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优化能源供应

在能源网中,要满足各个能源消费者的需求并最大程度减少能源投入的成本,就会涉及许多方面,包括各类能源供应、交易和存储组件(例如变电站、电池、风电场、太阳能电池板、微型涡轮机)以及需求响应报价。为此,在考虑请求不同类型的资源的成本,及每种资源的容量和物理特性后,能源网运营商必须确定每种能源在一段时间内应产生多少能量。

该解决方案以 Cortana Intelligence Suite 和外部开源工具为基础,可计算各类能源的最佳能源机组组合。该解决方案展示了 Cortana Intelligence Suite 兼容外部工具,在 Azure 虚拟机的 Azure Batch 上解决并行数值优化问题的能力。

Energy Supply OptimizationIn an energy grid, energy consumers are engaged with various types of energy supplying, trading, and storage components such as substations, batteries, windfarms and solar panels, micro-turbines, as well as demand response bids, to meet their respective demands and minimize the cost of energy commitment. To do so, the grid operator must determine how much energy each type of the resources should commit over a time frame, given the prices of soliciting different types of resources and the capacities and the physical characteristics of them.

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Energy Supply OptimizationIn an energy grid, energy consumers are engaged with various types of energy supplying, trading, and storage components such as substations, batteries, windfarms and solar panels, micro-turbines, as well as demand response bids, to meet their respective demands and minimize the cost of energy commitment. To do so, the grid operator must determine how much energy each type of the resources should commit over a time frame, given the prices of soliciting different types of resources and the capacities and the physical characteristics of them.

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