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Generation expansion planning considering health and societal damages - A simulation-based optimization approach

机译:考虑健康和社会损害的发电扩展计划-基于仿真的优化方法

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Electricity generation expansion planning models determine the optimal technology-capacity investment strategy that minimizes market costs including investment costs, and fixed and variable operating & maintenance costs over a long-term planning horizon. From a market cost perspective, fossil fuels are among the most economical sources of electricity, and thus are the primary sources of energy for electricity. However, these energy sources create by-products that have harmful health effects upon exposure. In this paper, a simulation-based, metamodeling approach is leveraged to quantify health damages associated with power grid expansion decisions by linking the outputs of generation expansion planning simulations with a screening tool that quantifies the human health damages from the electricity sector. Using this as a surrogate function for health damages, these costs are included in the objective function of a generation expansion planning model, in addition to market costs and the social damages of carbon emissions and methane leakage to minimize societal damages. Applying an improvement algorithm, candidate data points are selected to enhance metamodel prediction capability. Finally, using an updated metamodel, a new expansion plan is found. This framework enables researchers to better understand the health implications of long-term capacity expansion decisions. (C) 2018 Elsevier Ltd. All rights reserved.
机译:发电扩展计划模型确定了最佳的技术能力投资策略,该策略可将包括投资成本以及固定和可变运营与维护成本在内的市场成本降至最低。从市场成本的角度来看,化石燃料是最经济的电力来源之一,因此是电力的主要来源。但是,这些能源会产生副产品,这些副产品在暴露后会对健康产生有害影响。在本文中,通过将发电扩展计划模拟的输出与筛选工具链接在一起,该模型基于建模的元建模方法可用于量化与电网扩展决策相关的健康损害,该筛选工具可量化电力部门对人类健康造成的损害。使用此成本作为健康损害的替代功能,这些成本包括在市场扩展计划模型的目标函数中,此外还包括市场成本以及碳排放和甲烷泄漏的社会损害,以最大程度地减少社会损害。应用改进算法,选择候选数据点以增强元模型预测能力。最后,使用更新的元模型,找到新的扩展计划。该框架使研究人员可以更好地了解长期能力扩展决策对健康的影响。 (C)2018 Elsevier Ltd.保留所有权利。

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