A two-stage MPPT controller for PV system based on the improved artificial bee colony and simultaneous heat transfer
Linjuan Gong1, Guolian Hou2, Congzhi Huang3
1School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China; Xi'an Thermal Power Research Institute Co., Ltd., Xi'an 710054, China.
ISA Transactions
|June 26, 2022
Summary
This study introduces a two-stage maximum power point tracking (MPPT) strategy for photovoltaic (PV) systems. It uses an improved artificial bee colony algorithm and simultaneous heat transfer search (SHTS) for faster and more accurate power optimization, especially under partial shading.
Area of Science:
- Renewable Energy Systems
- Control Engineering
- Artificial Intelligence in Engineering
Background:
- Photovoltaic (PV) systems require efficient Maximum Power Point Tracking (MPPT) for optimal battery charging.
- Existing MPPT methods struggle with accuracy and speed, particularly under dynamic conditions like partial shading.
- Optimizing the duty cycle of DC-DC converters is crucial for maximizing PV energy harvest.
Purpose of the Study:
- To propose a novel bionic two-stage MPPT control strategy for enhancing tracking accuracy and speed.
- To optimize the duty cycle of DC-DC converters in PV systems for improved energy yield.
- To address the challenges of multiple peaks and partial shading in PV arrays.
Main Methods:
- A two-stage MPPT approach combining a fast positioning stage and a precise determination stage.
- An improved artificial bee colony (ABC) algorithm with a simplified probability selection and novel employed bee phase for rapid global peak region identification.
- The Simultaneous Heat Transfer Search (SHTS) algorithm for accurate global maximum power point (GMPP) acquisition within the identified region, featuring reduced parameter subjectivity and parallel search capabilities.
Main Results:
- The proposed two-stage MPPT strategy demonstrates excellent performance in precisely identifying the GMPP of PV systems, even with multiple peaks.
- The strategy achieves phenomenal rapidity in tracking the GMPP compared to conventional methods.
- Extensive simulations confirm superior tracking speed and accuracy under partial shading conditions.
Conclusions:
- The bionic two-stage MPPT control strategy offers a significant advancement in PV system efficiency and reliability.
- The combined approach of improved ABC and SHTS algorithms effectively balances exploration and exploitation for robust MPPT.
- This method provides a superior solution for real-time PV power optimization, especially under challenging environmental conditions.
Keywords:
Improved artificial bee colonyMaximum power point trackingPartial shading conditionsPhotovoltaic (PV) systemSimultaneous heat transfer searchMore Related Videos
07:18Experimental System of Solar Adsorption Refrigeration with Concentrated Collector
Published on: October 18, 2017
14.7K
08:13SwarmSight: Real-time Tracking of Insect Antenna Movements and Proboscis Extension Reflex Using a Common Preparation and Conventional Hardware
Published on: December 25, 2017
8.3K
Related Concept Videos
01:19PID Controller
230
Proportional-Integral-Derivative (PID) controllers are widely used in various control systems to enhance stability and performance. In a thermostat, it adjusts heating or cooling based on the temperature difference between the actual and desired levels. They are often used in automotive speed systems, effectively managing sudden speed changes while maintaining a constant speed under varying conditions. On the other hand, PI controllers, commonly employed in voltage regulation, enhance stability...
230
01:20Maxwell-Boltzmann Distribution: Problem Solving
1.7K
Individual molecules in a gas move in random directions, but a gas containing numerous molecules has a predictable distribution of molecular speeds, which is known as the Maxwell-Boltzmann distribution, f(v).
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
1.7K
01:16Maximum Power Transfer
379
Numerous practical applications within engineering disciplines, such as telecommunications, necessitate optimizing power delivery to a connected load. This pursuit, however, entails inherent internal losses, which can either equal or exceed the power supplied to the load. The Thevenin equivalent circuit is helpful in finding the maximum power a linear circuit can deliver to a load. It is assumed in this context that the load resistance can be adjusted.
By substituting the entire circuit with...
By substituting the entire circuit with...
379
01:24PI Controller: Design
470
Proportional Integral (PI) controllers are a fundamental component in modern control systems, widely used to enhance performance and mitigate steady-state errors. They are particularly effective in applications such as automatic brightness adjustment on smartphones, where they excel at mitigating steady-state errors for step-function inputs. Unlike PD controllers, which require time-varying errors to function optimally, PI controllers leverage their integral component to address residual...
470
01:17Ampere-Maxwell's Law: Problem-Solving
744
A parallel-plate capacitor with capacitance C, whose plates have area A and separation distance d, is connected to a resistor R and a battery of voltage V. The current starts to flow at t = 0. What is the displacement current between the capacitor plates at time t? From the properties of the capacitor, what is the corresponding real current?
To solve the problem, we can use the equations from the analysis of an RC circuit and Maxwell's version of Ampère's law.
For the first part of...
To solve the problem, we can use the equations from the analysis of an RC circuit and Maxwell's version of Ampère's law.
For the first part of...
744
01:26The Power Flow Problem and Solution
332
Power flow problem analysis is fundamental for determining real and reactive power flows in network components, such as transmission lines, transformers, and loads. The power system's single-line diagram provides data on the bus, transmission line, and transformer. Each bus k in the system is characterized by four key variables: voltage magnitude Vk, phase angle δk, real power Pk, and reactive power Qk. Two of these four variables are inputs, while the...
332