IoT based Performance Monitoring and Improvement of Solar (PV) Array during Various Partial Shading Conditions with the help of perturb and observe method

In context of increasing supply-demand gap due to consistent depletion/shortage of fossil fuels, improvement in living standards causing excessive reliance on electric power along with the rising environmental threats posed by the conventional power generation processes, renewable sources have becom

Project Title

IoT based Performance Monitoring and Improvement of Solar (PV) Array during Various Partial Shading Conditions with the help of perturb and observe method

Project Area of Specialization

Internet of Things

Project Summary

In context of increasing supply-demand gap due to consistent depletion/shortage of fossil fuels, improvement in living standards causing excessive reliance on electric power along with the rising environmental threats posed by the conventional power generation processes, renewable sources have become an indispensable future for the power sector. Photovoltaic (PV) technology is promising to be one of the best renewable energy sources with brilliant futurism due to its simple and easy installation, low maintenance and better reliability with no fuel cost. However, like most of the renewable sources, solar cells have non-steady power extraction characteristics influenced by the factors such as illumination, temperature and panel age. 

One of the crucial environmental condition, affecting the performance of solar panels known as partial shading (PS) causes the solar cells to exhibit multiple peaks in its P-V characteristics, which are known as local maximum power points (LMPP), while peak of highest power is called global maximum power point (GMPP). A number of MPPT algorithms have been addressed in the literature which serve to track the MPP for various operating conditions. However theses algorithms fail to track the MPP of solar panels under partial shading conditions such as having less convergence speed, low accuracy and oscillations at the MPP point.

Internet of Things (IoT) is an arising and a futuristic technology which is effectively and efficiently edifying our way of life by controlling a machine at distant with the help of cloud server.  Generally, in our country Pakistan, solar systems for electric power generation is manual. In this modern day life, we need an intelligent system for automatically monitoring and controlling solar power generation. Therefore, we are going to use a rising technology named as “IoT” in solar tracking system for remotely monitoring and controlling solar power generation to make the system smart, robust, and more reliable. In this study, an enhanced adaptive Perturb and Observe (AP&O) MPPT technique is proposed, which is simple with good dynamic properties, and easily implementable with already available drive compatible hardware, during partial shading condition such that, the settling time is small, complexity is less and hardware implementation is easier. The transient period required for reaching steady state value is almost negligible in case of proposed strategy with no further complication in hardware implementation. The performance of proposed algorithm is validated by experimental results obtained during various partial shading conditions.

Project Objectives

The present work is intended to design an enhanced perturb and observe based MPPT algorithm for photovoltaic power generation system along with IoT based smart monitoring and control. The proposed algorithm reduces the convergence time, achieves better tracking accuracy with no oscillation around MPP point while IoT allows an intelligent system for remote monitoring and controlling solar power generation. The project objectives can be summarized as under:

• To identify the drawbacks leading to failures of conventional MPPT algorithms in case of PV modules with partial shading.
• To develop a smooth optimized power tracking system for PV module based on adaptive enhanced perturb and observe (P & O) system.
• To design IoT based control system for continuous monitoring and control remotely.
• Simulation of proposed strategy in Matlab/Simulink environment.
• To validate the performance of proposed model through prototype development with different levels (weak, moderate, strong) of shading.

Project Implementation Method

To evaluate the performance of proposed MPPT algorithm (enhanced P&O), a PV array consisting of a number of solar modules connected in parallel is chosen. Apparently, a solar module under uniform irradiance exhibit a unique maximum power point (MPP) in its PV characteristics. However with partial shading conditions a solar cell has a number of PV characteristic each having a unique MPP. These are known as local maximum power points (LMPP). For different levels of shading PV characteristics are obtained experimentally to identify these MPPs.

Once MPPs are determined, an algorithm must be implemented which can accurately track these MPP points under partial shading. For the present case it is simply a dc/dc boost converter acting as an interface between PV module and load. The duty cycle of boost converter is readily determined by the MPP locating algorithm which works as follows:

• The algorithm starts by measuring voltage and current levels of PV module to determine the output power.
• The power and voltage difference between two successive iterations is calculated to determine the direction in which PV curve is being traced.
• If the power and voltage values are such that, the curve is being traced away from MPP point, the algorithm alters the duty cycle of the boost converter in a way such that the load resistance seen by PV system causes it to shift its voltage and hence power values in a direction towards MPP point and vice versa.
•  The algorithm is adaptive in a way that if operating point is farther away from MPP point, it increase the step size to reduce the convergence time, while if operating point is closer to MPP it reduces the step size to increase the stability causing less oscillations around MPP point.

The afore-described algorithm is tested for various shading levels and its convergence time, tracking accuracy and stability is observed to validate its performance against conventional MPPT techniques. Finally in IoT based intelligent monitoring system is incorporated in the setup that allows an efficient and reliable remote control to reduce human efforts/maintenance costs.

Benefits of the Project

This work presents a perfect technique for optimizing the operation of photovoltaic systems by continuously extracting the maximum power even under the worst cases of atmospheric variations. The proposed technique provides a robust solution that can overcome the drawbacks of power tracking algorithms under partial shading conditions, such as the failure of actual maximum power extraction, low tracking speed, complexity in the required computations and in implementation, low accuracy, and high oscillation around the tracked maximum power. Therefore, the proposed algorithm will enable the best performance for any applied photovoltaic configuration without any extra cost and complexity, thus enhancing the utilization of photovoltaic renewable energy for significant applications.

The Internet of Things (IOT) is a futuristic technology that allows a cloud server to remotely control or capture a machine. It is now employed in all aspects of life and automates daily operations, allowing for data transmission between humans and machines as well as remote monitoring and control of physical items. By implementing intelligence based system human error can be avoided and this controller will provide cost effective solution and will improve solar panel efficiency such as high convergence speed and high accuracy. The benefits can be further put as under:

• Affordable and clean power generation through PV.
• Easy maintenance.
• Purely depends upon solar energy which is easily available everywhere.
• Very less human effort due to computational intelligence involved in the system.
• Easy monitoring and controllability from anywhere.

Technical Details of Final Deliverable

Failure of conventional MPPT algorithms in tracking the MPPs of a photovoltaic system in presence of partial shading conditions has rendered them inappropriate. Keeping in view those drawbacks a computational intelligence based MPPT based on IoT is proposed such that it keeps smooth track of all the local MPPs exhibited by PV panel in its P-V characteristics. The proposed model consists of a PV array interfaced to dc load through dc-dc boost converter, the duty cycle of which is judiciously decided by an algorithm based on enhanced perturb and observe method. Using this smart solar PV system based on IoT, the required time for the management of plant is reduced.  Also, remote monitoring and control through IOT technology reduce work of manual directions for solar PV plant by making it computational intelligence-based system. Besides this,  the conventional MPPT algorithms show lower efficiency. The partial shading also leads to hot spots, resulting in physical damage of the panel. An improved MPPT technique has thus been developed to overcome those disadvantages. The proposed MPPT does the smooth tracking without further complicating the hardware implementation.  The transient period (convergence time) required for reaching steady state value is almost negligible and ultimately it adds to the efficiency of this smart solar system.

Final Deliverable of the Project

HW/SW integrated system

Core Industry

Energy

Other Industries

Education

Core Technology

Internet of Things (IoT)

Other Technologies

Clean Tech

Sustainable Development Goals

Affordable and Clean Energy, Sustainable Cities and Communities, Climate Action

Required Resources

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