(399a) Planning of Electricity Unit Commitment in Synergy with Nature’s Ability to Mitigate Carbon Dioxide and Criteria Air Pollutants

In 1970, the establishment of Clean Air Act (CAA) and Environmental Protection Agency (EPA) marked a breakthrough of the U.S. government to protect human health and environment by mandating the levels of air pollution.¹ The emissions of several precursor air pollutants have dropped over years of efforts, however, currently there are still 4.2 million people dying each year due to exposure to outdoor (or ambient) air pollution according to World Health Organization (WHO).² 2022 EPA Air Trends Report shows that most of the emissions are coming from stationary fuel combustion sources and industrial processes.³ Additionally, CO₂ as a large contributor to greenhouse effect, its emission rate from fossil fuels has reached 37.12 billion tons in 2021, increased by 5.28% from year 2020.⁴ CO₂ emissions from electricity generation and industry are still the largest portion over all sectors.⁵ Unit Commitment (UC) is solved as an optimization problem to find the optimal hourly operations of multiple electricity generating plants. In recent years, researchers have started to incorporate environmental factors into this problem by imposing constraints on emissions and setting up separate goals for human health impacts.^6-8 However, their results are only based on additional objectives or constraints associated with emission control by using industrial pollutant removal technologies. Trees are natural air filters which can take up large amount of air pollutants⁹ when properly planted, and they can be designed as unit operations to improve air quality and mitigate greenhouse gases. Some work^10–12 focused on Techno-Ecological Synergy (TES) which combines the operations of forests and modern emission removal technologies to treat air pollutants coming from manufacturing plants, however, they either did not consider the operations of the plant itself, or they only had one point source in the system boundary, and CO₂ emissions are not calculated and controlled in their study. In this work, we will introduce a new method which combines optimal electricity generation of multiple emission sources and the spatio-temporally varying TES framework to obtain the solution to air quality improvement, cost-saving operations, and social benefits. To the best of our knowledge, this is the first work to apply TES framework to electricity planning.

We design a framework called UC-TES (Unit Commitment with Techno-Ecological Synergy) to include ecosystem services into electricity unit commitment problem. Air pollution modeling was performed to obtain regional air quality maps and capacity of forests to take up air pollutants, and these results were then entered an optimization problem to explore the effect of vegetation on operations of electricity units and overall emissions and seek for a best solution to air pollution and monetary cost. A case study was conducted over the region of Louisville, KY. Nine power plants including coal, natural gas, and hydroelectric energy sources are optimized over a 24-hour time horizon together with decision variables for traditional air pollutants removal technologies and ecological tree planting design. CALPUFF version 7, an advanced non-steady-state meteorological and air quality modeling system, was used to generate concentration and dry deposition flux maps for three air pollutants (NO₂, SO₂, PM₁₀). Dry deposition flux is a measurement of the removal rate of forests in taking up air pollutants related to vegetation parameters.¹³ To identify the effect of vegetation on air quality, we performed air pollution modeling for two types of land use: the original land use , and when land use changes to forests on some selected areas. Results show that concentration of three pollutants decreases if we change some land use to forests, and the dry deposition flux increases a lot with the presence of more trees. Then we formulate an optimization problem which integrates the unit commitment of nine power plants with decisions of traditional technologies and reforestation area and location. In this work, four technologies are considered: selective catalytic reducer, flue gas desulfurization, baghouse filter, and aqueous monoethanolamine (MEA) solution for removal of NO₂, SO₂, PM₁₀, CO₂, respectively. The results will decide a. whether to include a specific type of technology or not; b. if included, how much capacity will be needed; c. location and total area for tree planting; d. optimal power output from electricity units to meet projected demand. The optimization problem was formulated as a mixed-integer linear program (MILP) and was solved in Julia by Gurobi solver. We explored five scenarios with different combinations of features such as emission constraints, conventional technologies, ecological reforestation. This work incorporates spatial and temporal variations through maps from air pollution modeling and hourly operations of power plants.

Our results show that the TES method results in designs that are superior to designs without ecosystem services, because with the benefits of forests, the same emission goal can be met without setting up some traditional technologies. Moreover, TES method can achieve a cost-saving solution and provide additional social benefits to nearby populations, and overall carbon emissions will significantly decrease with presence of more trees. The best schedule of electricity generation was also obtained from the optimization problem with power output combination in energy sources of coal, natural gas, and hydroelectric power plants on an hourly basis. This spatial-temporal work demonstrates the benefits of vegetation, develops the methodological framework to include ecosystem into industrial designs as a solution to air pollution by multiple point sources, selects best location for tree planting that optimizes the benefits , and reduces the overall regional air pollution including CO₂ emissions. Comparing with traditional UC problem, UC-TES can achieve a flexible operation of electricity units and emissions will be naturally captured by trees in an economic and environmental-friendly way that benefits besides air quality improvement, such as a cooling effect¹⁴, will last for a very long time. A sustainable way of pollutants removal and optimal power output will be explored and discussed which opens a new gate for system with both industrial system and ecological design.

Reference

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