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

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

Cooler and bigger than thought? Planetary host stellar parameters from the InfraRed Flux Method

Effective temperatures and radii for 92 planet-hosting stars as determined from the InfraRed Flux Method (IRFM) are presented and compared with those given by other authors using different approaches. The IRFM temperatures we have derived are systematically lower than those determined from the spectroscopic condition of excitation equilibrium, the mean difference being as large as 110 K. They are, however, consistent with previous IRFM studies and with the colors derived from Kurucz and MARCS model atmospheres. Comparison with direct measurements of stellar diameters for 7 dwarf stars, which approximately cover the range of temperatures of the planet-hosting stars, suggest that the IRFM radii and temperatures are reliable in an absolute scale. A better understanding of the fundamental properties of the stars with planets will be achieved once this discrepancy between the IRFM and the spectroscopic temperature scales is resolved.Comment: 15 pages, 4 figures. Accepted for publication in Ap

A photometric study of the hot exoplanet WASP-19b

Context: When the planet transits its host star, it is possible to measure the planetary radius and (with radial velocity data) the planet mass. For the study of planetary atmospheres, it is essential to obtain transit and occultation measurements at multiple wavelengths. Aims: We aim to characterize the transiting hot Jupiter WASP-19b by deriving accurate and precise planetary parameters from a dedicated observing campaign of transits and occultations. Methods: We have obtained a total of 14 transit lightcurves in the r'-Gunn, IC, z'-Gunn and I+z' filters and 10 occultation lightcurves in z'-Gunn using EulerCam on the Euler-Swiss telescope and TRAPPIST. We have also obtained one lightcurve through the narrow-band NB1190 filter of HAWK-I on the VLT measuring an occultation at 1.19 micron. We have performed a global MCMC analysis of all new data together with some archive data in order to refine the planetary parameters and measure the occultation depths in z'-band and at 1.19 micron. Results: We measure a planetary radius of R_p = 1.376 (+/-0.046) R_j, a planetary mass of M_p = 1.165 (+/-0.068) M_j, and find a very low eccentricity of e = 0.0077 (+/-0.0068), compatible with a circular orbit. We have detected the z'-band occultation at 3 sigma significance and measure it to be dF_z'= 352 (+/-116) ppm, more than a factor of 2 smaller than previously published. The occultation at 1.19 micron is only marginally constrained at dF_1190 = 1711 (+/-745) ppm. Conclusions: We have shown that the detection of occultations in the visible is within reach even for 1m class telescopes if a considerable number of individual events are observed. Our results suggest an oxygen-dominated atmosphere of WASP-19b, making the planet an interesting test case for oxygen-rich planets without temperature inversion.Comment: Published in Astronomy & Astrophysics. 11 pages, 11 figures, 4 table

Monte Carlo study of the two-dimensional site-diluted dipolar Ising model

By tempered Monte Carlo simulations, we study 2D site-diluted dipolar Ising systems. Dipoles are randomly placed on a fraction x of all L^2 sites in a square lattice, and point along a common crystalline axis. For x_c< x<=1, where x_c = 0.79(5), we find an antiferromagnetic phase below a temperature which vanishes as x approaches x_c from above. At lower values of x, we study (i) distributions of the spin--glass (SG) overlap q, (ii) their relative mean square deviation Delta_q^2 and kurtosis and (iii) xi_L/L, where xi_L is a SG correlation length. From their variation with temperature and system size, we find that the paramagnetic phase covers the entire T>0 range. Our results enable us to obtain an estimate of the critical exponent associated to the correlation length at T=0, 1/nu=0.35(10).Comment: 10 LaTeX pages, 10 figures, 1 table

Geometric Phase and Modulo Relations for Probability Amplitudes as Functions on Complex Parameter Spaces

We investigate general differential relations connecting the respective behavior s of the phase and modulo of probability amplitudes of the form \amp{\psi_f}{\psi}, where $\ket{\psi_f}$ is a fixed state in Hilbert space and $\ket{\psi}$ is a section of a holomorphic line bundle over some complex parameter space. Amplitude functions on such bundles, while not strictly holomorphic, nevertheless satisfy generalized Cauchy-Riemann conditions involving the U(1) Berry-Simon connection on the parameter space. These conditions entail invertible relations between the gradients of the phase and modulo, therefore allowing for the reconstruction of the phase from the modulo (or vice-versa) and other conditions on the behavior of either polar component of the amplitude. As a special case, we consider amplitude functions valued on the space of pure states, the ray space ${\cal R} = {\mathbb C}P^n$, where transition probabilities have a geometric interpretation in terms of geodesic distances as measured with the Fubini-Study metric. In conjunction with the generalized Cauchy-Riemann conditions, this geodesic interpretation leads to additional relations, in particular a novel connection between the modulus of the amplitude and the phase gradient, somewhat reminiscent of the WKB formula. Finally, a connection with geometric phases is established.Comment: 11 pages, 1 figure, revtex

Measuring the transition to homogeneity with photometric redshift surveys

We study the possibility of detecting the transition to homogeneity using photometric redshift catalogs. Our method is based on measuring the fractality of the projected galaxy distribution, using angular distances, and relies only on observable quantites. It thus provides a way to test the Cosmological Principle in a model-independent unbiased way. We have tested our method on different synthetic inhomogeneous catalogs, and shown that it is capable of discriminating some fractal models with relatively large fractal dimensions, in spite of the loss of information due to the radial projection. We have also studied the influence of the redshift bin width, photometric redshift errors, bias, non-linear clustering, and surveyed area, on the angular homogeneity index H2 ({\theta}) in a {\Lambda}CDM cosmology. The level to which an upcoming galaxy survey will be able to constrain the transition to homogeneity will depend mainly on the total surveyed area and the compactness of the surveyed region. In particular, a Dark Energy Survey (DES)-like survey should be able to easily discriminate certain fractal models with fractal dimensions as large as D2 = 2.95. We believe that this method will have relevant applications for upcoming large photometric redshift surveys, such as DES or the Large Synoptic Survey Telescope (LSST).Comment: 14 pages, 14 figure

Neural-Network Vector Controller for Permanent-Magnet Synchronous Motor Drives: Simulated and Hardware-Validated Results

This paper focuses on current control in a permanentmagnet synchronous motor (PMSM). The paper has two main objectives: The first objective is to develop a neural-network (NN) vector controller to overcome the decoupling inaccuracy problem associated with conventional PI-based vector-control methods. The NN is developed using the full dynamic equation of a PMSM, and trained to implement optimal control based on approximate dynamic programming. The second objective is to evaluate the robust and adaptive performance of the NN controller against that of the conventional standard vector controller under motor parameter variation and dynamic control conditions by (a) simulating the behavior of a PMSM typically used in realistic electric vehicle applications and (b) building an experimental system for hardware validation as well as combined hardware and simulation evaluation. The results demonstrate that the NN controller outperforms conventional vector controllers in both simulation and hardware implementation

Reaching the boundary between stellar kinematic groups and very wide binaries. III. Sixteen new stars and eight new wide systems in the beta Pictoris moving group

Aims. We look for common proper motion companions to stars of the nearby young beta Pictoris moving group. Methods. First, we compiled a list of 185 beta Pictoris members and candidate members from 35 representative works. Next, we used the Aladin and STILTS virtual observatory tools, and the PPMXL proper motion and Washington Double Star catalogues to look for companion candidates. The resulting potential companions were subjects of a dedicated astro-photometric follow-up using public data from all-sky surveys. After discarding 67 sources by proper motion and 31 by colour-magnitude diagrams, we obtained a final list of 36 common proper motion systems. The binding energy of two of them is perhaps too small to be considered physically bound. Results. Of the 36 pairs and multiple systems, eight are new, 16 have only one stellar component previously classified as a beta Pictoris member, and three have secondaries at or below the hydrogen-burning limit. Sixteen stars are reported here for the first time as moving group members. The unexpected large number of high-order multiple systems, 12 triples and two quadruples among 36 systems, may suggest a biased list of members towards close binaries or an increment of the high-order-multiple fraction for very wide systems.Comment: A&A in pres

Optimal Dispatch of Pumped Storage Hydro Cascade under Uncertainty

In this paper, we propose an optimal dispatch scheme for a pumped storage hydro cascade that maximizes the energy per cubic meter of water in the system taking into account uncertainty in the net load variations. To this end, we introduce a model to describe the behaviour of a pumped storage hydro cascade and formulate its optimal dispatch. We then incorporate forecast scenarios in the optimal dispatch, and define a robust variant of the developed system. The resulting optimization problem is intractable due to the infinite number of constraints. Using tools from robust optimization, we reformulate the resulting problem in a tractable form that is amenable to existing numerical tools and show that the computed dispatch is immunised against uncertainty. The efficacy of the proposed approach is demonstrated by means of a realistic case study based on the Seven Forks system located in Kenya