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Solar energy has attracted significant attentions around the globe, while one of its most crucial task is to harvest the maximum available solar power under different weather conditions, also known as maximum power point tracking (MPPT). This paper proposes a novel memetic reinforcement learning (MRL) based MPPT scheme for photovoltaic (PV) systems under partial shading condition (PSC). In order to enhance the searching ability of MRL, the memetic computing structure is incorporated into reinforcement learning (RL). In particular, a virtual population is used for the global information exchange between different agents, such that the learning rate can be dramatically accelerated. Besides, a RL based local search is designed in each memeplex, which can effectively improve the optimum quality. Comprehensive case studies are undertaken, such as start-up test, step change of solar irradiation, ramp change of solar irradiation and temperature, and field atmospheric data of Hong Kong. The PV system responses are then evaluated and compared to that of seven typical MPPT algorithms. • A novel MRL is proposed for maximum power point control of PV systems under PSC. • The memetic computing framework can improve the optimization efficiency of MRL. • A virtual population improves the convergence stability via a global coordination. • MRL can make PV systems generate more energy under different weather conditions. • MRL based MPPT can effectively reduce the power fluctuation of PV systems. [ABSTRACT FROM AUTHOR]

Polymethylpentene (PMP) polymers can be used to make advanced optics, especially for midinfrared (MIR) ultrafast optics. In this study, an optical parametric converter pumped by a Ti sapphire femtosecond laser was used to investigate the polymer. The thermal effect generated by loosely focused femtosecond near mid-infrared (MIR) pulses in bulky materials is observed in real-time, and the polymer exhibits thermal stability and conformability. To avoid strong linear absorption and to increase the nonlinear damage threshold, the spectral region for ultrafast applications is 1310 nm (0.95 eV)–1350 nm (0.92 eV). For the process in region VI, there is a sign of stronger coupling for short-wavelength photons, and the pulse duration is recommended to be lower than 160 fs. In the ultraviolet (UV) region, filamentary writing using a low-focused beam, the laser peak power was selected in the range of 2.2 MW–9.2 MW. High-density bulky gratings were written. The refractive-index modulation was significant, and the polymer exhibited highly nonlinear features. This study provides insights into the applications and production of PMP polymers in laser optics and laser engineering. • In situ thermal observation on filamentation built by near MIR femtosecond pulses in polymer. • Using super-continuum spectra to characterise filamentary process of PMP. • Writing bulky gratings with tightly focused beam. [ABSTRACT FROM AUTHOR]

This paper designs a novel maximum power point tracking (MPPT) technique for centralized thermoelectric generation (TEG) system under heterogeneous temperature difference (HeTD). Since the HeTD can result in multiple local maximum power points (LMPPs) for centralized TEG system, a fast atom search optimization (FASO) is designed to approximate the global maximum power point (GMPP) from multiple LMPPs. In order to accelerate the convergence for a high quality solution, the Euclidian distance ratio of the original atom search optimization (ASO) is employed to adaptively update according to the dynamic optimization results, as well as for the number of neighbours for each atom. Through case studies such as start-up test, step variation of temperature, stochastic temperature change, and analyse of sensitivity are carried out, in which the practicability and superiority of FASO are compared with that of MPPT method based on a single LMPP and four meta-heuristic algorithms. Simulation results show that the energy output produced by FASO ranges from 101.64% to 451.49% to the alternatives. Finally, through hardware-in-the-loop (HIL) experiment based on a dSpace, the feasibility of the hardware realization is confirmed, in which the difference between simulation results and HIL experiment results is less than 2.3%. • A novel MPPT model of centralized thermoelectric generation system is established. • Heterogeneous temperature difference causes multiple local maximum power points. • A novel fast atom search optimization is designed for MPPT of centralized TEG system. • Adynamic balance between exploration and exploitation is constructed in FASO. • FASObased MPPTobtainsalarger energy output than other five comparative methods. [ABSTRACT FROM AUTHOR]

• A maximum power point tracking of thermoelectric generation system is constructed. • The power output feature is analyzed under non-uniform temperature distribution. • A greedy search based data-driven method is used for maximum power point tracking. • The proposed method can rapidly search a high-quality maximum power point. • Both of energy loss and power fluctuation can be reduced by the proposed method. The generation efficiency of thermoelectric generation system is relatively low, thus how maximize its power production is of great importance. This paper designs a novel greedy search based data-driven method for centralized thermoelectric generation system to achieve maximum power point tracking under non-uniform temperature distribution. In order to effectively distinguish the local maximum power points and the global maximum power point under non-uniform temperature distribution, greedy search based data-driven employs a two-layer feed-forward neural network to accurately fit the curve between the power output and the controllable variable based on the real-time updated operation data. Based on the approximation curve, a greedy search is designed to efficiently approach the global maximum power point from a shrinking search space. Cases studies such as start-up test, step variation of temperature, stochastic temperature change, and analyse of sensitivity, are implemented to prove the effectiveness and superiority of the proposed algorithm. Simulation results verify that the proposed method can generate the highest energy under non-uniform temperature distribution condition, e.g., 391.34%, 115.71%, 110.92%, and 109.43% to that of perturb and observe, particle swarm optimization, whale optimization algorithm, and grey wolf optimizer in the stochastic temperature change. Lastly, the implementation feasibility of the proposed method is demonstrated by the hardware-in-the-loop experiment based on dSpace platform. [ABSTRACT FROM AUTHOR]

• Different circuits are compared to identify the most suitable compensation circuit. • The compensation circuit is designed in the modal system. • Capacitance of the compensation circuit are simplified as the shunt reactor. • The designed compensation circuits are compared with the natural HWTL. The compensation circuits are the core to improve the flexibility of practical application of half-wavelength transmission lines (HWTL), which are restricted to the fixed transmission length due to the constant fundamental frequency. This paper proposes a mode-phase transformation based method to design the parameters of compensation circuits after comparison of frequency responses of three kinds of compensation circuits, e.g., T segments, Π segments and L segments. At first, the compensation circuit parameters are obtained in the modal system that separates the coupling multiconductor system into isolated circuits to avoid the complexity of the three-phase system. Then, the compensation circuit parameters can be transformed into multiconductor system by modal-phase transformation, which accomplishes the compensation circuit parameter design in three-phase system. Lastly, the parameters acquired by the proposed method are compared with the natural HWTL. Comprehensive simulations are undertaken which validate that the proposed method is more suitable for tuning HWTL. [ABSTRACT FROM AUTHOR]

This paper designs a robust fractional-order sliding-mode control (RFOSMC) of a fully active battery/supercapacitor hybrid energy storage system (BS-HESS) used in electric vehicles (EVs), in which two bidirectional DC/DC converters are employed to decouple battery pack and supercapacitor pack from DC bus based on the classical 5th-order averaged model. Rule-based strategy (RBS) is firstly employed as the energy management strategy (EMS) to generate the battery current reference. Then, RFOSMC scheme is developed as the underlying controller to globally compensate nonlinearities and various uncertainties of BS-HESS by the real-time perturbation estimation via a sliding-mode state and perturbation observer (SMSPO). Two outputs are chosen, e.g., battery current and DC bus voltage, which are also the only states that need to be measured for the control system design, thus RFOSMC is relatively easy to be implemented. The control performance of RFOSMC is thoroughly investigated in comprehensive case studies to that of other three typical controllers. Finally, a hardware-in-the-loop (HIL) test is undertaken to validate the effectiveness of the proposed control scheme. • Anovel NRFOCis designed for BSM-HESSused inEVs application. • RBS is used to optimally assign power between battery and SMES. • Bio-inspired MSSA is used to optimally tune the NRFOC parameters. • Satisfactory control performance is realized under various operation conditions. • dSpace based HIL experiment validates the implementation feasibility. [ABSTRACT FROM AUTHOR]

This study attempts to develop a novel nonlinear robust fractional-order control (NRFOC) of a battery/superconducting magnetic energy storage (SMES) hybrid energy storage system (BSM-HESS) used in electric vehicles (EVs), of which rule-based strategy (RBS) is adopted to optimally assign the power demand. Based on the online perturbation estimation via a high-gain perturbation observer (HGPO), NRFOC is devised as the underlying controller which is able to fully compensate nonlinearities and modelling uncertainties of BSM-HESS through a fractional-order PID controller as the additional input. Here, the introduced fractional differentiator and fractional integrator can considerably improve the control performance while only two states, e.g., the battery current and DC bus voltage, need to be measured, in which no accurate system model is required. Case studies are undertaken to evaluate the effectiveness and merits of NRFOC to other control schemes. Moreover, the control costs of NRFOC required in heavy load condition is just 79.00%, 87.11%, and 82.96% to that of PID control, feedback linearization control (FLC), and sliding-mode control (SMC), respectively. At last, its implementation feasibility is validated by hardware-in-the-loop (HIL) experiment based on dSpace platform. • A novel NRFOC is designed for BSM-HESS used in EVs application. • RBS is used to optimally assign power between battery and SMES. • Bio-inspired MSSA is used to optimally tune the NRFOC parameters. • NRFOC owns the highest robustness with only 8.79% power variation. • DSpace based HIL experiment validates the implementation feasibility. [ABSTRACT FROM AUTHOR]

This paper develops a novel passive fractional-order sliding-mode control (PFOSMC) of a supercapacitor energy storage (SCES) system in microgrid with distributed generators. Firstly, a storage function is constructed and thoroughly analysed to investigate the inherent physical characteristics of SCES systems. Then, the beneficial terms are carefully retained for the sake of transient responses improvement, while the other detrimental terms are fully removed to achieve a globally control consistency. In order to further enhance the robustness of the closed-loop system, a fractional-order sliding-mode control (FOSMC) framework is synthesized as an additional input, which employs the fractional-order P D α sliding surface as well as an energy reshaping mechanism to realize a more flexible control performance. Four case studies, including (a) Active power and reactive power supply, (b) System restoration under power grid fault, (c) Power support under stochastic solar energy and wind energy integration, and (d) Robustness with system parameter uncertainties, are carried out to study the control performance of PFOSMC compared to that of PID control, interconnection and damping assignment passivity-based control (IDA-PBC), and FOSMC, Finally, a hardware-in-the-loop (HIL) experiment using dSpace platform is undertaken to validate its implementation feasibility. • A PFOSMC is designed for SCES system in microgrids. • The physical properties of SCES system is examined via passivity theory. • FOSMC framework is synthesized to enhance robustness. • Energy reshaping mechanism is adopted to improve dynamic responses. [ABSTRACT FROM AUTHOR]

• An MPPT model of centralized TEG system under NTD condition is constructed. • A novel adaptive compass search is developed for MPPT of centralized TEG system. • An adaptive sequence of exploration directions is used for searching enhancement. • The proposed method can make the centralized TEG system generate more energy. • The proposed method can reduce the power fluctuation of centralized TEG system. This paper proposes a novel adaptive compass search (ACS) for maximum power point tracking (MPPT) of centralized thermoelectric generation (TEG) system under non-uniform temperature distribution (NTD) condition. The centralized TEG system employs only one converter thus the overall costs of converter implementation and maintenance can be significantly reduced compared to that of string-type and modularized configurations. However, multiple maximum power points (MPPs) usually appear for centralized TEG system when exposed under NTD condition. In order to effectively and efficiently seek the global MPP, an adaptive sequence of exploration directions is employed to considerably enhance the global searching ability of ACS through the previous searching results, which is the main improvement against to the original compass search (CS) associated with fixed sequence. Four case studies, including start-up test, step change of temperature, random temperature variation, and sensitivity analysis, are carried out to verify the effectiveness and advantage of ACS in comparison to that of perturb and observe (P&O), particle swarm optimization (PSO), whale optimization algorithm (WOA), grey wolf optimizer (GWO), and CS, respectively. Lastly, a dSpace based hardware-in-the-loop (HIL) experiment is undertaken to validate its hardware implementation feasibility. [ABSTRACT FROM AUTHOR]