Addressing Computational Challenges In Renewable Energy Integration: Behind-the-Meter To Transmission

Integrating renewable energy into the power grid is challenging due to the intermittent, variable, and non-dispatchable characteristics of renewable energy generation. From behind-the-meter (BTM) to transmission settings, this thesis employs stochastic optimization methods to account for uncertainty in renewable energy generation and addresses computational challenges of including grid-connected energy storage systems (ESSs) models in optimization problems. For a BTM setting, a stochastic model predictive control (MPC)-based residential energy management system (EMS) algorithm is proposed to optimally coordinate residential electricity usage, controllable appliances, and customer-owned energy sources (e.g., rooftop photovoltaic (PV) panels and an ESS). Instead of computationally limiting sampling-based stochastic optimization approaches, chance constraints are used to ensure both a demand response (DR) event and indoor thermal comfort are satisfied with a high probability given uncertainty in PV generation and weather forecasts. Case study results highlight the residential EMS algorithm performance from both customer and utility perspectives. For large-scale wind power integration in a transmission setting, a two-stage stochastic flexible line capacity rating algorithm is proposed to determine economic conventional generator dispatch while minimizing the amount of curtailed wind power across probable wind power generation scenarios. Flexible line ratings are incorporated into the model using a sample average approximation of an integer chance constraint, limiting the probability of non-nominal line capacity rating violations. Case study results demonstrate the flexible line capacity rating algorithm can reduce total average wind power curtailment by 40\% compared to the static line rating case. From BTM to transmission settings, grid-connected ESSs are often coupled with renewable energy sources in optimization models for many applications in power systems. Theoretical analysis is provided that guarantees a relaxed convex ESS model will produce a physically realizable optimal control strategy with non-simultaneous ESS charging and discharging. The relaxed convex ESS model omits the non-convex complementarity constraint that explicitly ensures non-simultaneous ESS charging and discharging, avoiding computationally limiting non-convex or mixed-integer optimization solvers. Case studies with the relaxed convex ESS model show the optimal solutions satisfy the omitted complementarity constraint, result in significantly faster computation times, and the penalty-based approach has a negligible impact on the optimal solution.</p

Exploring the Influence of Patient Position During Mechanical Traction on Lumbar Mobility

Exploring the Influence of Patient Position During Mechanical Traction on Lumbar Mobility Ortman, I, Garifi, K, Moody, V. University of Montana Context: Mechanical traction uses a motorized device to apply a selected traction force to slowly elongate the spine. Research demonstrate the ability of sustained distraction forces to increase the length of spinal tissues by creep and hysteresis, with effects remaining longer in tissues of older individuals. There are three primary positions that a patient can be in for mechanical lumbar traction: supine, prone, and 90/90. The choice of position is driven by patient comfort, however, there might be differences in effectiveness based on resting lumbar curvature. The purpose of this study was to compare the effects of supine, prone, and 90-90 mechanical traction on lumbar mobility. Methods: A convenience sample of four healthy adults were selected for this study (2 females, 2 males; average age 23 + 2 years, height 69 ±4 inches, and weight 224 + 17 lbs). A repeated measures design was used whereby subjects completed three separate trials with a week between each trial. The three trials included 3 separate lumbar mechanical traction treatments in either a supine, prone, or 90-90 (hip flexion, knee flexion) position for 15 minutes. Lumbar flexion, extension, right lateral lumbar flexion (RLLF) and left lateral lumbar flexion (LLLF) was measured with a standard 12-inch goniometer before and after each trial. Three measurements were obtained and an average was recorded. Treatment order was randomized and spaced out at least a week apart. Microsoft Excel was used to calculate descriptive statistics for each participant’s height, weight, and age along with lumbar flexion, extension, RLF, and LLF. Separate 2 x 3 repeated measures ANOVA using SPSS v26.0 was used to calculate the mean difference in lumbar ROM between the supine, prone, and 90/90 trials for lumbar flexion, lumbar extension, RLLF, and LLF. Significance was set a priori at p = 0.05. Results: A 2 x 3 (time x trial) repeated measures ANOVA revealed no statistical significance between patient positions during traction (prone, supine, 90/90) for lumbar flexion (p=0.813), extension (p=0.146), RLLF (p=0.170), and LLLF (p=0.107). The main effect for time was noted for lumbar extension (p=0.004), where a further analysis revealed a significant difference between the supine and 90/90 position (p=0.037). However, a trend for an improved lumbar range of motion was noted across all three positions after receiving mechanical traction. Conclusion: The primary finding of our study was a trend of increased lumbar ROM following mechanical traction, regardless of position. Statistically significant improvement in lumbar extension was seen, but a large standard deviation in this measurement adds caution to clinical interpretation. Additional research is needed to support the clinical use of traction to improve lumbar ROM absent of symptomatic lumbar pathology. Word Count: 43

Y-Balance Scores Between Injured and Uninjured Athletes: A Systematic Review of Prospective Cohort Studies

Y-Balance Scores Between Injured and Uninjured Athletes: A Systematic Review of Prospective Cohort Studies Unequivocal evidence does not exist showing that the current recommended musculoskeletal assessment of a PPE is effective at consistently and accurately identifying athletes at risk for musculoskeletal injury, nor preventing such injuries. A different proposed injury risk screening measure is the Lower Quarter Y-Balance Test (LQ-YBT), a simplified and instrumented adaptation of the SEBT in which dynamic, unilateral balance is tested in anterior, posteromedial, and posterolateral reach directions. The objective was to compare anterior reach asymmetry (ARA) and composite score (CS) in injured and uninjured athletic populations to determine the injury risk identification efficacy of the lower quarter y-balance test (LQ-YBT). Researchers searched the database of PubMed in October 2021. Eligible studies were peer-reviewed articles that included the use of LQ-YBT individually, reported injury data, reported composite and/or anterior reach asymmetry, and had participants that were a part of the athletic population. Studies were excluded if the SEBT was used, data was not presented in a usable form, and the manuscript was not available in English. Researchers extracted data during the primary review. The extracted data included: study design, the purpose of study, population demographic, injury data, composite score, and asymmetry reach asymmetry. Studies that were included reported averages of composite scores, anterior reach asymmetry, and/or raw data that could be used to calculate these measures. The standard calculation to find the CS is [(ANT+PM+PL)/3x Limb Length] x100. To determine ARA, researchers calculated the absolute value difference between right and left scores, |R ANT - L ANT| Past reviews of similar research included SEBT data, however, the more simplified LQ-YBT is now more commonly used and procedurally different. A recent systematic review looked specifically at the predictive validity of a LQ-YBT injury risk cut-off score, however, in our research we found many cohorts did not even achieve the cut-off scores. A comparison between injured and non-injured group scores was needed to investigate the ability of the test scores to distinguish between athletes that get injured or stay healthy. Our systematic review of nine articles specifically examining LQ-YBT showed little observable differences in CS and ARA between injured and uninjured groups of athletes. These findings preclude recommendations for the use of LQ-YBT as a screening measure in a PPE for general athletic populations. Future research using the LQ-YBT in specific athletic subpopulations may be able to provide new predictive cut-off scores that will establish clinical relevance for screening in those populations alone. Other possible uses for the LQ-YBT identified may be specifically screening for ankle injury risk or longitudinal comparison of an individual in physical rehabilitation for a prior lower extremity injury