Optimal siting and sizing of demand response in a transmission constrained system with high wind penetration

This paper describes algorithms that use demand-side management to address large-scale integration of wind power. In particular, demand response (DR) is used to manage wind power intermittency by shifting the time that electrical power system loads occur in response to real-time prices and wind availability. An economic dispatch with transmission, DR capacity and operational constraints is used to model the operation of a transmission constrained system with a high penetration of wind power. This optimization model is used to determine the optimal sizing and distribution of DR given a fixed budget for customer incentives and the installation of enabling technology. We demonstrate the effectiveness of the operational model based on a simple PJM 5-bus system and an IEEE 118-bus system. Simulation results show that transmission constraints have a greater effect on sizing of DR capacity than the location of wind power, which means that buses electrically close to congested lines tend to have higher incentives to deploy DR resources than other buses. The second part of the work examines optimal siting of technology that enables DR based on the frequency of DR based load changes, which are generally a function of the network location.     

Semantically enriched Massive Open Online Courses (MOOCs) platform

Massive Open Online Courses (MOOCs) are becoming an essential source of information for both students and teachers. Noticeably, MOOCs have to adapt to the fast development of new technologies; they also have to satisfy the current generation of online students. The current MOOCs’ Management Systems, such as Coursera, Udacity, edX, etc., use content management platforms where content are organized in a hierarchical structure. We envision a new generation of MOOCs that support interpretability with formal semantics by using the SemanticWeb and the online social networks. Semantic technologies support more flexible information management than that offered by the current MOOCs’ platforms. Annotated information about courses, video lectures, assignments, students, teachers, etc., can be composed from heterogeneous sources, including contributions from the communities in the forum space. These annotations, combined with legacy data, build foundations for more efficient information discovery in MOOCs’ platforms. In this article we review various Collaborative Semantic Filtering technologies for building Semantic MOOCs’ management system, then, we present a prototype of a semantic middle-sized platform implemented at Western Kentucky University that answers these aforementioned requirements.     

Negotiation based adaptive learning sequences: Combining adaptivity and adaptability

This study proposes a negotiation-based approach to combine the notion of adaptivity (system-controlled adaptation) and adaptability (user-controlled adaptation) for an adaptive learning system. The system suggests adaptations and the student also submits his/her adaptation preference. When the student preference opposes the system suggestion, the student then negotiates with the system to reach an agreement of adaptation. A negotiation-based adaptive learning system (NALS) is implemented to support the generation of personalized adaptive learning sequences by system negotiations with students regarding assessments of learning performance (i.e. negotiated open student model) of the current content and choices of the next learning content (i.e. negotiation of adaptation). Students require two metacognitions in deciding adaptive learning sequences: self-assessment for evaluating their understanding of the current content and regulation for choosing appropriate learning content. Negotiated open student model are used for assist student self-assessment and negotiation of adaptation are used for assist student regulation of content choices. An experiment was conducted to compare a system-controlled adaptive learning system (SALS, adaptivity), a user-controlled adaptive learning system (UALS, adaptability), and a NALS. The results revealed that NALS promoted better metacognitions in student calibration (i.e. self-assessment) accuracy and learning content choices (i.e. regulation). Preliminary evidences also showed that NALS promoted better student performance in a delay test. The results further suggested that students with poor calibration accuracy and inappropriate content choices were not suitable to use UALS and were suitable to use SALS. The NALS can also be used for training students to make appropriate adaptation for learning.     

Modeling Smart Grid neighborhoods with the ENERsip ontology

The electricity consumption in the buildings sector has been steadily increasing during the last decade, up to the point that energy efficiency in this sector has become a major problem for governments, utilities, customers, and the environment. The foreseen high penetration of distributed micro-generation facilities based on renewables can help to reduce the environmental footprint of buildings and households, although the complexity of managing effectively the electric grid increases dramatically under these conditions. The IEEE 2030 standard for interoperability in the Smart Grid remarks upon the importance of well-defined data models in such complex scenarios and puts emphasis on the benefits of ontologies and OWL (Web Ontology Language) for this purpose. This paper presents an OWL-based ontology that formally defines the vocabulary and taxonomy and captures the engineering and business semantics of this domain of knowledge (i.e., energy efficiency in the so-called nZEN – nearly Zero-Energy Neighborhoods). This ontology has been defined under the scope of the EU (European Union) research project ENERsip. The paper also highlights the main benefits the ontology brought to all the phases of the project life cycle, as well as how future work can make the most out of it.     

Demand response for home energy management system

The optimization of energy consumption, with consequent cost reduction, is one of the main challenges for the present and future smart grid. Demand response (DR) program is expected to be vital in home energy management system (HEMS) which aims to schedule the operation of appliances to save energy costs by considering customer convenience as well as characteristics of electric appliances. The DR program is a challenging optimization problem especially when the formulations are non-convex or NP-hard problems. In order to solve this challenging optimization problem efficiently, an effective heuristic approach is proposed to achieve a near optimal solution with low computational costs. Different from previously proposed methods in literatures which are not suitable to be run in embedded devices such as a smart meter. The proposed algorithm can be implemented in an embedded device which has severe limitations on memory size and computational power, and can get an optimal value in real-time. Numerical studies were carried out with the data simulating practical scenarios are provided to demonstrate the effectiveness of the proposed method.     

Crosstalk-aware multi-bit flip-flop generation for power optimization

Applying multi-bit flip-flops (MBFFs) for clock power reduction in modern nanometer ICs has been becoming a promising lower-power design technique. Many previous works tried to utilize as more MBFFs with larger number of bits as possible to gain more clock power saving. However, an MBFF with larger number of bits may lead to serious crosstalk due to the close interconnecting wires belonging to different signal nets which are connected to the same MBFF. This paper analyzes, evaluates, and compares the relationship between power consumption and crosstalk when applying MBFFs with different numbers of bits. To solve the addressed problem, a novel crosstalk-aware power optimization approach is further proposed to optimize power consumption while satisfying the crosstalk constraint. Experimental results show that the proposed approach is very effective in crosstalk avoidance when applying MBFFs for power optimization.     

Sexual self-presentation on social network sites: Who does it and how is it perceived?

The aims of this study were to investigate (a) the role of peer factors in adolescents’ sexual self-presentation on social network sites, and (b) how adolescents who present themselves sexually online are evaluated by others. 238 high school students (aged 12–18) evaluated either a sexual or non-sexual online presentation of same-sex and opposite-sex peers. Moreover, they filled in a questionnaire about their own self-presentation behavior. Findings showed that peer norms played a crucial role in whether adolescents posted sexual pictures of themselves online. Moreover, need for popularity was a strong predictor for posting such pictures. Girls who presented themselves in sexual ways were evaluated more negatively by other girls but more positively by boys. Similarly, boys who presented themselves in sexual ways were evaluated more positively by girls but not by boys.     

A new catalyst based on a nickel(II) complex of diiminodiphosphine for hydrogen evolution and oxidation

Based on that hydrogen energy is widely used in fuel cells, we focus our interests on the design and research of new complexes that catalyze the reaction in both directions, such as hydrogen evolution reactions (HERs) and hydrogen oxidation reactions (HORs). A highly efficient catalyst for both hydrogen evolution and oxidation, based on a nickel(II) complex, [Ni-en-P₂](ClO₄)₂, has been designed and provided by the reaction of Ni(ClO₄)₂ with N,N′-bis[o-(diphenylphosphino)benzylidene]ethylenediamine (en-P₂) in our group. Its structure has been determined by X-ray diffraction. [Ni-en-P₂](ClO₄)₂ can electro-catalyze hydrogen evolution both from acetic acid and a neutral buffer (pH 7.0) with a turnover frequency (TOF) of 204 and 1327 mol of hydrogen per mole of catalyst per hour (H₂/mol catalyst/h) under an overpotential (OP) of 914.6 mV and 836.6 mV, respectively. [Ni-en-P₂](ClO₄)₂ also can electro-catalyze hydrogen oxidation with a TOF of 111.7 s⁻¹ under an OP of 330 mV. The results can be attributed to that [Ni^II-en-P₂](ClO₄)₂ has three good reversible redox waves at 1.01 (Ni^III/II), −0.79 (Ni^II/I) and −1.38 V (Ni^I/0) versus Fc^+/0, respectively. We hope these findings can afford a new method for the design of electrocatalysts for both H₂ evolution and H₂ oxidation.     

自动多功能可调式便老轮椅的设计

针对老年人群体设计一种自动可调式轮椅，轮椅靠背通过不完全齿轮机构进行自动调整。靠背竖起可作为普通轮椅使用；靠背放平可实现平躺，可通过靠背和座椅安置的滚轴实现从轮椅到床和沙发等位置的移动。该轮椅工作稳定，性能可靠，功能实现效果较好。