Application of quadratically-constrained model predictive control in power systems

Simulations for the quadratically-constrained model predictive control (qc-MPC) with power system linear models are studied in this work. In qc-MPC, the optimization is imposed with two additional constraints to achieve the closed-loop system stability and the recursive-feasibility simultaneously. Instead of engaging the traditional terminal constraint for MPC, both constraints in qc-MPC are imposed on the first control vector of the MPC control sequence. As a result, qc-MPC has the potential for further extension to the control of network centric power systems. The algorithm of qc-MPC has been developed in a previous paper. Here, simulation studies with small-signal linear models of three typical power systems are presented to demonstrate its efficacy. We also develop a computational strategy for the decentralized static state-feedback control using the same quadratic dissipativity constraint as of the qc-MPC. Only state constraints are considered in the state feedback design. A comparison is then provided in the simulation study of qc-MPC relatively to the constrained-state feedback control.This publication is made possible by the Singapore National Research Foundation under its Campus for Research Excellence And Technological Enterprise (CREATE) programmeThis is the author accepted manuscript. The final version is available from IEEE via http://dx.doi.org/10.1109/ICARCV.2014.706430

Parallelisation of sequential Monte Carlo for real-time control in air traffic management

This paper presents the parallelisation of a Sequential Monte Carlo algorithm, and the associated changes required when applied to the problem of conflict resolution and aircraft trajectory control in air traffic management. The target problem is non-linear, constrained, non-convex and multi-agent. The new method is shown to have a 98.5% computational time saving over that of a previous sequential implementation, with no degradation in path quality. The computation saving is enough to allow real-time implementation.This work was supported by EPSRC (Engineering and Physical Sciences Research Council - UK) Grant No. EP/G066477/1In proceedings of the IEEE Conference on Decision and Control 201

Multiplexed model predictive control of interconnected systems

A Multiplexed Model Predictive Control (MMPC) scheme with Quadratic Dissipativity Constraint (QDC) for interconnected systems is presented in this paper. A centralized MMPC is designed for the global system, wherein the controls of subsystems are updated sequentially to reduce the computational time. In MMPC, the global state vector of the interconnected system is required by the optimization. The QDC is converted into an enforced stability constraint for the MMPC as an alternative to the terminal constraint and terminal cost in this approach. The nominal recursive feasibility for the global system and the iterative feasibility for the local subsystems are obtained via set operations on the invariant sets. The admissible sets for the control inputs are obtained and employed in this approach for the QDC-based stability constraint. The set operations are speed up by multiple magnitudes thanks to the implementation of multiplexed inputs in MMPC. Numerical simulations with Automatic Generation Control (AGC) in power systems having tie-lines demonstrate the theoretical development.The authors acknowledge the support by the Singapore National Research Foundation (NRF) under its Campus for Research Excellence And Technological Enterprise (CREATE) programme and the Cambridge Centre for Advanced Research in Energy Efficiency in Singapore (Cambridge CARES), C4T project.This is the author accepted manuscript. The final version is available from IEEE via http://dx.doi.org/10.1109/CDC.2015.740256

Control of aircraft in the terminal manoeuvring area using parallelised sequential Monte Carlo

This paper reports on the use of a parallelised Model Predictive Control, Sequential Monte Carlo algorithm for solving the problem of conflict resolution and aircraft trajectory control in air traffic management specifically around the terminal manoeuvring area of an airport. The target problem is nonlinear, highly constrained, non-convex and uses a single decision-maker with multiple aircraft. The implementation includes a spatio-temporal wind model and rolling window simulations for realistic ongoing scenarios. The method is capable of handling arriving and departing aircraft simultaneously including some with very low fuel remaining. A novel flow field is proposed to smooth the approach trajectories for arriving aircraft and all trajectories are planned in three dimensions. Massive parallelisation of the algorithm allows solution speeds to approach those required for real-time use.This work was supported by EPSRC (Engineering and Physical Sciences Research Council - UK) Grant No. EP/G066477/1AIAA Conference on Guidance, Navigation and Control 201

Covariance Analysis of LAV Robust Dynamic State Estimation in Power Systems

In power system state estimation, the robust Least Absolute Value robust dynamic estimator is well-known. However, the covariance of the state estimation error cannot be obtained easily. In this paper, an analytical equation is derived using Influence Function approximation to analyze the covariance of the robust Least Absolute Value dynamic state estimator. The equation gives insights into the precision of the estimation and can be used to express the variances of the state estimates as functions of measurement noise variances, enabling the selection of sensors for specified estimator precision. Simulations on the IEEE 14-bus, 30-bus and 118-bus systems are given to illustrate the usefulness of the equation. Monte-Carlo experiments can also be used to determine the covariance, but many data points are needed and hence many runs are required to achieve convergence. Our result shows that to obtain the covariance of the state estimation error, the analytical equation proposed in this paper is four orders of magnitude faster than a 10,000-run Monte-Carlo experiment on both the IEEE 14-bus and 30-bus systems.National Research Foundation Singapor

A hierarchical EMS for aggregated BESSs in energy and performance-based regulation markets

The battery energy storage systems (BESSs) have been increasingly installed in the power system, especially with the growing penetration rate of the renewable energy sources. However, it is difficult for BESSs to be profitable due to high capital costs. In order to boost the economic value of BESSs, this paper proposes a hierarchical energy management system (HiEMS) to aggregate multiple BESSs, and to achieve multi-market business operations. The proposed HiEMS optimizes the multi-market bids considering a realistic BESS performance model, and coordinates the BESSs and manages their state of charge (SOC) values, according to their price penalties based on dynamically generated annualized cost. By taking part in the energy market and regulation market at the same time, the cost-performance index (CPI) of the BESS aggregation is greatly improved. The impact of photovoltaic generation (PV) on system performance and CPI is also studied.This work is supported in part by DNV GL Energy (formerly KEMA) Technology Centre, Nanyang Technological University, and the Energy Innovation Research Programme (EIRP, Award No. NRF2014EWT-EIRP002-005), administrated by the Energy Market Authority (EMA). The EIRP is a competitive grant call initiative driven by the Energy Innovation Programme Office, and funded by the National Research Foundation (NRF) Singapore

Model-based Aeroservoelastic Design and Load Alleviation of Large Wind Turbine Blades

This paper presents an aeroservoelastic modeling approach for dynamic load alleviation in large wind turbines with trailing-edge aerodynamic surfaces. The tower, potentially on a moving base, and the rotating blades are modeled using geometrically non-linear composite beams, which are linearized around reference conditions with arbitrarily-large structural displacements. Time-domain aerodynamics are given by a linearized 3-D unsteady vortexlattice method and the resulting dynamic aeroelastic model is written in a state-space formulation suitable for model reductions and control synthesis. A linear model of a single blade is used to design a Linear-Quadratic-Gaussian regulator on its root-bending moments, which is finally shown to provide load reductions of about 20% in closed-loop on the full wind turbine non-linear aeroelastic model

53BP1 can limit sister-chromatid rupture and rearrangements driven by a distinct ultrafine DNA bridging-breakage process

Chromosome missegregation acts as one of the driving forces for chromosome instability and cancer development. Here, we find that in human cancer cells, HeLa and U2OS, depletion of 53BP1 (p53-binding protein 1) exacerbates chromosome non-disjunction resulting from a new type of sister-chromatid intertwinement, which is distinct from FANCD2-associated ultrafine DNA bridges (UFBs) induced by replication stress. Importantly, the sister DNA intertwinements trigger gross chromosomal rearrangements through a distinct process, named sister-chromatid rupture and bridging. In contrast to conventional anaphase bridge-breakage models, we demonstrate that chromatid axes of the intertwined sister-chromatids rupture prior to the breakage of the DNA bridges. Consequently, the ruptured sister arms remain tethered and cause signature chromosome rearrangements, including whole-arm (Robertsonian-like) translocation/deletion and isochromosome formation. Therefore, our study reveals a hitherto unreported chromatid damage phenomenon mediated by sister DNA intertwinements that may help to explain the development of complex karyotypes in tumour cells