R. M. Brisilla

Bio: R. M. Brisilla is an academic researcher from VIT University. The author has contributed to research in topics: Photovoltaic system & Maximum power point tracking. The author has an hindex of 2, co-authored 4 publications receiving 17 citations.

Development of Cuckoo Search MPPT Algorithm for Partially Shaded Solar PV SEPIC Converter

Abstract: Photovoltaic (PV) power generation is playing a prominent role in rural power generation systems due to its low operating and maintenance cost. The output properties of solar PV mainly depend on solar irradiation, temperature, and load impedance. Hence, the operating point of solar PV oscillates. Due to the oscillatory behavior of operating point, it is difficult to transform maximum power from the source to load. To maintain the operating point constant at the maximum power point (MPP) without oscillations, a maximum power point tracking (MPPT) technique is used. Under partial shading condition, the nonlinear characteristics of PV comprise of multiple maximum power points (MPPs). As a result, discovering true MPP is difficult. The traditional and neural network MPPT methods are not suitable to track the MPP because of oscillations around MPP and impreciseness in tracking under partial shading (PS) condition. Therefore, in this article, a biological intelligence cuckoo search optimization (CSO) technique is utilized to track and extract the maximum power of the solar PV at two PS patterns. MATLAB/Simulink is used to demonstrate the CSO MPPT operation on SEPIC converter.

Mathematical Design and Analysis of Photovoltaic Cell Using MATLAB/Simulink.

Abstract: This study explored different models of PV cell, namely, single diode model and double diode models using MATLAB/Simulink Environment. The output power and current characteristics are analyzed for different solar intensity radiations and temperature variations of PV cell. Simulation results are obtained for different atmospheric and temperature conditions. The simulation results reveal that the double diode model generates maximum power and has a higher efficiency compared to single diode model.

Simulation of Metaheuristic Intelligence MPPT Techniques for Solar PV Under Partial Shading Condition

Abstract: The nonlinear characteristics of solar PV consist of different MPPs under the partial shading condition. Hence, it is difficult to find out true MPP. The conventional MPPT methods are not giving an accurate position of MPP. In this work, two global metaheuristic optimization techniques are simulated and the comparative analysis is carried out in terms of tracking speed, steady-state oscillations, algorithm complexity, periodic tuning, and dynamic response. Those are the Cuckoo Search Optimization (CSO) and Particle Swarm Optimization (PSO) MPPT methods used to extract the maximum power of solar PV under partial shading condition. The Matlab/Simulink is used to evaluate performance results of CSA and PSO MPPT techniques.

Design of SVPWM-Based Two-Leg VSI for Solar PV Grid-Connected Systems

Abstract: In this work, a four-switch Voltage Source Inverter (VSI) is considered for highly efficient and low power solar PV grid-connected applications to optimize the cost and size of the PV system. The Perturb and Observe (P&O) Maximum Power Point Tracking (MPPT) technique is used to track Maximum Power Point (MPP) of solar PV. This technique is simple, easy to design, and less complexity. By using two-leg four-switch inverter (B-4 inverter) the cost of the PV system can be reduced compared to six switch inverters, as the cost of inverter mainly depends on the cost of semiconductor switches. The boost converter is utilized to step-up the PV voltage. This work is to analyze the Space Vector Pulse Width Modulation Technique (SVPWM) in two-leg B-4 inverter topology to reduce the ripples at time of switching thereby reducing the Total Harmonic Distortion (THD) and reducing the inverter switching and conducting losses at high pulse width modulation frequency. Moreover, SVPWM technique improves the utilization factor of B-4 inverter. The results are analyzed by using MATLAB Simulink window.

Different Conventional and Soft Computing MPPT Techniques for Solar PV Systems with High Step-Up Boost Converters: A Comprehensive Analysis

Abstract: Solar photovoltaic (PV) systems are attracting a huge focus in the current energy scenario. Various maximum power point tracking (MPPT) methods are used in solar PV systems in order to achieve maximum power. In this article, a clear analysis of conventional MPPT techniques such as variable step size perturb and observe (VSS-P&O), modified incremental conductance (MIC), fractional open circuit voltage (FOCV) has been carried out. In addition, the soft computing MPPT techniques such as fixed step size radial basis functional algorithm (FSS-RBFA), variable step size radial basis functional algorithm (VSS-RBFA), adaptive fuzzy logic controller (AFLC), particle swarm optimization (PSO), and cuckoo search (CS) MPPT techniques are presented along with their comparative analysis. The comparative analysis is done under static and dynamic irradiation conditions by considering algorithm complexity, tracking speed, oscillations at MPP, and sensing parameters. The single-diode model PV panel and double-diode model PV panel are also compared in terms of fill factor (FF) and maximum power extraction. Clear insight is presented supporting the suitability of MPPT techniques for different types of converter configurations.

Performance Analysis of MPPT Techniques for Dynamic Irradiation Condition of Solar PV

Abstract: Solar Photovoltaic (PV) systems are playing a major role in the present electrical energy systems. The solar PV gives nonlinear I–V and P–V characteristics. As a result, it is difficult to extract the maximum power of the solar PV. Under Partial Shading Conditions (PSCs), the solar PV characteristics consist of multiple local Maximum Power Points (MPPs) and one global MPP. The classical Maximum Power Point Tracking (MPPT) techniques cannot track the global MPP under PSCs. Accordingly, this work aims to study the performance of five soft computing MPPT techniques. The studied five soft computing MPPT techniques are Modified Variable Step Size-Radial Basis Functional Network (MVSS-RBFN), Modified Hill-Climb with Fuzzy Logic Controller (MHC-FLC), Artificial Neuro-Fuzzy Inference System (ANFIS), Perturb and Observe with Practical Swarm Optimization (P&O-PSO), and Adaptive Cuckoo Search (ACS). The comparative performance analysis of five soft computing techniques has been carried out against the Variable Step Size-Incremental Resistance (VSS-INR), and Variable Step Size-Feedback Controller (VSS-FC)-based MPPT techniques. The performance analysis of seven MPPT techniques has been done by considering the parameters are steady-state settling time, MPP tracking speed, algorithm complexity, PV array dependency, handling of partial shading, and efficiency.

A New Robust Energy Management and Control Strategy for a Hybrid Microgrid System Based on Green Energy

Abstract: The recent few years have seen renewable energy becoming immensely popular. Renewable energy generation capacity has risen in both standalone and grid-connected systems. The chief reason is the ability to produce clean energy, which is both environmentally friendly and cost effective. This paper presents a new control algorithm along with a flexible energy management system to minimize the cost of operating a hybrid microgrid. The microgrid comprises fuel cells, photovoltaic cells, super capacitors, and other energy storage systems. There are three stages in the control system: an energy management system, supervisory control, and local control. The energy management system allows the control system to create an optimal day-ahead power flow schedule between the hybrid microgrid components, loads, batteries, and the electrical grid by using inputs from economic analysis. The discrepancy between the scheduled power and the real power delivered by the hybrid microgrid is adjusted for by the supervisory control stage. Additionally, this paper provides a design for the local control system to manage local power, DC voltage, and current in the hybrid microgrid. The operation strategy of energy storage systems is proposed to solve the power changes from photovoltaics and houses load fluctuations locally, instead of reflecting those disturbances to the utility grid. Furthermore, the energy storage systems energy management scheme will help to achieve the peak reduction of the houses’ daily electrical load demand. Also, the control of the studied hybrid microgrid is designed as a method to improve hybrid microgrid resilience and incorporate renewable power generation and storage into the grid. The simulation results verified the effectiveness and feasibility of the introduced strategy and the capability of proposed controller for a hybrid microgrid operating in different modes. The results showed that (1) energy management and energy interchange were effective and contributed to cost reductions, CO2 mitigation, and reduction of primary energy consumption, and (2) the newly developed energy management system proved to provide more robust and high performance control than conventional energy management systems. Also, the results demonstrate the effectiveness of the proposed robust model for microgrid energy management.

A New Robust Control Strategy for Parallel Operated Inverters in Green Energy Applications

Abstract: This research work puts forward a hybrid AC/DC microgrid with renewable energy sources pertaining to consumer’s residential area for meeting the demand. Currently, the power generation and consumption have experienced key transformations. One such tendency would be integration of microgrids into the distribution network that is characterized by high penetration of renewable energy resources as well as operations in parallel. Traditional droop control can be employed in order to get an accurate steady state averaged active power sharing amongst parallel inverters pertaining to hybrid AC/DC microgrid. It is presumed that there would be similar transient average power responses, and there would be no circulating current flowing between the units for identical inverters possessing the same droop gain. However, the instantaneous power could be affected by different line impedances considerably and thus resulting in variation in circulating power that flows amongst inverters, especially during unexpected disturbances like load changes. This power, if absorbed by the inverter, could result in sudden DC-link voltage rise and trip the inverter, which in turn causes performance degradation of the entire hybrid microgrid. When the hybrid generators act as unidirectional power source, the issue worsens further. In this research work, we have put forward a new distributed coordinated control pertaining to hybrid microgrid, which can be applied for both grid connected and islanded modes that include variable loads and hybrid energy resources. Also, in order to choose the most effective controller scheme, a participation factor analysis has been designed for binding the DC-link voltage as well as reducing the circulating power. Moreover, to both photovoltaic stations and wind turbines, maximum power point tracking (MPPT) techniques have been used in order to extract the maximum power from hybrid power system when there is discrepancy in environmental circumstances. Lastly, the feasibility and effectiveness pertaining to the introduced strategy for hybrid microgrid in various modes are confirmed via simulation results.