Application of meta-analytical probabilistic approach for reliability benefits reflective optimal transmission costing – the case of India

In the deregulated Power markets it is necessary to have a appropriate Transmission Pricing methodology that also takes into account “Congestion and Reliability”, in order to ensure an economically viable, equitable, and congestion free power transfer capability, with high reliability and security. This thesis presents results of research conducted on the development of a Decision Making Framework (DMF) of concepts and data analytic and modelling methods for the Reliability benefits Reflective Optimal “cost evaluation for the calculation of Transmission Cost” for composite power systems, using probabilistic methods. The methodology within the DMF devised and reported in this thesis, utilises a full AC Newton-Raphson load flow and a Monte-Carlo approach to determine, Reliability Indices which are then used for the proposed Meta-Analytical Probabilistic Approach (MAPA) for the evaluation and calculation of the Reliability benefit Reflective Optimal Transmission Cost (ROTC), of a transmission system. This DMF includes methods for transmission line embedded cost allocation among transmission transactions, accounting for line capacity-use as well as congestion costing that can be used for pricing using application of Power Transfer Distribution Factor (PTDF) as well as Bialek’s method to determine a methodology which consists of a series of methods and procedures as explained in detail in the thesis for the proposed MAPA for ROTC. The MAPA utilises the Bus Data, Generator Data, Line Data, Reliability Data and Customer Damage Function (CDF) Data for the evaluation of Congestion, Transmission and Reliability costing studies using proposed application of PTDF and other established/proven methods which are then compared, analysed and selected according to the area/state requirements and then integrated to develop ROTC. Case studies involving standard 7-Bus, IEEE 30-Bus and 146-Bus Indian utility test systems are conducted and reported throughout in the relevant sections of the dissertation. There are close correlation between results obtained through proposed application of PTDF method with the Bialek’s and different MW-Mile methods. The novel contributions of this research work are: firstly the application of PTDF method developed for determination of Transmission and Congestion costing, which are further compared with other proved methods. The viability of developed method is explained in the methodology, discussion and conclusion chapters. Secondly the development of comprehensive DMF which helps the decision makers to analyse and decide the selection of a costing approaches according to their requirements. As in the DMF all the costing approaches have been integrated to achieve ROTC. Thirdly the composite methodology for calculating ROTC has been formed into suits of algorithms and MATLAB programs for each part of the DMF, which are further described in the methodology section. Finally the dissertation concludes with suggestions for Future work.

‘‘Model age-based” and ‘‘copy when uncertain” biases in children’s social learning of a novel task

Theoretical models of social learning predict that individuals can benefit from using strategies that specify when and whom to copy. Here the interaction of two social learning strategies, model age-based biased copying and copy when uncertain, was investigated. Uncertainty was created via a systematic manipulation of demonstration efficacy (completeness) and efficiency (causal relevance of some actions). The participants, 4- to 6-year-old children (N = 140), viewed both an adult model and a child model, each of whom used a different tool on a novel task. They did so in a complete condition, a near-complete condition, a partial demonstration condition, or a no-demonstration condition. Half of the demonstrations in each condition incorporated causally irrelevant actions by the models. Social transmission was assessed by first responses but also through children’s continued fidelity, the hallmark of social traditions. Results revealed a bias to copy the child model both on first response and in continued interactions. Demonstration efficacy and efficiency did not affect choice of model at first response but did influence solution exploration across trials, with demonstrations containing causally irrelevant actions decreasing exploration of alternative methods. These results imply that uncertain environments can result in canalized social learning from specific classes of mode

Do children copy an expert or a majority? Examining selective learning in instrumental and normative contexts

This study examined whether instrumental and normative learning contexts differentially influence 4- to 7-year-old children’s social learning strategies; specifically, their dispositions to copy an expert versus a majority consensus. Experiment 1 (N = 44) established that children copied a relatively competent “expert” individual over an incompetent individual in both kinds of learning context. In experiment 2 (N = 80) we then tested whether children would copy a competent individual versus a majority, in each of the two different learning contexts. Results showed that individual children differed in strategy, preferring with significant consistency across two different test trials to copy either the competent individual or the majority. This study is the first to show that children prefer to copy more competent individuals when shown competing methods of achieving an instrumental goal (Experiment 1) and provides new evidence that children, at least in our “individualist” culture, may consistently express either a competency or majority bias in learning both instrumental and normative information (Experiment 2). This effect was similar in the instrumental and normative learning contexts we applied.