State Estimation for the Individual and the Population in Mean Field Control with Application to Demand Dispatch

This paper concerns state estimation problems in a mean field control setting. In a finite population model, the goal is to estimate the joint distribution of the population state and the state of a typical individual. The observation equations are a noisy measurement of the population. The general results are applied to demand dispatch for regulation of the power grid, based on randomized local control algorithms. In prior work by the authors it has been shown that local control can be carefully designed so that the aggregate of loads behaves as a controllable resource with accuracy matching or exceeding traditional sources of frequency regulation. The operational cost is nearly zero in many cases. The information exchange between grid and load is minimal, but it is assumed in the overall control architecture that the aggregate power consumption of loads is available to the grid operator. It is shown that the Kalman filter can be constructed to reduce these communication requirements,Comment: To appear, IEEE Trans. Auto. Control. Preliminary version appeared in the 54rd IEEE Conference on Decision and Control, 201

Individual risk in mean-field control models for decentralized control, with application to automated demand response

Flexibility of energy consumption can be harnessed for the purposes of ancillary services in a large power grid. In prior work by the authors a randomized control architecture is introduced for individual loads for this purpose. In examples it is shown that the control architecture can be designed so that control of the loads is easy at the grid level: Tracking of a balancing authority reference signal is possible, while ensuring that the quality of service (QoS) for each load is acceptable on average. The analysis was based on a mean field limit (as the number of loads approaches infinity), combined with an LTI-system approximation of the aggregate nonlinear model. This paper examines in depth the issue of individual risk in these systems. The main contributions of the paper are of two kinds: Risk is modeled and quantified: (i) The average performance is not an adequate measure of success. It is found empirically that a histogram of QoS is approximately Gaussian, and consequently each load will eventually receive poor service. (ii) The variance can be estimated from a refinement of the LTI model that includes a white-noise disturbance; variance is a function of the randomized policy, as well as the power spectral density of the reference signal. Additional local control can eliminate risk: (iii) The histogram of QoS is truncated through this local control, so that strict bounds on service quality are guaranteed. (iv) This has insignificant impact on the grid-level performance, beyond a modest reduction in capacity of ancillary service.Comment: Publication without appendix to appear in the 53rd IEEE Conf. on Decision and Control, December, 201

A Holistic Approach to Forecasting Wholesale Energy Market Prices

Electricity market price predictions enable energy market participants to shape their consumption or supply while meeting their economic and environmental objectives. By utilizing the basic properties of the supply-demand matching process performed by grid operators, known as Optimal Power Flow (OPF), we develop a methodology to recover energy market's structure and predict the resulting nodal prices by using only publicly available data, specifically grid-wide generation type mix, system load, and historical prices. Our methodology uses the latest advancements in statistical learning to cope with high dimensional and sparse real power grid topologies, as well as scarce, public market data, while exploiting structural characteristics of the underlying OPF mechanism. Rigorous validations using the Southwest Power Pool (SPP) market data reveal a strong correlation between the grid level mix and corresponding market prices, resulting in accurate day-ahead predictions of real time prices. The proposed approach demonstrates remarkable proximity to the state-of-the-art industry benchmark while assuming a fully decentralized, market-participant perspective. Finally, we recognize the limitations of the proposed and other evaluated methodologies in predicting large price spike values.Comment: 14 pages, 14 figures. Accepted for publication in IEEE Transactions on Power System

Zap Q-Learning for Optimal Stopping Time Problems

The objective in this paper is to obtain fast converging reinforcement learning algorithms to approximate solutions to the problem of discounted cost optimal stopping in an irreducible, uniformly ergodic Markov chain, evolving on a compact subset of $\mathbb{R}^n$. We build on the dynamic programming approach taken by Tsitsikilis and Van Roy, wherein they propose a Q-learning algorithm to estimate the optimal state-action value function, which then defines an optimal stopping rule. We provide insights as to why the convergence rate of this algorithm can be slow, and propose a fast-converging alternative, the "Zap-Q-learning" algorithm, designed to achieve optimal rate of convergence. For the first time, we prove the convergence of the Zap-Q-learning algorithm under the assumption of linear function approximation setting. We use ODE analysis for the proof, and the optimal asymptotic variance property of the algorithm is reflected via fast convergence in a finance example

Synthetic gauge fields stabilize a chiral spin liquid phase

We calculate the phase diagram of the SU($N$) Hubbard model describing fermionic alkaline earth atoms in a square optical lattice with on-average one atom per site, using a slave-rotor mean-field approximation. We find that the chiral spin liquid predicted for $N\ge5$ and large interactions passes through a fractionalized state with a spinon Fermi surface as interactions are decreased before transitioning to a weakly interacting metal. We also show that by adding an artificial uniform magnetic field with flux per plaquette $2\pi/N$, the chiral spin liquid becomes the ground state for all $N\ge 3$ at large interactions, persists to weaker interactions, and its spin gap increases, suggesting that the spin liquid physics will persist to higher temperatures. We discuss potential methods to realize the artificial gauge fields and detect the predicted phases

Hourly paid teachers in UK universities: Findings from an exploratory survey

The Higher Education sector in the UK has seen some unprecedented changes in recent years. One of the most striking changes has been the widespread use of casualised contracts in UK universities. In 2012-13, almost 34 per cent of academics worked part-time, nearly 36 per cent had fixed-term contracts, 25 per cent of all full-time contracts were fixed-term, and almost 56 per cent of all part-time contracts were fixed-term (HESA, 2014). A recent Freedom of Information Request by UCU revealed that 75 (53 per cent) of institutions that responded use zero hours contracts for teaching, research and/or academic related staff (UCU, 2013). Jenny Chen and Ana Lopes from UWE have conducted an exploratory study of the impact of casualised contracts in UK universities

A New Control Method for Input-Output Harmonic Elimination of the Pwm Boost-Type Rectifier Under Extreme Unbalanced Operating Conditions

Under severe fault conditions in the distribution system, not only input voltages but also input impedances must be considered as unbalanced. This paper presents a new control method for input-output harmonic elimination of the pulsewidth-modulation (PWM) boost-type rectifier under conditions of both unbalanced input voltages and unbalanced input impedances. The range of imbalance in both input voltages and input impedances, for which the proposed method is valid, is analyzed in detail. An analytical approach for complete harmonic elimination shows that PWM boost-type rectifier can operate at unity power factor under extremely unbalanced operating conditions resulting in a smooth (constant) power flow from ac to dc side. Based on the analyses in open-loop configuration, a feedforward control method is proposed. Elimination of harmonics at ac and dc side of the converter affects the cost of dc link capacitor and ac side filter. The proposed method is very useful when the PWM boost-type rectifier is subject to extreme imbalance due to severe fault conditions in the power system. In addition, by using the proposed method, the PWM boost-type rectifier can be operated from the single-phase supply in cases where three-phase source is not available. Simulation results show excellent response and stable operation of the PWM boost-type rectifier under the proposed control algorithm. Experimental and simulation results are in excellent agreemen

Non-Coherent Multiuser Massive MIMO-OFDM with Differential Modulation

Proceedings of: ICC 2019 - 2019 IEEE International Conference on Communications (ICC), 20-24 may, 2019, Shanghai.Massive multiple-input multiple-output (MIMO) and orthogonal frequency division multiplexing (OFDM) are wireless technologies adopted by the Fifth Generation (5G) of mobile communications. The channel estimation and pre/postequalization processes in coherent detection schemes for massive MIMO-OFDM are a challenging task, where several issues are faced, such as pilot contamination, channel calibration, matrix inversions, among others. Moreover, they increase the energy consumption and latency of the system. A non-coherent technique relying on DPSK constellation has been proposed for a singlecarrier scheme, assuming flat-fading. In our paper, we extend this technique to be combined with OFDM, where the channel is doubly dispersive (time and frequency). We will show that the differential modulation can be performed either in the time or frequency domain, where the latter suffers from an additional phase rotation, which should be estimated and compensated. We provide the analytical expression of the signal-to-interferenceand-noise ratio (SINR) for both cases, and we show numerical results in order to verify our analysis.This work has been funded by project TERESA-ADA (TEC2017-90093-C3-2-R) (MINECO/AEI/FEDER, UE)