Particle swarm optimization based maximum power point tracking for Partially Shaded Photovoltaic Arrays

This paper presents particle swarm optimization based perturb and observe (PSO-P&O) algorithm for maximizing output power of photovoltaic (PV) array under partially shaded conditions (PSC). During PSC, the P-V characteristic of PV will become more complex with multiple maximum power points (MPP). Most of the conventional maximum power point tracking (MPPT) algorithms, such as P&O, will be trapped at the local MPP and hence limiting the maximum power generation. As such, investigation on PSO-P&O algorithm is carried out to maximize the PV generated power principally under PSC operation. The performances of conventional P&O and the proposed PSO-P&O algorithms are investigated particularly on the transient and steady state responses under various shaded conditions. The simulation results show the developed PSO- P&O algorithm is able to facilitate the PV array to reach the global MPP and assist the PV array to produce more stable output power compared to the conventional P&O algorithm

mcSi and CdTe solar photovoltaic challenges: Pathways to progress

Multi-crystalline Si (mcSi) and CdTe solar photovoltaic technologies have gained significant improvement. Shockley–Queisser (S-Q) limit consideration further progress of open-circuit voltage (Voc), fill factor (FF) and the efficiency of CdTe cell are anticipated. Sub-bandgap parasitic absorption, grain boundaries and back contacts recombination lessening are vital to minimize these opto-electrical losses. mcSi and CdTe heterojunction (HJ) cells’ intrinsic thermal co-efficient to optical (bandgap) loss, interface and bulk defects and related thermal diffusion are possible opto-electrical limitations. Wafer based mcSi passivated emitter rear contact (PERC) and tunnel oxide passivated contact (TOPCon) over Al back surface field (Al-BSF) contact have incredibly progressed in current decades. Similar as mcSi cell, advancement of commercial CdTe cell is desired. Reviewing CdTe and mcSi/cSi (photo-physical similarity) based one hundred and fifty research papers it is comprehended that not only band aligned but also thin, transparent passivation window and electron reflector as barrier are central to minimize the shortcomings. CdTe absorber thickness-dependent Voc and fill factor trade-off while diverse window and barrier layer performance review are realized optical transparencies to electrical loss outcome. Stated opto-electrical development purpose thin absorber supportive band and lattice matching double HJ or graded CdSexTe1-x/CdTe HJ is possible realistic pathways. mcSi thin wafer is exposed to minimize bulk degradation that is caring for a stable and cost-effective PV. Finally, CdTe solar cells present limitations to laboratory design towards the best progression trails are focused. It is anticipated to limit the levelized cost of energy (LCOE)

Optimal allocation of soft open point devices in renewable energy integrated distribution systems

Renewable Energy Sources (RESs) are increasingly integrated into distribution networks due to their undeniable technical and environmental advantages. Despite all the economical and environmental benefits of RESs, they can negatively affect the distribution network. For instance, their output generations are not predictable, and these uncertainties will lead to some operational challenges. Also, RESs are affected by the climate situation, and there are high correlations between them, generally. The correlations between RESs intensify the operational challenges of energy systems. Soft open points (SOPs) are flexible power electronic devices that can effectively increase the efficiency of energy systems. They realize accurate active power control and reactive power compensation to reduce power losses and adjust three-phase voltages. This paper focused on the optimal determination of the location and setting points of SOPs in unbalanced distribution networks in the presence of correlated uncertain sources. The genetic algorithm (GA) was used to solve the main optimization problem, and the correlation between uncertain sources was managed by the Nataf transformation technique. The IEEE 37 bus test system was utilized to illustrate the effectiveness of the proposed method

Deep reinforcement learning with robust deep deterministic policy gradient

Recently, Deep Deterministic Policy Gradient (DDPG) is a popular deep reinforcement learning algorithms applied to continuous control problems like autonomous driving and robotics. Although DDPG can produce very good results, it has its drawbacks. DDPG can become unstable and heavily dependent on searching the correct hyperparameters for the current task. DDPG algorithm risk overestimating the Q values in the critic (value) network. The accumulation of estimation errors as time elapse can result in the reinforcement agent trapping into a local optimum or suffering from disastrous forgetting. Twin Delayed DDPG (TD3) mitigated the overestimation bias problem but might not exploit full performance due to underestimation bias. In this paper Twin Average Delayed DDPG (TAD3) is proposed for specific adaption to TD3 and shows that the resulting algorithm perform better than TD3 in a challenging continuous control environment

Power and current limiting strategy based on droop controller with floating characteristic for grid-connected distributed generations

The Grid-Connected Droop-Controlled Distributed Generations (GCDCDGs) are widely used in power systems. However, their power flow is very sensitive to the Upstream Grid (UG) frequency and voltage magnitude fluctuations. This paper focuses on the power and current limiting of inverter-interfaced GCDCDGs under UG frequency and/or voltage magnitude drops. GCDCDG output power and current increase under the UG frequency drop, and if this increase exceeds the maximum of them, current limiters are saturated and according to P ∼ ω droop characteristic the GCDCDG frequency does not track the UG frequency, and this frequency difference leads to power oscillation between DG and UG and the system becomes unstable. In this paper, a new strategy based on the droop-control method is proposed to limit the output power and current of GCDCDGs without using a current limiter that realizes a stable operation under the mentioned conditions. In the proposed method instead of increasing the droop coefficients to limit P and Q at their constraints, the droop curves move down after powers and currents exceed maximum values, using two supplementary control signals. The performance of the proposed method is demonstrated with simulation results using MATLAB/Simulink environment under several case studies

Autonomous underwater vehicle Manoeuvrability studies

This research project is aimed to understanding the manoeuvrability of AUV and develop mathematical model to describe behaviour of vehicle interaction with the operating environment. A hovering type of AUV was defined base on the operation need of the AUV where it is likely to be applied in underwater research and exploring activities. Due to the increase demand of AUV, major efforts have been made in developing AUV in overcoming the challenging scientific and engineering problems caused by the unstructured ocean environment. The theoretical modeling of the AUV had being developed via Newtonian mechanics approach and the 6-DOF dynamic equations of motion are derived throughout the process. The governing equations mainly constitute terms of rigid body inertia matrix, hydrodynamic damping matrix, restoring forces and moments, environmental and propulsion forces and moments. Subsequently, a feasible 3-D solid modeling of the AUV had been designed through iterative method with CAD and CAE verification. Fluid interactions and manoeuvrability design analysis was achieved through implementation of CFD tool, COSMOSFloWorks. The theoretical modeling developed had been simplified under several relevant assumptions and the second order non-linear differential . equation solved using the programming software MA TI.AB to investigate the translational motion of the vehicle in the surging direction. The result from the model is the AUV motion relation, drag force and lift coefficient that could be utilized in the further AUV prototype development. The solid 3D design of the AUV had been achieved through spiral design process of iterative method. The method involves design statement, preliminary design, conceptual design and detailed design. Fundamental hydrodynamic knowledge had been applied to facilitate the design of the AUV. The optimum thruster location had been identified and the optimum design achieved. The scope of physical solid modeling had been effectively implemented via CAD software. SolidWorks licence by Universiti Malaysia Sabah had been utilized as the CAD platform in developing the AUV 3D model Stalling phenomena had also been identified as 15° through simulation software, COSMOSFloWorks. The stall pitching angle defines where the unstable manoeuvring of the vehicle will occur. COSMOSFloWorks also had been utilized to examine the effect of current velocities towards the AUV lift and drag coefficients. The simulation was conducted at various Reynolds number and various pitching angles. The investigation has found that the lift coefficient and drag coefficient increases as the pitching angle increases, but the considered range of Reynolds number had no significant effect on these hydrodynamic coefficients. These results were important for the design of better guidance and control systems for the AUV to achieve effective manoeuvring in current flow environment

Modelling and control of partially shaded photovoltaic arrays

The photovoltaic (PV) array controlled by Maximum Power Point Tracking (MPPT) method for optimum PV power generation, particularly when the PV array is under partially shaded condition is presented in this paper. The system modelling is carried out in MATLAB-SIMULINK where the PV array is formed by five series connected identical PV modules. Under uniform solar irradiance conditions, the PV module and the PV array present nonlinear P-V characteristic but the maximum power point (MPP) can be easily identified. However, when the PV array is under shaded conditions, the P-V characteristic becomes more complex with the present of multiple MPP. While the PV array operated at local MPP, the generated power is limited. Thus, the investigation on MPPT approach is carried out to maximize the PV generated power even when the PV array is under partially shaded conditions (PSC). Fuzzy logic is adopted into the conventional MPPT to form fuzzy logic based MPPT (FMPPT) for better performance. The developed MPPT and FMPPT are compared, particularly the performances on the transient response and the steady state response when the array is under various shaded conditions. FMPPT shows better performance where the simulation results demonstrate FMPPT is able to facilitate the PV array to reach the MPP faster while it helps the PV array to produce a more stable output power