Cost Efficient Distributed Load Frequency Control in Power Systems

The introduction of new technologies and increased penetration of renewable resources is altering the power distribution landscape which now includes a larger numbers of micro-generators. The centralized strategies currently employed for performing frequency control in a cost efficient way need to be revisited and decentralized to conform with the increase of distributed generation in the grid. In this paper, the use of Multi-Agent and Multi-Objective Reinforcement Learning techniques to train models to perform cost efficient frequency control through decentralized decision making is proposed. More specifically, we cast the frequency control problem as a Markov Decision Process and propose the use of reward composition and action composition multi-objective techniques and compare the results between the two. Reward composition is achieved by increasing the dimensionality of the reward function, while action composition is achieved through linear combination of actions produced by multiple single objective models. The proposed framework is validated through comparing the observed dynamics with the acceptable limits enforced in the industry and the cost optimal setups

Load Frequency Control: A Deep Multi-Agent Reinforcement Learning Approach

The paradigm shift in energy generation towards microgrid-based architectures is changing the landscape of the energy control structure heavily in distribution systems. More specifically, distributed generation is deployed in the network demanding decentralised control mechanisms to ensure reliable power system operations. In this work, a Multi-Agent Reinforcement Learning approach is proposed to deliver an agentbased solution to implement load frequency control without the need of a centralised authority. Multi-Agent Deep Deterministic Policy Gradient is used to approximate the frequency control at the primary and the secondary levels. Each generation unit is represented as an agent that is modelled by a Recurrent Neural Network. Agents learn the optimal way of acting and interacting with the environment to maximise their long term performance and to balance generation and load, thus restoring frequency. In this paper we prove using three test systems, with two, four and eight generators, that our Multi-Agent Reinforcement Learning approach can efficiently be used to perform frequency control in a decentralised way

Numerical Analysis of National Travel Data to Assess the Impact of UK Fleet Electrification

Accurately predicting the future power demand of electric vehicles is important for developing policy and industrial strategy. Here we propose a method to create a representative set of electricity demand profiles using survey data from conventional vehicles. This is achieved by developing a model which maps journey and vehicle parameters to an energy consumption, and applying it individually to the entire data set. As a case study the National Travel Survey was used to create a set of profiles representing an entirely electric UK fleet of vehicles. This allowed prediction of the required electricity demand and sizing of the necessary vehicle batteries. Also, by inferring location information from the data, the effectiveness of various charging strategies was assessed. These results will be useful in both National planning, and as the inputs to further research on the impact of electric vehicles

Typological variation in language contact: A phonological analysis of Italiot Greek

This dissertation investigates the phonology of Italiot Greek (IG) from both a synchronic and a diachronic perspective, pursuing two core objectives: first, to provide an up-to-date description of the phonological system of IG, highlighting the deviations from Medieval Greek as well as the vast cross- and intra-dialectal variation, and, second, to account for the typological changes IG has undergone and formalize the convergence with the Romance grammatical system. The description of the phonological system of IG is based on original data obtained via fieldwork in the IG-speaking enclaves (Salento and Calabria). The in-depth presentation covers phoneme inventories, phonological processes, the organization of the syllable, sandhi phenomena, and stress properties. Moreover, it focuses attention on the diachronic changes with respect to the consonant inventories and certain phonological processes. Special emphasis is placed on substantial modifications in syllable structure, compared to the Medieval Greek system, and the processes these changes have triggered; specifically, (a) the gradual reduction of place and manner features that are admitted in the coda, which is manifested through diachronic shifts towards less marked values; (b) the licensing of complex onsets at the left edge of the root, which allows long-distance metathesis of liquids. These phenomena not only differentiate contemporary IG from its ancestor as well as from virtually any other Modern Greek dialect, but also constitute crucial points of convergence with Romance dialects due to language contact. Within Optimality Theory (Prince & Smolensky 1993/2004), the dissertation proposes a novel typological analysis of these major changes in the syllable structure of IG. Following Alber & Prince (2015, in prep.), the analysis places IG within a broader typology of place and manner changes as well as long-distance metathesis and identifies the crucial ranking conditions, i.e. the typological properties, that define each grammar of the typological system. Minimally varying grammars, i.e. grammars that share all but one property value, are shown to constitute chronologically adjacent stages in the history of IG (see Alber 2015; Alber & Meneguzzo 2016). In light of this, stepwise diachronic changes are explained as minimal switches in the property values. Crucially, the divergence of the IG grammar from the Greek system and its converge with Romance is accounted for through the lens of minimal differences in the property values. Thus, the dissertation offers an innovative formal account of contact-induced grammatical change

Fluid transport through porous media: A novel application of kinetic Monte Carlo simulations

With increasing global energy demands, unconventional formations, such as shale rocks, are becoming an important source of natural gas. Current efforts are focused on understanding fluid dynamics to maximise natural gas yields. Although shale gas is playing an increasingly important role in the global energy industry, our knowledge of the fundamentals of fluid transport through multiscale and heterogeneous porous media is incomplete, as both static and dynamic properties of confined fluids differ tremendously from those at the macroscopic scale. Transport models, derived from atomistic studies, are frequently used to bridge this gap. However, capturing and upscaling the interactions between the pore surface and fluids remains challenging. In this thesis, a computationally efficient stochastic approach is implemented to simulate fluid transport through complex porous media. One-, two-, and three-dimensional kinetic Monte Carlo models were developed to predict methane transport in heterogeneous pore networks consisting of hydrated and water-free micro-, meso-, and macropores, representative of shale rock minerals. Molecular dynamics (MD) simulations, experimental imaging and adsorption data, which describe the surface – fluid interaction and the pore network features respectively were utilised to inform the KMC models. The stochastic approach was used to (1) quantify the effect of the pore network characteristics (pore size, chemistry, connectivity, porosity, and anisotropy) on the transport of supercritical methane, (2) estimate the permeability of an Eagle Ford shale sample and evaluate the effect of proppants on permeability, and (3) to upscale atomistic insights and predict fluid diffusivity through different size pores. The results obtained were consistent with the analytical solutions of the diffusion equation, experimental data, and MD simulations, respectively, demonstrating the effectiveness of the stochastic approach. In addition, the applicability of less computationally intensive deterministic approaches was examined using multiple case studies; recommendations are provided on the optimal conditions under which each method can be used

Appealing to the Authority of a Learned Patriarch: New Evidence on Gennadios Scholarios’ Responses to the Questions of George Branković

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Optimized FTR portfolio construction: the speculator's problem

In this thesis, we propose a systematic methodology to construct an optimized financial transmission rights (FTR) portfolio for the speculator, who purchases FTR holdings in order to have returns that are as good as possible. The conventional approach of selecting the FTR in a portfolio requires the exhaustive evaluation of all the possible FTR combinations, which in a large-scale network is computationally too demanding a task, particularly when the wide variations in the behavior of the locational marginal price (LMP) differences of nodes over the many hours of the holding period are taken into account. In order to make the speculator's problem more manageable, we recast the problem into a form that allows us to exploit the salient characteristics of power systems, the topological nature of the underlying network and the historical data, so as to gain mathematical insights that we apply to develop the proposed scheme. The speculator returns are collected from the hourly day ahead markets (DAMs) only for those hours that the grid is congested, i.e., the flows on one or more lines are at their maximum limits. Each MW flowing through those lines incurs a transmission usage cost. Unlike a physical transaction from a source node to a sink node that holds FTR in the amount of the flow and receives reimbursement for the transmission usage charges from the independent grid operator (IGO), the speculator who holds FTR for the same node pair simply receives those revenues, because of lack of physical flows. Thus, the identification of congested lines is a key step in the construction methodology. So, rather than focusing on the LMP differences of node pairs to choose FTR, we select node pairs such that the selected congested lines are on their paths from the source nodes to the sink nodes. Conceptually, we specify FTR such that transactions with same node pairs and amounts induce real power flows on the selected congested lines. The strategy of the speculator is to select each congested line and his level of participation on the congested flows on the line. In practice, the speculator cannot do this for all the congested lines, because that would imply the acquisition of too large a number of FTR, whose premiums add to his costs and, thus, lower his returns. Under the assumption that the past behavior continues in the future, he judiciously chooses a subset of lines whose transmission usage costs exceeded the speculator's specified price and time fraction thresholds historically. This subset forms the basis of the optimized FTR portfolio construction. In our proposed scheme, we construct the FTR portfolio with minimum number of node pairs; i.e., we find the minimum number of transactions that induce the desired real power flows on the subset of selected lines. To demonstrate the computational efficiency of the construction algorithm, we select a subset of nodes to specify the FTR node pairs in the portfolio. The manageability of the problem is further aided by focusing on a small number of node pairs. Fewer node pairs improve the manageability. The recasting of the problem in terms of congested lines, rather than LMP differences of node pairs, results in a simplified solution methodology that is amenable to practical implementation. We have extensively tested the proposed methodology on multiple test systems and we discuss representative case study results. The results on three test systems, including the PJM ISO network, illustrate the effectiveness of the proposed approach and provide insights into the nature of the problem

Typological variation in language contact: A phonological analysis of Italiot Greek

This dissertation investigates the phonology of Italiot Greek (IG) from both a synchronic and a diachronic perspective, pursuing two core objectives: first, to provide an up-to-date description of the phonological system of IG, highlighting the deviations from Medieval Greek as well as the vast cross- and intra-dialectal variation, and, second, to account for the typological changes IG has undergone and formalize the convergence with the Romance grammatical system. The description of the phonological system of IG is based on original data obtained via fieldwork in the IG-speaking enclaves (Salento and Calabria). The in-depth presentation covers phoneme inventories, phonological processes, the organization of the syllable, sandhi phenomena, and stress properties. Moreover, it focuses attention on the diachronic changes with respect to the consonant inventories and certain phonological processes. Special emphasis is placed on substantial modifications in syllable structure, compared to the Medieval Greek system, and the processes these changes have triggered; specifically, (a) the gradual reduction of place and manner features that are admitted in the coda, which is manifested through diachronic shifts towards less marked values; (b) the licensing of complex onsets at the left edge of the root, which allows long-distance metathesis of liquids. These phenomena not only differentiate contemporary IG from its ancestor as well as from virtually any other Modern Greek dialect, but also constitute crucial points of convergence with Romance dialects due to language contact. Within Optimality Theory (Prince & Smolensky 1993/2004), the dissertation proposes a novel typological analysis of these major changes in the syllable structure of IG. Following Alber & Prince (2015, in prep.), the analysis places IG within a broader typology of place and manner changes as well as long-distance metathesis and identifies the crucial ranking conditions, i.e. the typological properties, that define each grammar of the typological system. Minimally varying grammars, i.e. grammars that share all but one property value, are shown to constitute chronologically adjacent stages in the history of IG (see Alber 2015; Alber & Meneguzzo 2016). In light of this, stepwise diachronic changes are explained as minimal switches in the property values. Crucially, the divergence of the IG grammar from the Greek system and its converge with Romance is accounted for through the lens of minimal differences in the property values. Thus, the dissertation offers an innovative formal account of contact-induced grammatical change

Stochastic Hosting Capacity in LV Distribution Networks

Hosting capacity is defined as the level of penetration that a particular technology can connect to a distribution network without causing power quality problems. In this work, we study the impact of solar photovoltaics (PV) on voltage rise. In most cases, the locations and sizes of the PV are not known in advance, so hosting capacity must be considered as a random variable. Most hosting capacity methods study the problem considering a large number of scenarios, many of which provide little additional information. We overcome this problem by studying only cases where voltage constraints are active, with results illustrating a reduction in the number of scenarios required by an order of magnitude. A linear power flow model is utilised for this task, showing excellent performance. The hosting capacity is finally studied as a function of the number of generators connected, demonstrating that assumptions about the penetration level will have a large impact on the conclusions drawn for a given network

Pupils’ representations of rivers on 2D and 3D maps

AbstractIn this research we investigate the conceptions of 11 year old pupils about the flow of a river from its sources to the sea. 2D and 3D small scale maps were used from 287 pupils from 15 different schools situated in urban and rural environments from mountainous, plain and coastal areas of Greece. The purpose of the study was to investigate whether 3D maps contribute to a better understanding of a fluvial system on the physical landscape, to identify stereotypical imagery about the direction of the river flow, and to identify the type of map that will help children visualize and better understand features of the natural environment. Pupils completed an individual questionnaire with closed and open ended questions and designed rivers on 2D and 3D maps. The results were analyzed and categorized into model types according to the direction, the representation of the mouth of the river, the consistency of the river flow with the physical landscape, the types of lines used to draw the river's flow. A number of misconceptions are discussed. While the correct drawings on 2D maps surpass those on 3D maps, there is higher percentage of pupils drawing straight line river flow on 2D than on 3D maps suggesting that they cannot interpret the physical landscape through the map. Over two thirds of the pupils chose the 3D maps as more helpful to complete the task