Microgrid systems located within commercial premises are becoming increasingly popular and their dynamic behavior is still uncharted territory in modern power networks. Improved understanding in design and operation is required for the electricity utility and building services design sectors. This paper evaluates the design requirements for a commercial building microgrid system to facilitate seamless mode transition considering an actual commercial building microgrid system. A dynamic simulation model of the proposed microgrid system is established (utilizing DIgSILENT Power Factory) to aid the development of planning and operational philosophy for the practical system. An economic operational criterion is developed for the microgrid to incorporate selective mode transition in different time intervals and demand scenarios. In addition, a multi-droop control strategy has been developed to mitigate voltage and frequency variations during mode transition. Different system conditions considering variability in load and generation are analyzed to examine the responses of associated microgrid network parameters (i.e., voltage and frequency) with the proposed mode transition strategy during planned and unplanned islanding conditions. It has been demonstrated that despite having a rigorous mode transition strategy, control of certain loads such as direct online (DOL) and variable-speed-drive (VSD) driven motor loads is vital for ensuring seamless mode-transition, in particular for unplanned islanding conditions.
This paper presents a clustering-based strategy to identify typical daily electricity usage (TDEU) profiles of multiple buildings. Different from the majority of existing clustering strategies, the proposed strategy consists of two levels of clustering, i.e. intra-building clustering and inter-building clustering. The intrabuilding clustering used a Gaussian mixture model-based clustering to identify the TDEU profiles of each individual building. The inter-building clustering used an agglomerative hierarchical clustering to identify the TDEU profiles of multiple buildings based on the TDEU profiles identified for each individual building through intra-building clustering. The performance of this strategy was evaluated using two-year hourly electricity consumption data collected from 40 university buildings. The results showed that this strategy can discover useful information related to building electricity usage, including typical patterns of daily electricity usage (DEU) and periodical variation of DEU. It was also shown that this proposed strategy can identify additional electricity usage patterns with a less computational cost, in comparison to two singlestep clustering strategies including a Partitioning Around Medoids-based clustering strategy and a hierarchical clustering strategy. The results obtained from this study could be potentially used to assist in improving energy performance of university buildings and other types of buildings.
The design principles and performance characteristics of a prototype high-temperature superconductor saturable magnetic core-type fault current limiter are described. These are based on a distribution network service provider feasibility specification that included the footprint and regulatory requirements for limiting fault currents. Time-domain simulations using PSCAD/EMTDC are given to illustrate specific applications and the transient behavior of the different distribution system configurations are investigated. Disciplines Physical Sciences and Mathematics Publication DetailsThis article was originally published as: Abbott, SB, Robinson, DA, Perera, S, et al, Abstract-The design principles and performance characteristics of a prototype high-temperature superconductor saturable magnetic core-type fault current limiter are described. These are based on a distribution network service provider feasibility specification that included the footprint and regulatory requirements for limiting fault currents. Time-domain simulations using PSCAD/EMTDC are given to illustrate specific applications and the transient behavior of the different distribution system configurations are investigated.
This report provides an introduction to the various probabilistic methods developed roughly between 1956-1985 for performing reliability or probabilistic uncertainty analysis on complex systems. This exposition does not include the traditional reliability methods (e.g. parallel-series systems, etc.) that might be found in the many reliability texts and reference materials (e g Kapur and Lamberson, 1977). Rather, the report centers on the relatively new, and certainly less well known across the engineering community, analytical techniques. Discussion of the analytical methods has been broken into two reports. This particular report is limited to those methods developed between 1956-1985. While a bit dated, methods described in the later portions of this report still dominate the literature and provide a necessary technical foundation for more current research. A second report (Analytical Techniques n) addresses methods developed since 1985. The flow of this report roughly follows the historical development of the various methods so each new technique builds on the discussion of strengths and weaknesses of previous techniques. To facilitate the understanding of the various methods discussed, a simple 2-dimensional problem is used throughout the report. The problem is used for discussion purposes only; conclusions regarding the applicability and efficiency of particular methods are based on secondary analyses and a number of years of experience by the author. This document should be considered a 'living document' in the sense that as new methods or variations of existing methods are developed, the document and references will be updated to reflect the current state of the literature as much as possible. For those scientists and engineers already familiar with these methods, the discussion will at times become rather obvious. However, the goal of this effort is to provide a common basis for future discussions and, as such, will hopefully be useful to those more intimate with probabilistic analysis and design techniques. There are clearly alternative methods of dealing with uncertainty (e g fuzzy set theory, possibility theory), but this discussion will be limited to those methods based on probability theory.
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