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A Scalable Energy-Economy Model for State-Level Policy Analysis Applied to a Demand-Side Management Program

机译:一种可扩展的能量 - 经济性模型,用于施加侧管理计划的国家级政策分析

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摘要

Over the past two decades, states and cities implemented low-carbon energy development, renewable portfolio standards, demand-side management (DSM), renewable energy production incentives, green building requirements, regional carbon trading agreements, and other energy-based economic development initiatives. Yet the dearth of state-level and substate-level models makes it difficult to predict the effects of such actions. This article addresses this shortcoming by presenting the performance results of the new Indiana Scalable Economy and Energy Model (IN-SEEM)-a model utilizing a dynamic, simultaneous equations framework-and demonstrates the model's capabilities with an analysis of electricity price increases from a DSM program in the state of Indiana. Overall performance of the model is strong, with high adjustedR(2)values and low mean absolute percent errors for most of 30 endogenous variables. A DSM price increase analysis finds variation in impact across the state's 10 major economic sectors and small changes in energy consumption.
机译:在过去的二十年中,各国和城市实施了低碳能源发展,可再生组合标准,需求侧管理(DSM),可再生能源生产激励措施,绿色建筑要求,区域碳交易协议和其他能源的经济发展举措。然而,状态级和子级模型的缺乏使得难以预测这些行为的影响。本文通过呈现新印第安纳可扩展经济和能源模型(In-Sems)-A模型的绩效结果,利用动态,同步等式框架 - 并演示模型的能力与DSM的电价增加印第安纳州的计划。该模型的整体性能强,具有高调整型(2)值和大部分内源性变量的低平均绝对误差。 DSM价格增加分析发现该州10个主要经济部门的影响和能源消耗的小变化。

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