An Integrated Multi-Time-Scale Modeling for Solar Irradiance Forecasting Using Deep Learning

For short-term solar irradiance forecasting, the traditional point forecasting methods are rendered less useful due to the non-stationary characteristic of solar power. The amount of operating reserves required to maintain reliable operation of the electric grid rises due to the variability of solar energy. The higher the uncertainty in the generation, the greater the operating-reserve requirements, which translates to an increased cost of operation. In this research work, we propose a unified architecture for multi-time-scale predictions for intra-day solar irradiance forecasting using recurrent neural networks (RNN) and long-short-term memory networks (LSTMs). This paper also lays out a framework for extending this modeling approach to intra-hour forecasting horizons thus, making it a multi-time-horizon forecasting approach, capable of predicting intra-hour as well as intra-day solar irradiance. We develop an end-to-end pipeline to effectuate the proposed architecture. The performance of the prediction model is tested and validated by the methodical implementation. The robustness of the approach is demonstrated with case studies conducted for geographically scattered sites across the United States. The predictions demonstrate that our proposed unified architecture-based approach is effective for multi-time-scale solar forecasts and achieves a lower root-mean-square prediction error when benchmarked against the best-performing methods documented in the literature that use separate models for each time-scale during the day. Our proposed method results in a 71.5% reduction in the mean RMSE averaged across all the test sites compared to the ML-based best-performing method reported in the literature. Additionally, the proposed method enables multi-time-horizon forecasts with real-time inputs, which have a significant potential for practical industry applications in the evolving grid.Comment: 19 pages, 12 figures, 3 tables, under review for journal submissio

Reconciling the Personalization-Privacy Paradox: Exploring Privacy Boundaries in Online Personalized Advertising

To reconcile the personalization-privacy paradox, we adopt the privacy as a state view and define privacy as a state of information boundary rule-following. We further identify five types of boundaries underlying some of the important implicit rules of maintaining privacy: communication channel, platform, device, temporal, and purpose boundaries. Using an online vignette survey, we investigated how each of these boundary types affected users’ privacy perceptions when they were subjected to personalized advertisements. Using fixed- and random-effects models, we investigated how violating different boundary rules leads to changes in perceived privacy. Our results show that all five boundary types are significant predictors of perceived privacy within individuals. The communication channel, device, and business versus private purpose are significant predictors of perceived privacy across the whole sample. Temporal boundaries and platform boundaries failed to achieve statistical significance when evaluated simultaneously with the other factors across the whole sample. This means that for each individual, observing the rules of these five boundary types leads to higher perceived privacy than not observing these conditions. Taken as a whole, observing communication channel, device, and business versus private purpose boundaries also leads to higher averages of perceived privacy across the whole sample. Theoretical and practical implications are discussed based on the result

Moving toward full, active, and conscious participation: worshiping practices for the entire beloved community

Work toward ecumenical liturgical convergence may be traced back to at least 1910; however, this project thesis expands upon the concept of full, active, and conscious participation in worship found in the 1963 Second Ecumenical Vatican Council’s Sacrosanctum Concilium to illumine how shaping the worship practices of the Church can make our communities of faith inclusive of all sexual orientations and gender expressions. This thesis presents the design of a curriculum for worship leaders to reflect upon the worship practices of these local context, and move from their current state to a place where all members of the beloved community are valued

Informal distributed leadership in technology adoption

Published ArticleThis study investigated the role of informal distributed leadership in dealing with the complexities of adopting technology innovation in Higher Education contexts. In the study, in-depth semi-structured interviews and focus group discussions were held with a group of informal leaders in a South African university. The findings suggest that informal distributed leadership works best in promoting technology adoption when there is a clear understanding of: (1) the locus of control of technology adopters; (2) power contestations between academics and students; (3) alignment of technology with pedagogical goals; and (4) shared intentionality between the core group of informal leaders. In practical terms, the study offers a middle-of-the-road approach to diffusion of technology innovation as an alternative to the ineffective top-down and individual innovative leader (bottom-up) approaches. For originality/novelty, the study introduces the distributed leadership theory into the technology adoption discourse