Optimal Use of Grid-Connected Energy Storage to Reduce Human Health Impacts

该项目将开发新的方法，通过有针对性地使用并网储能，减轻电力部门排放对人类健康的不利影响。蓄电池或抽水蓄能水电等储能设备可以根据其充放电策略改变电力部门排放的时间和地点。二氧化硫(SO2)和氮氧化物(NOx)等标准污染物对人类健康的总体影响与排放的时空分布密切相关。将解决的首要研究问题是：并网储能的运营策略能否以成本效益的方式减少电力部门排放对人类健康的影响？为了回答这个问题，研究团队将开发一个带有储能的机组组合和经济调度模型，以确定电力系统的最佳运行，并提供机组水平的SO2和NOx排放。最先进的空气污染化学传输模型和敏感性分析技术将用于提供发电厂和储能调度决策产生的PM2.5和臭氧浓度的空间和时间分辨率。人类健康损害成本估算将根据接触这些二次污染物的变化确定健康反应，将这些结果与统计寿命的价值结合起来，并确定与初级排放相关的单位水平边际健康损害成本。这些成本然后作为电力系统模型的输入，以便进行实时决策，有效地将排放的外部性成本内部化，并产生能量存储的最佳充放电行为，以经济高效地减少对人类健康的影响。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This project will develop new methods to mitigate adverse human health impacts from power sector emissions through the targeted use of grid-connected energy storage. Energy storage devices, such as batteries or pumped storage hydropower, can shift both the time and location of power sector emissions based on their charging and discharging strategies. The overall human health impacts of criteria pollutants such as sulfur dioxide (SO2) and oxides of nitrogen (NOx) are closely related to the both temporal and spatial distribution of emissions. The overarching research question that will be addressed is: Can operational strategies for grid-connected energy storage yield cost-effective reductions in the human health impacts associated with power sector emissions?To answer this question, the research team will develop a unit commitment and economic dispatch model with energy storage to determine optimal power system operations and provide unit-level SO2 and NOx emissions. A state-of-the-science air pollution chemical transport model and sensitivity analysis technique will be used to provide spatially- and temporally-resolved PM2.5 and O3 concentrations stemming from power plant and energy storage dispatch decisions. Human health damage cost estimates will determine the health response from changes in exposure to these secondary pollutants, coupling those results with the value of a statistical life and determine the unit-level marginal health damage costs associated with the primary emissions. Those costs then serve as inputs into the power system model to allow real-time decision making, effectively internalizing the externality costs of the emissions and yielding the optimal charge/discharge behavior of the energy storage to cost-effectively reduce human health impacts.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.