Determinants of price fluctuations in the electricity market: a study with PCA and NARDL models

In the modern electricity markets, negative prices and spike prices coexist as a pair of opposite economic phenomena. This study investigates how these extreme prices play as the determinants to drive price fluctuations in the electricity market. We construct a two-stage analysis including a principal component analysis (PCA) and a nonlinear autoregressive distributed lags model (NARDL). We apply this analytical method to the wholesale Pennsylvania, New Jersey and Maryland (PJM) electricity market. We find that according to PCA, in the individual transmission lines, spike prices are determinants with largest explanatory power to the variation of prices, while according to NARDL, from the standpoint of the overall market, negative prices have a larger potential effect on both the real-time market and the forward market. These results are valuable and contributive to managers and operators in the electricity markets for policy decision making

Principal Component Analysis of Price Fluctuation in the Smart Grid Electricity Market

Large price fluctuations have become a significant character and impede resource allocation in the electricity market. Negative prices and peak load spike prices coexist and represent over-supply and over-demand, respectively. It is important to interpret the impact of these extreme prices on sustainable power management from the perspective of economics. In this paper, we build a principal component analysis (PCA) to assess the impact of the two opposite phenomena on the smart grid electricity system. We perform a big-data study using intra-day data from the Pennsylvania, New Jersey, and Maryland (PJM) electricity system with over 11,000 transmission lines. As the contribution, this paper (1) measures the price fluctuations from the perspective of economics, (2) captures and observes the full-length behavior of negative and spike pricing in a modern smart grid system with multi-transmission lines and high-frequency price updates, and (3) employs methods with distinctive advantages to bring more in-depth findings to interpret the smart grid system. We find that spike prices hold the principal explanatory power for electricity market fluctuation in all the transmission lines. The results are consistent with previous studies about resolutions such as electrical energy storage, transmission capacity upgrade, and demand response

Using trends and outliers in managing delayed transfusions

OBJECTIVES: To investigate if time to initiate a blood transfusion after an informative laboratory test could feasibly be used by the transfusion medicine service as a metric to monitor for transfusion delays. BACKGROUND: Delayed transfusions may result in patient morbidity and mortality, but no standards for timely transfusion have been developed. Information technology tools could be implemented to identify gaps in provision of blood and to recognise areas of improvement. MATERIALS AND METHODS: Data obtained from a children\u27s hospital\u27s data science platform and time from the release of laboratory results to the initiation of transfusions were calculated and weekly medians were used for trend analyses. Outlier events were obtained using locally estimated scatterplot smoothing and generalised extreme studentized deviate test. RESULTS: Overall, the number of outlier events on the timing of transfusions based on patients\u27 haemoglobin level and platelet count were small (n = 1 and n = 0 for 139 weeks, respectively). Investigation of these events for adverse clinical outcomes was non-significant. CONCLUSIONS: Herein, we propose that the trends and outlier events could be further investigated and used to make decisions and implement protocols to improve patient care

Measuring the Impact of a Blood Supply Shortage Using Data Science

BACKGROUND: Transfusion medicine is the only section of the clinical laboratory that performs diagnostic testing and dispenses a drug (blood) on the basis of those results. However, not all of the testing that informs the clinical decision to prescribe a blood transfusion is performed in the blood bank. To form a holistic assessment of blood bank responsiveness to clinical needs, it is important to be able to merge blood bank data with datapoints from the hematology laboratory and the electronic medical record. METHODS: We built an interactive visualization of the time from hemoglobin result availability to initiation of red blood cell (RBC) transfusion and monitored the result over a 2-year period that coincided with several severe blood shortages. The visualization runs entirely on free software and was designed to be feasibly deployed on a variety of hospital information technology platforms without the need for significant data science expertise. RESULTS: Patient factors, such as hemoglobin concentration, blood type, and presence of minor blood group antibodies influenced the time to initiation of transfusion. Time to transfusion initiation did not appear to be significantly affected by periods of blood shortage. CONCLUSION: Overall, we demonstrate a proof of concept that complex, but clinically important, blood bank quality metrics can be generated with the support of a free, user-friendly system that aggregates data from multiple sources

Biofilms and mucosal healing in postsurgical patients with chronic rhinosinusitis

10.2500/ajra.2009.23.3376American Journal of Rhinology and Allergy235506-511AJRH

The Length of Product Line in Distribution Channels

This paper studies a manufacturer's optimal decisions on extending its product line when the manufacturer sells through either a centralized channel or a decentralized channel. We show that a manufacturer may provide a longer product line for consumers in a decentralized channel than in a centralized channel if the market is fully covered. In addition, a manufacturer's decisions on the length of its product line may not always be optimal from a social welfare perspective in either a centralized or a decentralized channel. Under certain conditions, a decentralized channel can provide the product line length that is socially optimal, whereas a centralized channel cannot.product line, distribution channel, consumer heterogeneity, game theory