Design of Self Powered Internet of Medical Things Using Robust Wolf Optimization Based PI Controller for Health Care Monitoring System

2021 ◽  
Vol 11 (12) ◽  
pp. 3223-3236
Author(s):  
C. Karuppasamy ◽  
S. Venkatanarayanan
Keyword(s):  
Health Condition ◽  
Smart Devices ◽  
Maximum Point ◽  
Solar Pv ◽  
Operational Environment ◽  
Pv System ◽  
Mean Power ◽  
Point Tracking ◽  
Practical Standpoint ◽  
Internet Of Medical Things

In order to gather, transmit, and develop input from the patients for monitoring their health condition through smart devices or devices which use embedded systems, such as processors and transducers and equipment for communication in the healthcare system, the Internet of Medical Things (IoMT) maintains a huge network infrastructure. These devices therefore comprise of a powerful, scalable, lightweight storage knot, which requires power and batteries to run from a practical standpoint. The above shows that the energy collection plays a significant part in the enhancement of IoMT devices’ efficiency and lifespan for its application in healthcare systems. Moreover, in view of the energy acquisition from the operational environment, energy collection is required to make the IoMT devices network more ecologically sustainable. In large solar PV generating systems, partly shading situations usually develop, causing system losses. Thus, in power-voltage curves characteristic of solar systems, the appearance of several peak levels is conceivable. These kinds of problems can be handled by using new multilayer link inverter monitoring techniques. A Maximum Point Tracking Scheme (MPPT) is being suggested for self-proposed Internet of Medical Things for the purpose of optimizing harvesting of solar power on entire PV chain with the usage of RGWO (Robust Wolf Optimization) dependent PI with PWM. The mistaken PV error might create inconsistent power supply to the 7-level H-bridge inverter linked to a grid. The modulation compensation is included in the control system in order to stabilize the grid power. The suggested technique is applied to a 7-level inverter under partial shade conditions. The multi-level modular H-bridge inverter is used for the grid-linked PV system. In addition to a DC link across all H-bridges, a short PV panel string is used for feeding each phase of n H-bridge converters which is connected in series. For pulse switching inverters, the usage of RGWO-based PI with PWM is used. The PWM is used. Then L filters used to reduce the switch harmonics found in the grid are used to link the Cascade multilevel inverter with the grid. A seven-level threephase inverter with three H-bridges allows the individual MPPT control need. The harvester is under direct sunlight and sometimes overcast circumstances realistically tested outside. The wearable IoMT sensor node uses a mean power of 20, 23 mW in a wake-up mode for one hour, and the node’s service life is 28 hours. The performance analysis is finally performed and MATLAB/SIMULINK simulation is performed.

A brief overview of maximum power point tracking algorithm for solar PV system

2021 ◽  
Author(s):  
C. Pavithra ◽  
Pooja Singh ◽  
Venkatesa Prabhu Sundramurthy ◽  
T.S. Karthik ◽  
P.R. Karthikeyan ◽  
...  
Keyword(s):  
Maximum Power Point Tracking ◽  
Tracking Algorithm ◽  
Maximum Power ◽  
Solar Pv ◽  
Pv System ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Solar Pv System ◽  
Power Point

scholarly journals A Comparative Study and Analysis on Conventional Solar PV Based DC-DC Converters and MPPT Techniques

2018 ◽  
Vol 11 (3) ◽  
pp. 831 ◽  
Author(s):  
Premkumar Manoharan ◽  
Karthick K ◽  
Sowmya R
Keyword(s):  
Thermal Power ◽  
Photovoltaic Module ◽  
Atmospheric Conditions ◽  
Solar Pv ◽  
Renewable Energy Resources ◽  
Pv System ◽  
Power Sources ◽  
Advantages And Disadvantages ◽  
Point Tracking ◽  
Solar Pv System

<p>As electricity demand escalated with supply, though there are lot of thermal power station, nuclear energy and other conventional power sources. Yet, there is exhaustion in the above assets and adding dangerous impacts to the atmospheric conditions.  The world searches for sustainable power source that it is normally accessible such as sun and wind. Apart from all the renewable energy resources, solar energy is readily harnessed for domestic application to meet demand. To increase the power conversion efficiency from the solar PV system it is better have a perfect DC to DC converters. The proposed outcome of this paper is to outline the DC to DC converter with MPPT algorithms to concentrate on extreme productivity at roof-top for solar PV application which decreases the cost of energy. In addition to that it also prevents panel miss matching at all environmental conditions for safer DC Voltage with flexible site design especially for domestic applications from the solar photovoltaic module. It is necessary to analyze the converters and MPPT algorithms under closed loop condition for the design and installation of solar PV system to the load or to the grid. This review summarizes few DC to DC converter topologies, maximum power point tracking algorithm and also paid attention on the advantages and disadvantages of these algorithms and topologies.</p>

scholarly journals A Novel Artificial Intelligence based Hybrid Maximum Power Point Tracking Technique for Solar Photovoltaic System

2020 ◽  
Author(s):  
Mohammad junaid Khan
Keyword(s):  
Artificial Intelligence ◽  
Maximum Power ◽  
Solar Pv ◽  
Pv System ◽  
Maximum Power Point ◽  
Ecological Conditions ◽  
Pv Array ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

Abstract Backgrounds: Solar photo-voltaic (PV) arrays have non-linear characteristics with distinctive maximum power point (MPP) which relies on ecological conditions such as solar radiation and ambient temperature. In order to obtain continuous maximum power (MP) from PV arrays under varying ecological conditions, maximum power point tracking (MPPT) control methods are employed. MPPT is utilized to extract MP from the solar PV array, high-performance soft computing techniques can be used as an MPPT technique. Results: In order to show the feasibility and performance of the proposed Artificial Intelligence based Perturbe and Observe (AIAPO) MPPT controller, a simulation analysis has been carried out using the PV system. Combined results with different MPPT systems for power, voltage and current waveforms are the output values increase to 272.4W, 157V and 1.74A respectively. Using proposed AIAPO MPPT provides more accurate and stable result as compared to Perturbe and Observe (PO), Fuzzy Logic (FL) and Artificial Neural Network (ANN) based MPPT Technique. As per the experimentation performed by various MPPT techniques are carried out for PV system which are clearly indicating that the comparative analysis of power, voltage and current performance of PV system (i.e. have been recorded 272.4W, 157V and 1.74A) using proposed MPPT method which is better than the PO based MPPT (i.e. 169.1W, 127V, 1.43A), FL based MPPT technique (i.e. 256.9W, 152V, 1.69A) and ANN based MPPT technique (i.e. 265W, 154V, 1.71A) correspondingly. Conclusions: The aim of this paper is to track MPP from the solar PV array by the proposed hybrid controller for irradiation changes and comparing results with PO, FL and ANN based MPPT controllers. Different MPPT techniques have been used to compute MPP and improved efficiency of the PV panel. AIAPO, ANN, FL and PO MPPT methods have been chosen to obtain this objective. Simulation results showing that the system in which proposed control method has been used gives better performance and reduce fluctuations of the MPP as compared to PO, FL and ANN based MPPT technique at rapid changes of irradiation. In order to fabricate a reliable and real time hybrid system, there is a massive scope of research to develop multi-input renewable energy systems.

scholarly journals Power optimization in partially shaded photovoltaic systems

2018 ◽  
Vol 12 (1) ◽  
pp. 34-38
Author(s):  
Halil Erol ◽  
Mahmut Uçman
Keyword(s):  
Climatic Conditions ◽  
Maximum Power ◽  
Hill Climbing ◽  
Solar Pv ◽  
Pv System ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Point Tracking ◽  
Linear Behaviour ◽  
Power Point

The Power-Voltage characteristic of a photovoltaic (PV) array exhibits non-linear behaviour when exposed to uniform solar irradiance. Maximum Power Point (MPP) tracking is challenging due to the varying climatic conditions in a solar PV system. Moreover, the tracking algorithm becomes more complicated due to the presence of multiple peaks in the power voltage characteristics under the condition of partial shading. This research is devoted to the Stochastic Beam Search (SBS) based algorithm and Stochastic Hill Climbing (SHC) for a maximum power point tracking (MPPT) at a partial shading condition in the PV system. To give a partial shading effect over the entire array of a PV system, a mast is placed in front of the modules. The modules in the array are connected in such a way that one does not need to rewire the electrical connection during the rearrangement of modules. It is validated that the power generation performance of an array under a moving shading condition is increased. Furthermore, it is observed that the SHC method outperforms the SBS method in the MMP tracking.

scholarly journals DC-Microgrid System Design, Control, and Analysis

Electronics ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 124 ◽  
Author(s):  
Adel El-Shahat ◽  
Sharaf Sumaiya
Keyword(s):  
Power Systems ◽  
Direct Current ◽  
Complete System ◽  
Systems Design ◽  
Maximum Power ◽  
Solar Pv ◽  
Pv System ◽  
Dc Microgrid ◽  
Point Tracking ◽  
Power Point

Recently direct current (DC) microgrids have drawn more consideration because of the expanding use of direct current (DC) energy sources, energy storages, and loads in power systems. Design and analysis of a standalone solar photovoltaic (PV) system with DC microgrid has been proposed to supply power for both DC and alternating current (AC) loads. The proposed system comprises of a solar PV system with boost DC/DC converter, Incremental conductance (IncCond) maximum power point tracking (MPPT), bi-directional DC/DC converter (BDC), DC-AC inverter and batteries. The proposed bi-directional DC/DC converter (BDC) lessens the component losses and upsurges the efficiency of the complete system after many trials for its components’ selection. Additionally, the IncCond MPPT is replaced by Perturb & Observe (P&O) MPPT, and a particle swarm optimization (PSO) one. The three proposed techniques’ comparison shows the ranking of the best choice in terms of the achieved maximum power and fast—dynamic response. Furthermore, a stability analysis of the DC microgrid system is investigated with a boost converter and a bidirectional DC-DC converter with the Lyapunov function for the system has been proposed. The complete system is designed and executed in a MATLAB/SIMULINK environment and validated utilizing an OPAL real-time simulator.

scholarly journals Modeling of Photovoltaic MPPT Lead Acid Battery Charge Controller for Standalone System Applications

2020 ◽  
Vol 182 ◽  
pp. 03005
Author(s):  
Rodney H.G. Tan ◽  
Chee Kang Er ◽  
Sunil G. Solanki
Keyword(s):  
Maximum Power ◽  
Maximum Point ◽  
Solar Pv ◽  
Lead Acid Battery ◽  
Pv System ◽  
Photovoltaic Panel ◽  
Battery Charge ◽  
Pv Panel ◽  
Charging Strategy ◽  
Lead Acid

This paper presents the circuitry modeling of the solar photovoltaic MPPT lead-acid battery charge controller for the standalone system in MATLAB/Simulink environment. A buck topology is utilized as a DC-DC converter for the charge controller implementation. The maximum power of the photovoltaic panel is tracked by the Perturb and Observe MPPT algorithm. The battery charge controller charges the lead-acid battery using a three-stage charging strategy. The three charging stages include the MPPT bulk charge, constant voltage absorption charge, and float charge stage. The performance analysis of the model is carried out in the following aspects, there are MPPT tracking performance, battery charging performance and overall charge controller efficiency performance are benchmarked with commercial MPPT charge controller for validation. The performance result shows that the MPPT is capable to track to the PV panel maximum point at any solar irradiance variation within 0.5 seconds with maximum power tracking efficiency up to 99.9 %. The three-stage charging strategy also successfully demonstrated. The overall charge controller average efficiency achieved up to 98.3 % which matches many high end commercial solar PV MPPT charge controller product specifications. This validated model contributes to a better sizing of PV panel and battery energy storage for the small and medium standalone PV system.

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