环境，从而导致在正确的地点和时间提供有限的信息以支持决策制定。与金融服务、银行等其他行业不同，电力行业尚未充分利用互联网技术的优势，实现高效运营。在一个旨在支持开放访问的放松管制的系统中，决策必须是透明的，它需要许多参与者的参与，这些参与者的行为受到各种利益的支配，从有利可图的贸易一直到系统操作的安全性。特别是可以预见的是，决策支持工具的部署应使其能够在任何地方和任何时间访问。这导致了为电力系统分析计算引入软件即服务[21]模型的工作——利用互联网提供随时随地的访问。这项工作将体系结构扩展到其他电力系统决策支持工具，使它们基于SaaS模型在web上可用。提出了基于智能电网成熟度模型（SGMM）的公用事业智能电网成熟度评估工具。本文还研究了基于云计算的虚拟化和托管选项。
Utilities world over use decision support tools based on in-premise software with standalone architecture and suffer vulnerability when needing to extend their application to meet new business requirements. Accessibility of these applications are limited to specific operating environments resulting in restricted information being available at the right place and time to support decision making. Unlike other sectors such as Financial Services, Banking etc., power sector is yet to leverage the benefits of the internet technologies for efficient operations. In a deregulated system designed to support open access, decision making has to be transparent and it requires participation of many players whose behavior is governed by diverse interests from profitable trade all the way to security in system operations. In particular it is foreseen that decision support tools should be so deployed that they can be accessed from anywhere and at any time. This led to the work on introducing Software-as-a-Service [21] model for power system analysis computations — using the internet to provide access from anywhere and at any time. This work extends the architecture to other power system decision support tools to make them available over the web based on the SaaS model. Tools to evaluate Smart Grid Maturity of the utilities based on the Smart Grid Maturity Model (SGMM) are proposed. Cloud computing based virtualization and hosting options are also examined.