BCIT Citations Collection | BCIT Institutional Repository

BCIT Citations Collection

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Collection of published works from BCIT researchers, faculty, and instructors.

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Predictive algorithm for Volt/VAR optimization of distribution networks using Neural Networks
Proceedings of IEEE Canadian Conference on Electrical and Computer Engineering (CCECE2014),May 2014, Toronto, Canada. Smart Grid functions such as Advanced Metering Infrastructure, Pervasive Control and Distribution Management Systems have brought numerous control and optimization opportunities for distribution networks through more accurate and reliable techniques. This paper presents a new predictive approach for Volt/VAr Optimization (VVO) of smart distribution systems using Neural Networks (NN) and Genetic Algorithm (GA). The proposed predictive algorithm is capable of predicting the load profile of target nodes a day ahead by employing the historical metrology data of Smart Meters, It can further perform a comprehensive VVO in order to minimize distribution network loss/operating costs and run Conservation Voltage Reduction (CVR) to conserve more energy. To test the merits of the proposed algorithm, British Columbia Institute of Technology north campus distribution grid is used as research case study., Conference paper, Published.
Preliminary results from field experimental study of rain load and penetration into wood-frame wall systems at window sill defects
14th Canadian Conference on Building Science and Technology, Toronto, Canada, October 29th-30th, 2014. A field study is presented here on the investigation of the correlation between wind-driven rain (WDR) as the driving force and the relative proportions of water penetration at intended defects (openings) located at the interface of windows and exterior walls. In this field study, eight full-scale exterior-wall panels of vinyl siding and stucco claddings were built and installed on a field testing station, which is subjected to British Columbia’s west coast climate rain. This paper focuses on the preliminary results from one of the stucco wall panels with a discontinuity in the sealant around the perimeters of the windows. The water passing through this defect was collected and measured. The instantaneous and automatic water collection measurements were synchronized to the data gathered by a nearby weather station on wind-driven rain intensity, wind speed and direction. In addition, rain gauges on exterior of walls collected the wind-driven rain against each façade of the test station. Compared to previous computer simulations and laboratory experimental studies on rain penetration through exterior walls, this study was conducted under more realistic conditions. The panels were subjected to real wind-driven rain events. Also collectively, the experiment took into account rain that splashed off the wall façade upon impact and the rain water around the defect location due to run-off. The study is ongoing. However, when complete, the results from this study will be useful for fine-tuning the principal moisture load that is applied in hygrothermal performance assessment and design of exterior wall systems., Conference paper, Published.
Program Comprehension: Identifying Learning Trajectories for Novice Programmers
This working group asserts that Program Comprehension (PC) plays a critical part in the writing process. For example, this abstract is written from a basic draft that we have edited and revised until it clearly presents our idea. Similarly, a program is written in an incremental manner, with each step being tested, debugged and extended until the program achieves its goal. Novice programmers should develop their program comprehension as they learn to code, so that they are able to read and reason about code while they are writing it. To foster such competencies our group has identified two main goals: (1) to collect and define learning activities that explicitly cover key components of program comprehension and (2) to define possible learning trajectories that will guide teachers using those learning activities in their CS0/CS1 or K-12 courses. We plan to achieve these goals as follows: Step 1 Review the current state of research and development by analyzing literature on classroom activities that improve program comprehension. Step 2 Concurrently, survey lecturers at various institutions on their use of workshop activities to foster PC. Step 3 Use the outputs from both activities to define and conceptualize what is meant by PC in the context of novice programmers. Step 4 Catalog learning activities with regard to their prerequisites, intended learning outcomes and additional special characteristics. Step 5 Catalog learning activities with regard to their prerequisites, intended learning outcomes and additional special characteristics. Step 6 Develop a map of learning activities and thereby also models of probable learning trajectories., Not peer reviewed, Conference proceedings
Program comprehension: identifying learning trajectories for novice programmers
This working group asserts that Program Comprehension (PC) plays a critical part in the writing process. For example, this abstract is written from a basic draft that we have edited and revised until it clearly presents our idea. Similarly, a program is written in an incremental manner, with each step being tested, debugged and extended until the program achieves its goal. Novice programmers should develop their program comprehension as they learn to code, so that they are able to read and reason about code while they are writing it. To foster such competencies our group has identified two main goals: (1) to collect and define learning activities that explicitly cover key components of program comprehension and (2) to define possible learning trajectories that will guide teachers using those learning activities in their CS0/CS1 or K-12 courses. We plan to achieve these goals as follows: Step 1 Review the current state of research and development by analyzing literature on classroom activities that improve program comprehension. Step 2 Concurrently, survey lecturers at various institutions on their use of workshop activities to foster PC. Step 3 Use the outputs from both activities to define and conceptualize what is meant by PC in the context of novice programmers. Step 4 Catalog learning activities with regard to their prerequisites, intended learning outcomes and additional special characteristics. Step 5 Catalog learning activities with regard to their prerequisites, intended learning outcomes and additional special characteristics. Step 6 Develop a map of learning activities and thereby also models of probable learning trajectories., Not peer reviewed, Conference proceedings
Ranking functions for belief change
Proceedings of the 6th International Conference on Agents and Artificial Intelligence in Angers, France, 2014. In this paper, we explore the use of ranking functions in reasoning about belief change. It is well-known that the semantics of belief revision can be defined either through total pre-orders or through ranking functions over states. While both approaches have similar expressive power with respect to single-shot belief revision, we argue that ranking functions provide distinct advantages at both the theoretical level and the practical level, particularly when actions are introduced. We demonstrate that belief revision induces a natural algebra over ranking functions, which treats belief states and observations in the same manner. When we introduce belief progression due to actions, we show that many natural domains can be easily represented with suitable ranking functions. Our formal framework uses ranking functions to represent belief revision and belief progression in a uniform manner; we demonstrate the power of our approach through formal results, as well as a series of natural problems in commonsense reasoning., Conference paper, Published.
Real-time adaptive optimization engine algorithm for integrated Volt/VAr optimization and conservation voltage reduction of smart microgrids
Proceedings from CIGRÉ Canada Conference, Montreal, Sept. 2012. In recent decade, smart microgrids have raised the feasibility and affordability of adaptive and real-time Volt/VAr optimization (VVO) and Conservation Voltage Reduction (CVR) implementations by their exclusive features such as using smart metering technologies and various types of dispersed generations. Smart distribution networks are presently capable of achieving higher degrees of efficiency and reliability through employing a new integrated Volt/VAr optimization system. For VVO application, two well-known approaches are recommended by different utilities and/or companies: Centralized VVO and Decentralized VVO. In centralized VVO, the processing system is placed in a central controller unit such as DMS in the so called “Utility Back Office”. The DMS uses relevant measurements taken from termination points (i.e. utility subscribers) supplied to it from either field collectors or directly from MDMS, to determine the best possible settings for field-bound VVO/CVR assets to achieve the desired optimization and conservation targets. These settings are then off-loaded to such assets through existing downstream pipes, such as SCADA network In contrast, decentralized VVO utilizes VVO/CVR engines which are located in the field and in close-proximity to the relevant assets to conserve voltage and energy according to local attributes of the distribution network. In this case, local measurements do not need to travel from the field to the back-office, and the new settings for VVO/CVR assets are determined locally, rather than from a centralized controller. Without having any preference between above mentioned VVO techniques, this paper studies an adaptive optimization engine for real-time VVO/CVR in smart microgrids based on Intelligent Agent technology. The optimization algorithm provides the best optimal solution for VVO/CVR problem at each real-time stage through minimizing system loss cost and improves system energy efficiency as well as voltage profile of the relevant distribution system. The algorithm may employ distributed generation sources to address the Volt/VAr optimization problem in real-time. Coordinated VVO/CVR requires real-time data analysis every 15 minutes. It utilizes a distributed command and control architecture to supply the VVO Engine (VVOE) with the required data, and secures real-time configuration from the VVO engine for the VVO control devices such as On-Load Tap Changers (OLTCs), Voltage Regulators (VRs) and Capacitor Banks (CBs). It also has the option of employing distributed generation (DG) as well as modelling load effects in VVO/CVR application. The algorithm minimizes the distribution network power loss cost at each time stage, checks the voltage deviation of distribution buses and distributed generation sources considering different types of constraints such as system power flow, distribution network power factor, system active and reactive power constraints and switching limitations of Volt/VAr control devices. The algorithm receives required real-time data from an intelligent agent. Then, it starts to solve the real-time VVO/CVR problem in order to find the best optimal configuration of the network in real-time. The paper uses British Columbia Institute of Technology (BCIT) distribution network as its case study in order to explore the effectiveness and the accuracy of the optimization engine. Moreover, the VVO/CVR optimization algorithm is implemented in different configurations; a) VVO/CVR confined to the substation and b) VVO/CVR optimization algorithm within the substation and along distribution feeders. The algorithm also checks the availability of DGs to assist VVO/CVR control functions and assesses the impact of new distributed sources such as: Flywheel Energy Storage System (FESS) on real-time VVO/CVR. For this reason, the algorithm classified DGs in a microgrid based on their impacts and instantiates them based on their application feasibility for real-time VVO/CVR., Conference paper, Published.
Real-time co-simulated platform for novel Volt-VAR Optimization of smart distribution network using AMI data
Accepted in IEEE International Conference on Smart Energy Grid Engineering, May 2015. This paper presents a real-time co-simulated platform for novel voltage and reactive power optimization (VVO) of distribution grids through a real-time digital simulator (RTDS) in presence of a reliable communication platform. The proposed VVO engine is able to capture quasi real-time data from local Advanced Metering Infrastructure (AMI) and optimizes the distribution network for each quasi real-time stage (every 5 minutes) based on system main characteristics (i.e. active/reactive power of nodes). At each time stage, the VVO engine tries to minimize losses in the distribution network as well as to improve the voltage profile of the system. In order to test robustness, performance and the applicability of proposed Volt-VAR Optimization engine, a 33 node distribution network has been modeled and studied in a real-time Co-simulated environment by real-time simulator (RTDS) and a real communication platform with DNP.3 protocol. The preliminary results prove well-performance of proposed AMI-based VVO engine and show that the engine enables system to achieve higher level of loss/operating cost reduction through a sophisticated optimization engine compare with conventional approaches., Conference paper, Published.
Recruiting new genes in evolving genetic networks
Proceedings of the World Congress on Engineering and Computer Science 2007 WCECS 2007, October 24-26, 2007, San Francisco, USA. Gene recruitment or co-option is defined as the placement of a gene under a foreign regulatory system. Such re-arrangement of pre-existing regulatory networks can lead to an increase in genomic complexity. This reorganization is recognized as a major driving force in evolution. We simulated the evolution of gene networks by means of the Genetic Algorithms (GA) technique. We used standard GA methods of (point) mutation and multi-point crossover, as well as our own operators for introducing or withdrawing new genes on the network. The starting point for our computer evolutionary experiments was a minimal 4-gene dynamic model representing the real genetic network controlling segmentation in the fruit fly Drosophila. Model output was fit to experimentally observed gene expression patterns in the early fly embryo. We found that the mutation operator, together with the gene introduction procedure, was sufficient for recruiting new genes into pre-existing networks. Reinforcement of the evolutionary search by crossover operators facilitates this recruitment. Gene recruitment causes outgrowth of an evolving network, resulting in structural and functional redundancy. Such redundancies can affect the robustness and evolvability of networks., Conference paper, Published.
The Reservist Re-Entry Program : an alternative approach prior learning assessment and advanced placement in academic and vocational programs for Canadian Soldiers
Prepared for the Atlantic Canada Economic Association Conference, October 19-20, 2012, Halifax Nova Scotia. Both the Canada and United States invest a great deal of resources in the training of their military personal. Many of the skills and experiences accumulated by soldiers are those that are highly valued by civilian employers. Further, these skills are often embodied in academic programs, suggesting soldiers would have a comparative advantage in such programs; however, despite the efforts of government agencies, many soldiers are unable to convert their skills and training into meaningful careers. This paper presents the findings from a pilot program at the BC institute of Technology 2009-2012. The program uses an alternative approach to assessing military training for advanced placement into post-secondary programs. By mapping learning outcomes rather than course equivalences, those from non-traditional education backgrounds are given advanced placement into post-secondary programs. During the pilot period, a cohort of reservists and veterans who have been given advanced placement are tracked and benchmarked against regular students in the same programs over time, measuring academic scores and testing for the development of skills, abilities, and qualities considered important for workplace success., Conference paper, Draft available.
Retroviral genetic algorithms
Proceedings of the 2011 International Conference on Evolutionary Computation Theory and Applications. Classical understandings of biological evolution inspired creation of the entire order of Evolutionary Computation (EC) heuristic optimization techniques. In turn, the development of EC has shown how living organisms use biomolecular implementations of these techniques to solve particular problems in survival and adaptation. An example of such a natural Genetic Algorithm (GA) is the way in which a higher organism's adaptive immune system selects antibodies and competes against its complement, the development of antigen variability by pathogenic organisms. In our approach, we use operators that implement the reproduction and diversification of genetic material in a manner inspired by retroviral reproduction and a genetic-engineering technique known as DNA shuffling. We call this approach Retroviral Genetic Algorithms, or retroGA (Spirov and Holloway, 2010). Here, we extend retroGA to include: (1) the utilization of tags in strings; (2) the capability of the Reproduction-Crossover operator to read these tags and interpret them as instructions; and (3), as a consequence, to use more than one reproductive strategy. We validated the efficacy of the extended retroGA technique with benchmark tests on concatenated trap functions and compared these with Royal Road and Royal Staircase functions., Conference paper, Published.
Searching for early developmental activities leading to computational thinking skills
Proceedings from the 2017 ACM Conference on Innovation and Technology in Computer Science Education. Drawing on the long debate about whether computer science (CS) and computational thinking skills are innate or learnable, this working group is based on the following hypothesis: The apparent innate ability of some CS learners who succeed in CS courses despite no prior exposure to computing is a manifestation of early childhood experiences and learning outside formal education., Peer reviewed, Conference paper, Published., K-12 education, Computational thinking
Security and trust for surveillance cameras
Proceedings of 2017 IEEE Conference on Communications and Network Security (CNS) in Las Vegas, NV, USA, USA on 9-11 Oct. 2017.We address security and trust in the context of a commercial IP camera. We take a hands-on approach, as we not only define abstract vulnerabilities, but we actually implement the attacks on a real camera. We then discuss the nature of the attacks and the root cause; we propose a formal model of trust that can be used to address the vulnerabilities by explicitly constraining compositionality for trust relationships., Conference paper, Published.
Simulation of wind-driven rain effects on the performance of a stucco-clad wall
Thermal Performance of Exterior Envelopes of Whole Buildings X International Conference, Clearwater Beach, Florida, USA, December 02, 2007. This climate sensitivity study studied the effects of wind-driven rain on a stucco-clad wall using the advanced hygrothermal model, hygIRC. Simulations were made for a number of climatic conditions based on the moisture index (MI) and for amounts of water deposited inside a wall. The moisture index was based on the severity of a given climate in respect to wall assemblies and the degree of wetting and drying to which a wall could potentially be subjected. The failure criteria was the concurrent occurrence of temperature and relative humidity above thresholds of 10oC and 95% respectively, for ninety consecutive days at any location of wood-based material in the wall., Conference paper, Published. A version of this document is published in: Thermal Performance of Exterior Envelopes of Whole Buildings X International Conference, Clearwater Beach, FL., Dec. 2-7, 2007, pp. 1-15.
Spectrum hierarchies and subdiagonal functions
Proceedings of the 18th IEEE Symposium on Logic in Computer Science (LICS-03), Ottawa, ON, 2003. The spectrum of a first-order sentence is the set of cardinalities of its finite models. Relatively little is known about the subclasses of spectra that are obtained by looking only at sentences with a specific signature. In this paper, we study natural subclasses of spectra and their closure properties under simple subdiagonal functions. We show that many natural closure properties turn out to be equivalent to the collapse of potential spectrum hierarchies. We prove all of our results using explicit transformations on first-order structures., Conference paper, Published.
Stochastic dynamics of gene expression in developing fly embryos
Proceedings of 2017 International Conference on Noise and Fluctuations (ICNF), Vilnius, Lithuania on 20-23 June 2017. Segmentation of the developing insect body is preceded by cell-specific gene expression. In fruit flies (Drosophila), pair-rule genes are expressed in spatial stripes specifying segment fates. Transcription of the even-skipped (eve) pair-rule gene was recently shown to proceed in noisy bursts. Here, we develop a stochastic model of eve transcription from DNA to mRNA. This indicates that eve transcription proceeds at two rates, with a slow rate providing basal production and a fast rate allowing for high mRNA output. This two-rate transcription may afford more reliability in mRNA output, and therefore the protein levels which specify cell type, than a simple on-off (one-rate) mechanism., Conference paper, Published.
Structured documents
Proceedings of 2012 European Intelligence and Security Informatics Conference (EISIC) in Odense, Denmark 22-24 Aug. 2012. Much of the information exchanged between agents over a network is encapsulated in XML documents. An XML document has a tree structure, and the meaning of the document can be understood in terms of a set of label-value pairs. The content of a document is often secured through digital signatures applied to different sections, while the document is passed between several agents. In this paper, we illustrate that this process is insecure in the sense that a malicious agent can deceive an honest agent to hold beliefs that are untrue. We provide a formal framework for analyzing the security of structured documents, based on the implicit epistemic impact that a signed document will have on a recipient. This kind of analysis can provide significant insight into deception and fraud detection., Conference paper, Published.

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