Label-free bio-sensing is a critical functionality underlying a variety of health- and security-related applications. Micro-/nano-photonic devices are well suited for this purpose and have emerged as promising platforms in recent years. Here we propose and demonstrate an approach that utilizes the optical spring effect in a high-Q coherent optomechanical oscillator to dramatically enhance the sensing resolution by orders of magnitude compared with conventional approaches, allowing us to detect single bovine serum albumin proteins with a molecular weight of 66 kDa at a signal-to-noise ratio of 16.8. The unique optical spring sensing approach opens up a distinctive avenue that not only enables biomolecule sensing and recognition at individual level, but is also of great promise for broad physical sensing applications that rely on sensitive detection of optical cavity resonance shift to probe external physical parameters.

In this paper, distributed energy storage systems (ESSs) are proposed to solve the voltage rise/drop issues in lowvoltage (LV) distribution networks with high penetration of rooftop photovoltaics (PVs). During peak PV generation period, the voltages are mitigated by charging the ESSs, and the stored energy is discharged for voltage support during peak load period. The impact of storage device integrated with PV source on feeder voltages is investigated in detail. A coordinated control method which includes both distributed and localized controls is proposed for distributed ESSs. The distributed control using consensus algorithm regulates the feeder voltages within the required limits, while the localized control regulates the state of charge (SoC) of each ESS within desired SoC range. The entire control structure ensures voltage regulation while effectively utilizes storage capacity under various operation conditions. The proposed control method is evaluated in LV distribution networks and the simulation results validate the effectiveness of this method.

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Inserting an array of nearly 100 similar lenses into a common focal system, the uniformity of the illumination of a target can evidently be improved without being affected by the near-field distribution of laser beams. We report here geometrical- and physical-optics analyses of the lens array and compare them with the experimental results.

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Microgrid (MG) is a cyber-physical system with coupled power and communication networks. The centralized secondary control of MGs with periodical communications restricts system efficiency and resilience. This paper proposes a distributed event-triggered secondary control scheme in islanded MGs with its cyber-physical implementation. The proposed control scheme operates with reduced frequency of communications depending on the MG states change 'events' (e.g. load variations and communication failures). Besides, the secondary control objectives, including frequency/voltage regulation and accurate real/reactive power sharing, are decoupled into two timescales. Instead of designing eventtriggering conditions (ETCs) for each secondary control functions, only ETCs for power sharing control in slower timescale are designed. Thus, the communication burden is significantly reduced since communications among neighbour controllers are only needed at the event-triggered time. The proposed controller has been tested on a hardware-in-the-loop (HIL) platform, where the physical system is modelled in OPAL-RT and the cyber system is realized in Raspberry Pis. The control effectiveness is validated by the HIL results. 1 Index Terms-distributed event-triggered control, cyberphysical systems, microgrids, hardware-in-the-loop, raspberry pi.

In future power systems, widespread small-scale energy storage systems (ESSs) can be aggregated to provide ancillary services. In this context, this paper aims to integrate energy storage aggregators (ESAs) into the load frequency control (LFC) framework for power system frequency control. Firstly, a system disturbance observer is designed to supplement the secondary frequency control, where the ESA can respond to the estimated disturbance and accelerate the system frequency recovery. Then, within the ESA, a finite-time leader-follower consensus algorithm is proposed to control the small-scale ESSs via sparse communication network. This algorithm ensures that the ESAs can track the frequency control signals and the state-ofcharge balancing among each ESS in finite-time. The external characteristics of the ESA will resemble to that of one large-scale ESS. Numerical examples demonstrate the convergence of the ESA under different communication graphs. The effectiveness of the entire framework for power system frequency control is validated under a variety of scenarios.

Dynamic optimization and multi-objective optimization have separately gained increasing attention from the research community during the last decade. However, few studies have been reported on dynamic multi-objective optimization (dMO) and scarce effective dMO methods have been proposed. In this paper, we fulfill these gabs by developing new dMO test problems and new effective dMO algorithm. In the newly designed dMO problems, Pareto-optimal decision values (i.e., Pareto-optimal solutions: POS) or both POS and Pareto-optimal objective values (i.e., Pareto-optimal front: POF) change with time. A new multi-strategy ensemble multi-objective evolutionary algorithm (MS-MOEA) is proposed to tackle the challenges of dMO. In MS-MOEA, the convergence speed is accelerated by the new offspring creating mechanism powered by adaptive genetic and differential operators (GDM); a Gaussian mutation operator is employed to cope with premature convergence; a memory like strategy is proposed to achieve better starting population when a change takes place. In order to show the advantages of the proposed algorithm, we experimentally compare MS-MOEA with several algorithms equipped with traditional restart strategy. It is suggested that such a multi-strategy ensemble approach is promising for dealing with dMO problems.