A COMPARISON OF MARKET CLEARING TOOLS IN ELECTRICITY SYSTEMS

To maintain a strict balance between demand and supply in the US power systems, the Independent System Operators (ISOs) schedule power plants and determine electricity prices using a market clearing model. This model determines for each time period and power plant, the times of startup, shutdown, the amount of power production, and the provisioning of spinning and non-spinning power generation reserves, etc. Such a deterministic optimization model takes as input the characteristics of all the generating units such as their power generation installed capacity, ramp rates, minimum up and down time requirements, and marginal costs for production, as well as the forecast of intermittent energy such as wind and solar, along with the minimum reserve requirement of the whole system. This reserve requirement is determined based on the likelihood of outages on the supply side and on the levels of error forecasts in demand and intermittent generation. With increased installed capacity of intermittent renewable energy, determining the appropriate level of reserve requirements has become harder. Stochastic market clearing models have been proposed as an alternative to deterministic market clearing models. Rather than using a fixed reserve targets as an input, stochastic market clearing models take different scenarios of wind power into consideration and determine reserves schedule as output. Using a scaled version of the power generation system of PJM, a regional transmission organization (RTO) that coordinates the movement of wholesale electricity in all or parts of 13 states and the District of Columbia, and wind scenarios generated from BPA (Bonneville Power Administration) data, this paper explores a comparison of the performance between a stochastic and deterministic model in market clearing. The two models are compared in their ability to contribute to the affordability, reliability and sustainability of the electricity system, measured in terms of total operational costs, load shedding and air emissions. The process of building the models and running for tests indicate that a fair comparison is difficult to obtain due to the multi-dimensional performance metrics considered here, and the difficulty in setting up the parameters of the models in a way that does not advantage or disadvantage one modeling framework. Along these lines, this study explores the effect that model assumptions such as reserve requirements, value of lost load (VOLL) and wind spillage costs have on the comparison of the performance of stochastic vs deterministic market clearing models.

On the Origin of Natural Antibody

Natural IgM (nIgM) is constitutively present in the serum, where it aids in the early control of viral and bacterial expansions. nIgM also plays a significant role in the prevention of autoimmune disease by promoting the clearance of cellular debris. However, the cells that maintain high titers of nIgM in the circulation had not yet been identified. Several studies have linked serum nIgM with the presence of fetal-lineage B cells, and others have detected IgM secretion directly by B1a cells in various tissues. Nevertheless, a substantial contribution of undifferentiated B1 cells to nIgM titers is doubtful, as the ability to produce large quantities of antibody (Ab) is a function of the phenotype and morphology of differentiated plasma cells (PCs). No direct evidence exists to support the claim that a B1-cell population directly produces the bulk of circulating nIgM. The source of nIgM thus remained uncertain and unstudied.

In the first part of this study, I identified the primary source of nIgM. Using enzyme-linked immunosorbent spot (ELISPOT) assay, I determined that the majority of IgM Ab-secreting cells (ASCs) in naïve mice reside in the bone marrow (BM). Flow cytometric analysis of BM cells stained for intracellular IgM revealed that nIgM ASCs express IgM and the PC marker CD138 on their surface, but not the B1a cell marker CD5. By spinning these cells onto slides and staining them, following isolation by fluorescence-activated cell sorting (FACS), I found that they exhibit the typical morphological characteristics of terminally differentiated PCs. Transfer experiments demonstrated that BM nIgM PCs arise from a progenitor in the peritoneal cavity (PerC), but not isolated PerC B1a, B1b, or B2 cells. Immunoglobulin (Ig) gene sequence analysis and examination of B1-8i mice, which carry an Ig knockin that prohibits fetal B-cell development, indicated that nIgM PCs differentiate from fetal-lineage B cells. BrdU uptake experiments showed that the nIgM ASC compartment contains a substantial fraction of long-lived plasma cells (LLPCs). Finally, I demonstrated that nIgM PCs occupy a survival niche distinct from that used by IgG PCs.

In the second part of this dissertation, I characterized the unique survival niche of nIgM LLPCs, which maintain constitutive high titers of nIgM in the serum. By using genetically deficient or Ab-depleted mice, I found that neither T cells, type 2 innate lymphoid cells, nor mast cells, the three major hematopoietic producers of IL-5, were required for nIgM PC survival in the BM. However, IgM PCs associate strongly with IL-5-expressing BM stromal cells, which support their survival in vitro when stimulated. In vivo neutralization of IL-5 revealed that, like individual survival factors for IgG PCs, IL-5 is not the sole supporter of IgM PCs, but is likely one of several redundant molecules that together ensure uninterrupted signaling. Thus, the long-lived nIgM PC niche is not composed of hematopoietic sources of IL-5, but a stromal cell microenvironment that provides multiple redundant survival signals.

In the final part of my study, I identified and characterized the precursor of nIgM PCs, which I found in the first project to be resident in the PerC, but not a B1a, B1b, or B2 cell. By transferring PerC cells sorted based on expression of CD19, CD5, and CD11b, I found that only the CD19+CD5+CD11b- population contained cells capable of differentiating into nIgM PCs. Transfer of decreasing numbers of unfractionated PerC cells into Rag1 knockouts revealed an order-of-magnitude drop in the rate of serum IgM reconstitution between stochastically sampled pools of 106 and 3x105 PerC cells, suggesting that the CD19+CD5+CD11b- compartment comprises two cell types, and that interaction between the two necessary for nIgM-PC differentiation. By transferring neonatal liver, I determined that the early hematopoietic environment is required for nIgM PC precursors to develop. Using mice carrying a mutation that disturbs cKit expression, I also found that cKit appears to be required at a critical point near birth for the proper development of nIgM PC precursors.

The collective results of these studies demonstrate that nIgM is the product of BM-resident PCs, which differentiate from a PerC B cell precursor distinct from B1a cells, and survive long-term in a unique survival niche created by stromal cells. My work creates a new paradigm by which to understand nIgM, B1 cell, and PC biology.