1,721,026 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Optimal operation strategy for multi-carrier energy systems including various energy converters by multi-objective information gap decision theory and enhanced directed search domain method
No full text•Presenting a new operation model for multi-carrier energy systems.•Uncertainty modeling by a multi-objective information gap decision theory approach.•Presenting a novel multi-objective solution method to solve the proposed model.•Introducing a new post-optimization method to attain the best robustness level. Multi-carrier energy systems can increase energy efficiency due to the ability of these systems to consider and optimize the interactions of various energy carriers. However, the operation of these systems is somehow different from the operation of conventional single-carrier energy systems. In this paper, a new operation strategy for multi-carrier energy systems including natural gas and electricity is proposed. Various energy converters, including conventional and renewable electricity generators, gas furnace, and combined heat and power generator, are modeled in the proposed strategy to supply different electric, heat, and gas loads in the output. The proposed operation strategy employs a multi-objective information gap decision theory approach to model the uncertainty sources of multi-carrier energy systems, such as the uncertainties of demand forecasts, wind power forecast, and photovoltaic power forecast. For solving the multi-objective optimization problem, based on information gap decision theory, for multi-carrier energy system operation, an enhanced directed search domain method is proposed as a new multi-objective optimization approach. The performance of the proposed multi-carrier energy system operation optimization model and the proposed enhanced directed search domain solution method is investigated on the IEEE 118-bus test system by comparing with the other alternatives
Adaptive-robust multi-resolution generation maintenance scheduling with probabilistic reliability constraint
No full textThis study presents a reliability-constrained adaptive-robust multi-resolution model for generation maintenance scheduling (GMS) problem considering the uncertainty sources of electricity demand, wind power generation, and equipment unavailabilities. In the proposed tri-level adaptive-robust model, a polyhedral uncertainty set is used to model the electricity demand and wind power generation fluctuations. In addition, equipment unavailabilities as discrete uncertainty sources are modelled in the reliability sub-problem where the expected energy not supplied is determined as a reliability criterion. Accordingly, the proposed model obtains a robust maintenance schedule for generating units immunised against the worst realisation of electricity demand and wind power generation while satisfying the reliability constraint considering equipment unavailabilities. Moreover, maintenance and operation periods are specifically modelled using different resolutions in the proposed multi-resolution GMS approach. To solve the proposed reliability-constrained adaptive-robust multi-resolution model, a new solution approach including Benders cut, reliability cut, and block coordinate descent method is presented. Numerical results on two test systems show the effectiveness of both the proposed GMS model and the proposed solution approach
Adaptive robust optimization framework for day-ahead microgrid scheduling
No full textThis paper proposes a framework to address day-ahead scheduling of a microgrid (MG) with wind, solar and micro-turbine distributed generators as well as batteries, considering the associated uncertainties and AC power flow constraints. The problem uncertainties are wind and solar generations, demand, and grid electricity price. The uncertainties are modelled using bounded intervals within adaptive robust optimization method. Unlike previous robust models presented for MG scheduling, our proposed adaptive robust model optimizes both wait-and-see and here-and-now decisions simultaneously which leads to obtaining a better operating point. In order to make wait-and-see and here-and-now decisions and immunize the model against worst case realizations, the proposed MG scheduling model has been formulated as a tri-level optimization framework. In the first level, here-and-now commitment decisions are made (these are decisions made before realization of uncertainties). In the second stage, the worst case realization of the uncertain parameters is determined. In the third level, the wait-and-see recourse decisions are made (these are decisions made after realization of uncertainties). Since there are before uncertainty-realization decisions, worst uncertainty-realization determination, and after uncertainty-realization decisions, the proposed model becomes a tri-level optimization framework. The proposed adaptive robust tri-level MG scheduling model, the proposed solution approach including AdptRob and ConvAC problems, and the proposed out-of-sample analysis are the main contributions of this paper. A convexified AC power flow model is used in the proposed framework for modeling the distribution network. The 69-bus distribution test system is used to test the proposed adaptive robust model as well as the proposed solution approach which converges very fast. Moreover, the results of the out-of-sample analysis shows that the proposed adaptive robust model results in lower expected cost and lower cost variance. © 2018 Elsevier Lt
A new spinning reserve requirement forecast method for deregulated electricity markets
No full textAncillary services are necessary for maintaining the security and reliability of power systems and constitute an important part of trade in competitive electricity markets. Spinning Reserve (SR) is one of the most important ancillary services for saving power system stability and integrity in response to contingencies and disturbances that continuously occur in the power systems. Hence, an accurate day-ahead forecast of SR requirement helps the Independent System Operator (ISO) to conduct a reliable and economic operation of the power system. However, SR signal has complex, non-stationary and volatile behavior along the time domain and depends greatly on system load. In this paper, a new hybrid forecast engine is proposed for SR requirement prediction. The proposed forecast engine has an iterative training mechanism composed of Levenberg-Marquadt (LM) learning algorithm and Real Coded Genetic Algorithm (RCGA), implemented on the Multi-Layer Perceptron (MLP) neural network. The proposed forecast methodology is examined by means of real data of Pennsylvania-New Jersey-Maryland (PJM) electricity market and the California ISO (CAISO) controlled grid. The obtained forecast results are presented and compared with those of the other SR forecast methods.Electricity market Spinning reserve requirement Hybrid forecast engine LM learning algorithm RCGA
Stochastic multiobjective generation maintenance scheduling using augmented normalized normal constraint method and stochastic decision maker
No full textSummary This paper presents a stochastic multiobjective model for generation maintenance scheduling (GMS) problem and a solution method to solve it. The proposed model properly considers both competing objectives and uncertainty sources of GMS problem. Three competing objective functions including total cost, risk measure, and total emission are simultaneously minimized in the proposed model. Moreover, forced outages of generating units throughout the GMS horizon are characterized by externally generated scenarios. Stochastic programming as an efficient approach to model uncertainty sources has been used in the proposed stochastic multiobjective GMS. Augmented normalized normal constraint (A‐NNC) method is developed as an efficient multiobjective mathematical programming approach to obtain Pareto optimal solutions for the proposed model. Further, a stochastic decision maker based on out‐of‐sample analysis is suggested to find the most preferred solution for GMS problem. The IEEE 118‐bus test system is used to investigate the effectiveness of the proposed model and solution method
Enhanced goal attainment method for solving multi-objective security-constrained optimal power flow considering dynamic thermal rating of lines
No full textSecurity-constrained optimal power flow (SCOPF) is an important problem in power system operation. Dynamic thermal rating (DTR), as an effective method to increase transmission capacity of power systems, has been recently considered in some optimal power flow (OPF) and SCOPF models. Additionally, in today power systems, OPF problem involves various objectives leading to multi-objective OPF models. In this paper, a new multi-objective SCOPF model considering DTR of transmission lines is presented. In addition, a new multi-objective solution method is proposed to solve the multi-objective SCOPF problem. The proposed method is an enhanced version of goal attainment technique in which the search capability of this technique to cover borders of the Pareto frontier is enhanced. The proposed multi-objective DTR-included SCOPF model as well as the proposed multi-objective solution method are tested on the IEEE 118-bus test system and the obtained results are compared with the results of other alternatives. •A new multi-objective DTR-included SCOPF model is presented.•A new multi-objective solution method is proposed.•Proposed method can search the beyond-utopia-hyperplane parts of Pareto frontier.•Effectiveness of the proposed model and proposed method is extensively evaluated
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