Photovoltaic Generation System Research Articles

Analysis of the Hybridization of PV Plants with a BESS for Annual Constant Power Operation

The electrical generation of photovoltaic systems is variable and non-dispatchable. Energy storage systems can provide the system with energy management capabilities. In particular, with a hybrid system that combines a photovoltaic system and an energy storage system, it is possible to deliver firm power to the grid, if it is correctly dimensioned and operated. The objective of this work is to study the most appropriate relationship between the capacity of the battery energy storage system (BESS) and the peak power of the photovoltaic generator that enables the delivery of constant power throughout the year. Analysis parameters are presented that help to decide the most convenient energy injection constant value (PV-CPG set point) and the size of the storage system. As a case study, the most suitable battery capacity for a 1 MWp photovoltaic system with a battery located in Zaragoza (Spain), and the most convenient annual setpoint values for its operation are analyzed.

An evaluation of battery energy efficiency with multi-step sampling rate recording for DC data loggers

DC data loggers are widely employed in the battery testing system or PV generation system for collecting the data to evaluate the performance of the operating system or the battery performance. Without any assistance from the monitoring section, the system requires enormous data storage size, and it is difficult to process all information in short time. This paper proposes the method of multi-step sampling rate recording algorithm that can be used for dc data loggers by varying the sampling rate depending on the conditions of input parameters. It can detect the rate of change during the charging or discharging of the battery testing with simultaneously evaluated the battery condition from energy efficiency results. The hardware implementation by applying the proposed method with the lead–acid battery testing is performed to verify the effectiveness of the proposed method. All collecting data can be displayed by using LabVIEW in the monitoring section to see the actual performance of the testing battery.

Optimal Sizing of a Centralized Hybrid Photovoltaic System for Efficient Operation of Street Lights

The photovoltaic energy generation system is one of the most promising technology to meet our future electricity demand as well as mitigate climate change. This study aims to design, simulate and evaluate the performance of hybrid photovoltaic (PV) system using PVsyst software to supply electricity for energy efficient streetlights in educational institute. Meteonorm database of daily and monthly irradiation, temperatures, precipitation and sunlight hours are utilized while performing the analysis. The photovoltaic system consists of 56 bifacial-polycrystalline 360-watt PV modules having 17.9% efficiency. The photovoltaic modules were installed at 0° azimuth angle and 15° tilt angle. Two hybrid inverters with rated capacity of 10 kW are used. The energy storage system consists of 16 batteries (2 in series x 8 in parallel) with a nominal capacity of 1600 ampere-hours and discharging minimum SOC is 20 %. A total of 100 streetlight poles with 8 working-hours/day are installed to cover both sides of the road, with monthly energy consumption of 672 kilowatt-hours. The average annual ambient temperature is 23.66℃, and the annual GH irradiation is 1693 kilowatt-hour/m2. The annual production of the hybrid PV system is 25.96 MWh/year, the specific energy production of the system is 1288 kWh/kWp/year with 70.38% performance ratio. By means of proposed photovoltaic system for energy efficient street lightning structure, 157.9t CO2 is reduced. The project can save 0.004737 million tonnes of CO2 emissions over its lifetime of 30 years. The proposed system is a viable solution for public lighting with the right selection of system components.

A control design for a photovoltaic transformerless HB-NPC inverter with leakage-ground current reduction

A control design for an HB-NPC transformerless inverter is presented in this paper, the proposal includes a modified LCL passive output filter which is aimed to attenuate leakage-ground currents in a transformerless photovoltaic generation system. This modification consists of a simple connection of the filter capacitors to the positive and negative nodes of the DC-link. A theoretical analysis of the differential-mode and common-mode models is performed. Thus, the proposed control law is designed in these new variables of the system. Therefore, the proposed control law consists of two main loops, an inner control loop which is based on the differential-mode model, and a DC-link voltage balance control loop based on the common-mode model. The current tracking loop features a proportional gain plus a bank of resonant filters to enhance the tracking on the differential-mode current reference. The common-mode voltage loop features a PI controller aimed to guarantee the DC-link common-mode voltage regulation objective. To assess the performance of the proposed solution a 1 kW experimental setup of the H-bridge neutral-point clamped transformerless inverter is used with the proposed LCL filter and controller.

An Enhanced P&O MPPT Algorithm for PV Systems with Fast Dynamic and Steady-State Response under Real Irradiance and Temperature Conditions

This paper presents an enhanced perturb and observe (P&O) method for reconciling the trade-off problem between the dynamic response and steady-state oscillations in maximum power point tracking (MPPT). The constraint of having to sacrifice either the dynamic response or the steady-state oscillations has been solved. The method uses the relationship between the open-circuit voltage and maximum power voltage from the fractional open-circuit voltage (FOCV) MPPT method to establish a valid, reduced, and confined search space within which an enhanced P&O via dynamic adaptive step size terminates the search for the maximum power point. The feasibility of the proposed method has been validated by comparing its performance with the conventional P&O algorithm. It was noted that the proposed method increased the operational efficiency of the PV module to 99.89%, reduced the tracking time to 1.8 ms, and preserved the good steady-state response with a power attenuation of less than 0.10 W or relative 0.16% under MATLAB environment. An experimental setup was used to collect real irradiance and temperature data which was used in real-time simulations. The enhanced P&O method was able to resist abrupt changes in irradiance and temperature as it effectively and efficiently followed the maximum power point (MPP). Finally, to appreciate the supremacy of the proposed method, it was compared to nineteen different MPPT methods from literature. The comparison showed that the enhanced P&O MPPT method is highly efficient and effective for MPPT in photovoltaic (PV) generation systems.

In-Depth Design and Multiobjective Optimization of an Integrated Transformer for Five-Phase LLC Resonant Converters

High-power isolated dc–dc converters are preferred in the medium-voltage cascaded H-bridge (CHB) photovoltaic (PV) generation systems due to high power density and galvanic isolation. However, high-power transformers in dc–dc converters can result in high power losses and poor heat dissipation due to thick isolation materials. The three-phase LLC (3P-LLC) converter has been reported suitable for high power applications. Comparing to the single-phase counterpart, the 3P-LLC converter employs three discrete transformers, leading to a larger core area for better heat dissipation. To further increase the power density and the heat dissipation capability of resonant converters, increasing the phase number and integrating magnetic components are considered. This work proposes a five-phase LLC (5P-LLC) resonant converter for the CHB PV application. To increase the power density, a five-phase magnetic integrated transformer (5P-MIT) is proposed and designed with an optimal limb structure to avoid local flux saturation. To further increase the power density, reduce the transformer losses, and enhance the heat dissipation capability, multiobjective optimization is developed to meet multiple design requirements simultaneously. A design case is studied to show the advances of the proposed 5P-MIT. To further investigate the proposed 5P-LLC, a down-scaled prototype is developed with a 5P-MIT. Experiments are conducted to verify the analyses and the functionality.

Application of Artificial Intelligence in PV Fault Detection

The rapid revolution in the solar industry over the last several years has increased the significance of photovoltaic (PV) systems. Power photovoltaic generation systems work in various outdoor climate conditions; therefore, faults may occur within the PV arrays in the power system. Fault detection is a fundamental task needed to improve the reliability, efficiency, and safety of PV systems, and, if not detected, the cost associated with the loss of power generated from PV modules will be quite high. Moreover, maintenance staff will take more time and effort to fix undetermined faults. Due to the current-limiting nature and nonlinear output characteristics of PV arrays, fault detection is not that easy and the application of artificial intelligence is proposed for the sake of fault detection in PV systems. The idea behind this approach is to compare the faulty PV module with its accurate model (factory fingerprint) by checking every PV array’s I–V and P–V curves using the Artificial Neural Network (ANN) logarithm as a subsection of the Artificial Intelligence’s (AI) techniques. This proposed approach achieves a high performance of fault detection and gives the advantage of determining what type of fault has occurred. The results confirm that the proposed logarithm performance becomes better as the number of distinguishing points extend, providing great value to the Solar PV industry.

MPC‐based DC microgrid integrated series active power filter for voltage quality improvement in distribution system

SummaryThis paper presents a DC microgrid integrated series active power filter (Se‐APF) to improve the voltage profile of the utility distribution system under sag, swell, and harmonics scenario. The DC microgrid encompasses a solar photovoltaic generation unit and a composite energy storage unit (CESU). A lithium‐ion battery and supercapacitor as a CESU are envisioned in this work. Compared to conventional Se‐APF supported by the capacitor/battery storage, the integrated DC microgrid prolonged the operational features of the Se‐APF for voltage quality improvement and feeding the localized dc loads or charging the CESU occasionally from the PV generation system. Further, a power management algorithm is implemented to coordinate the operations of the sources in the DC microgrid to accomplish the above‐mentioned features. The Se‐APF and associated power converters in the DC microgrid are regulated by a nonlinear controller based on optimal switching vector‐model predictive control algorithm. The proposed control method can be used to help distribution networks with voltage fluctuations by offering much faster and more precise voltage regulation. The feasibility and effectiveness of the proposed control strategy are verified in MATLAB/Simulink platform and then validated in a real‐time simulation platform using Opal‐RT Lab real‐time simulator OP4510.

Mathematical Modelling and Simulation of Second Life Battery Pack with Heterogeneous State of Health

The service life of Lithium-ion batteries disposed from electric vehicles, with an approximate remaining capacity of 75–80%, can be prolonged with their adoption in less demanding second life applications such as buildings. A photovoltaic energy generation system integrated with a second life battery energy storage device is modelled mathematically to assess the design’s technical characteristics. The reviewed studies in the literature assume, during the modelling process, that the second life battery packs are homogeneous in terms of their initial state of health and do not consider the module-to-module variations associated with the state of health differences. This study, therefore, conducts mathematical modelling of second life battery packs with homogenous and heterogeneous state of health in module level using second-order equivalent circuit model (ECM). The developed second-order ECM is validated against experimental data performed in the lab on 3Ah NCM batteries. The degradation parameters are also investigated using the battery cell’s first life degradation data and exponential triple smoothing (ETS) algorithm. The second-order ECM is integrated with the energy generation system to evaluate and compare the performance of the homogenous and heterogeneous battery packs during the year. Results of this study revealed that in heterogeneous packs, a lower electrical current and higher SOC is observed in modules with lower state of health due to their higher ohmic resistance and lower capacity, compared to the other modules for the specific battery pack configuration used in this study. The methodology presented in this study can be used for mathematical modelling of second life battery packs with heterogenous state of health of cells and modules, the simulation results of which can be employed for obtaining the optimum energy management strategy in battery management systems.

Cooperative voltage management by demand resources and fair payoff allocation for distribution systems

This paper proposes a socially acceptable framework for the realization of efficient voltage management by cooperation among consumers in electric distribution systems where the frequent voltage variation problem is caused by large amounts of photovoltaic (PV) generation systems. In the proposed framework, the profit maximization problem of the coalition under the constraints to suppress the voltage variations caused by PVs is formulated as a linear programming problem, and the payoff allocation among consumers is provided using a solution concept from cooperative game theory called the core. The proposed method efficiently computes the payoff allocation in the nonempty core to accomplish the cooperative voltage management system. Unlike most related works, this paper employs cooperative game theory to explicitly address incentives for cooperation with the consumers. Although the computation for finding an allocation in the core generally requires a significant amount of time, this paper demonstrates that the allocation can be efficiently calculated by using the dual optimal solution of a formulated linear programming problem. The proposed method is validated by computational experiments on a large-scale distribution system model in which consumers with demand resources (including PVs and controllable loads) are connected.

Influence of an Anti-Reflective Coating (ARC) with a pyramidal texture on a Building Integrated low-Concentration Photovoltaic (BICPV) system

Photovoltaic solar energy brings a new opportunity to reduce electricity generation costs and the emission of greenhouse gases. This generation has positioned itself as the most important for renewable energies, mainly because of its impact on generation at an industrial scale. However, in the residential sector, different strategies are proposed within the framework of the best use of the available area to reduce costs, as is the case of low-concentration photovoltaic systems. This document presents an Anti-Reflective Coating (ARC) with a pyramidal texture in two dimensions, for a V-Trough type photovoltaic concentrator, specifically for a Building Integrated low-Concentration Photovoltaic (BICPV) system to increase the light capture avoiding the energy loss caused by the rays coming from incidence angles different from the normal surface. For this, the authors propose a design methodology for the concentrator, determining the material and the geometry of the texture for the ARC and ray tracing simulations and experimentation validate the whole assembly. Finally, electrical generation data is taken in real-time, and it is observed how this texture's application positively affects the photovoltaic system's generation, increasing the normalized efficiency by more than 3 %.

Maximum power point tracking using decision-tree machine-learning algorithm for photovoltaic systems

Abstract This work presents a machine-learning (ML) algorithm for maximum power point tracking (MPPT) of an isolated photovoltaic (PV) system. Due to the dynamic nature of weather conditions, the energy generation of PV systems is non-linear. Since there is no specific method for effectively dealing with the non-linear data, the use of ML methods to operate the PV system at its maximum power point (MPP) is desirable. A strategy based on the decision-tree (DT) regression ML algorithm is proposed in this work to determine the MPP of a PV system. The data were gleaned from the technical specifications of the PV module and were used to train and test the DT. These algorithms predict the maximum power available and the associated voltage of the module for a defined amount of irradiance and temperature. The boost converter duty cycle was determined using predicted values. The simulation was carried out for a 10-W solar panel with a short-circuit current of 0.62 A and an open-circuit voltage of 21.50 V at 1000 W/m2 irradiance and a temperature of 25°C. The simulation findings demonstrate that the proposed method compelled the PV panel to work at the MPP predicted by DTs compared to the existing topologies such as β-MPPT, cuckoo search and artificial neural network results. From the proposed algorithm, efficiency has been improved by >93.93% in the steady state despite erratic irradiance and temperatures.

태양광 발전효율 증대를 위한 최대전력추종 시스템에서 Anti-windup 적용의 효과 분석

In this paper, application and comparative analysis of anti-windup method for improving the response of voltage control of MPPT method in photovoltaic generation system is proposed. In the case of MPPT, PI control can be mainly used to control a target voltage from a reference voltage that continuously changes according to changes in the surrounding environment for optimal control of PV power production. However, its PI controller has accumulated saturation of errors in the process of integrating the errors, so it is necessary to consider the integrator windup. This problem could affect the power production efficiency when performing MPPT control, so this paper sought to verify its effect by applying the follow-up anti-windup technique to MPPT control to improve the integral windup phenomenon. It could be confirmed from the results of the presented simulation that the application of the proposed algorithm mixed is more effective to improve the control performance of the photovoltaic system.

Maximum Power Point Tracking Algorithm for Advanced Photovoltaic Systems

Photovoltaic (PV) systems are the major nonconventional sources for power generation for present power strategy. The power of PV system has rapid increase because of its unpolluted, less noise and limited maintenance. But whole PV system has two main disadvantages drawbacks, that is, the power generation of it is quite low and the output power is nonlinear, which is influenced by climatic conditions, namely environmental temperature and the solar irradiation. The natural limiting factor is that PV potential in respect of temperature and irradiation has nonlinear output behavior. An automated power tracking method, for example, maximum power point tracking (MPPT), is necessarily applied to improve the power generation of PV systems. The MPPT methods undergo serious challenges when the PV system is under partial shade condition because PV shows several peaks in power. Hence, the exploration method might easily be misguided and might trapped to the local maxima. Therefore, a reasonable exploratory method must be constructed, which has to determine the global maxima for PV of shaded partially. The traditional approaches namely constant voltage tracking (CVT), perturb and observe (P&O), hill climbing (HC), Incremental Conductance (INC), and fractional open circuit voltage (FOCV) methods, indeed some of their improved types, are quite incompetent in tracking the global MPP (GMPP). Traditional techniques and soft computing-based bio-inspired and nature-inspired algorithms applied to MPPT were reviewed to explore the possibility for research while optimizing the PV system with global maximum output power under partially shading conditions. This paper is aimed to review, compare, and analyze almost all the techniques that implemented so far. Further this paper provides adequate details about algorithms that focuses to derive improved MPPT under non-uniform irradiation. Each algorithm got merits and demerits of its own with respect to the converging speed, computing time, complexity of coding, hardware suitability, stability and so on.

Power Management and Power Quality System Applied in a Single-Phase Nanogrid

This work aims to present an electrical power management system, between a photovoltaic generation system and a battery energy storage system, by using a low-power dual-stage microinverter connected to the electrical distribution network, configuring a nanogrid. The presented system is capable of performing the active power injection of the photovoltaic arrangement, increasing the availability of electrical energy through a maximum power point tracking algorithm. The system is also able to manage the processes of the charge and discharge of the battery system, where the energy storage system will serve as grid support when renewable power is not available. Furthermore, to ensure the quality of electric energy the proposed microinverter also has the characteristic of parallel active filter for suppression of harmonic currents and reactive compensation of local load current, ensuring the quality of electric energy. As a result, this work presents the system topology, modeling and control of electronic converters, the management strategy with its modes of operation and the results of numerical validation of the proposed system.

Study on Integration of Retired Lithium-Ion Battery With Photovoltaic for Net-Zero Electricity Residential Homes

Abstract The behavior of a retired lithium-ion battery (LIB) from its first-life in an electric aircraft (EA) to its second-life in a solar photovoltaic (PV) system for a net-zero electricity residential home is studied. The first part of this study presents the design and sizing of a battery energy storage system (BESS), made from retired LIBs, to store a portion of the PV generation for a typical home in Ohio. The home is connected to the grid, but the net electricity usage from the grid in one year is zero. The purpose of the BESS is to peak shaving, power arbitrage, reduce the home dependency on the grid, and increase the economic benefits. The sizing is determined based on the hourly data of the PV system generation, ambient temperature, irradiation, and home demand electricity. In the second part of this study, the retired LIB degradation rate and its remaining useful life in the BESS are estimated using an adopted empirical LIB model. The model includes the capacity-fade for both first-life and second-life of the LIB under various duty cycles. It is shown that the retired LIB from its first-life is still suitable to be used in the PV grid-tied battery (PVGB) system for another 10 years. The results of this study can potentially reduce the LIB cost for electric vehicles (EVs) and EAs because the retired LIBs from these applications still have value to serve for other applications such as PVGB systems for residential homes.

Optimal Sizing and Location of Photovoltaic Generation and Energy Storage Systems in an Unbalanced Distribution System

There has been an increasing number of renewable energy sources introduced into the distribution system to decrease the dependence on single power sources and relieve their effects related to global warming caused by power consumption. When greatly increasing renewable energy in the power system, the renewable energy connected to the power grid must be coupled with corresponding energy-storage technologies. This mechanism not only effectively improves the power floating problem but also more efficiently re-dispatches the power output. The purpose of this paper is to deal with the optimal sizing and location issue of the photovoltaic generation system and the battery energy storage system, which are proposed in order to improve the power loss, bus voltage profile, and voltage unbalance for the actual unbalanced loading distribution system of a large-scale chemical factory. The power loss, construction cost of the solar power and the energy storage systems, voltage variation ratio and voltage unbalance ratio will be treated as part of the objective function of the optimal problem. These variables are subject to various operating constraints and the voltage variation limit of the system when the photovoltaic generation and battery energy storage systems are operated. Furthermore, a refined genetic algorithm, which possesses an auto-selective crossover and mutation scheme, is proposed and applied in this paper in order to solve the optimization problem. Moreover, the simulation results are expected to demonstrate the superiority of the proposed algorithm.

Comparative study of modern heuristic algorithms for global maximum power point tracking in photovoltaic systems under partial shading conditions

Under partial shading conditions (PSCs), photovoltaic (PV) generation systems exhibit multiple local and a single global maximum power point. Consequently, global maximum power point tracking (GMPPT) is required to improve the performance of PV systems in such scenarios. This paper comparatively studies and evaluates the tracking performance of modern heuristic-optimization-based GMPPT techniques. Monte Carlo method is used to statistically analyze different methods. Simulation and experimental results indicate that many of the algorithms have difficulties in balancing the explorative and exploitative searching behaviors. Therefore, we propose a variable vortex search (VVS), which is capable of improving the performance of GMPPT by using a variable step size and deterministic starting points. This paper will aid researchers and practical engineers to gain a thorough understanding on how to use modern heuristic algorithms for maximum power out of PV systems. Furthermore, it offers a comprehensive guidance on how to perform efficiently GMPPT in the PV systems under PSCs.

Evaluation of energy extraction of PV systems affected by environmental factors under real outdoor conditions

The global agenda to increase the renewable energy share has driven many countries and entities to harness solar energy from solar photovoltaic (PV) systems. However, the power generation of PV systems is strongly affected by climate conditions. Therefore, the main objective of this study is to analyze and predict the power generation of different PV technologies under arid desert climate conditions on an hourly basis. Two areas have been considered as case studies: Adrar in Algeria and Alice Springs in Australia. A total of nine physical models and input parameter combinations from six different power plants have been used and tested for the suitability of the proposed models for predicting the power yield of PV power plants depending on solar irradiance and other meteorological variables. Then, an ensemble learning technique is applied to improve the performance capabilities of the best-fit input combinations. The results reveal that the global irradiance, ambient air temperature, and relative humidity combination are the most related to the PV power output of all technologies under all-sky conditions and provide effective and efficient performance with the proposed ensemble learning, with an estimated accuracy of over 99%.

A low voltage ride-through strategy for grid-connected PV converters based on variable power point tracking method

A novel low voltage ride through control strategy with variable power tracking trajectory is proposed. The voltage fall amplitude is controlled by feedforward, and the tracking trajectory of power point is adjusted to realize the real-time change of the photoelectric cell voltage. On this basis, the output power of the photovoltaic generation system is controlled quickly and efficiently, and the purpose of power balance in the PV inverter is achieved. Through collaborative control of the grid-tied inverters, the output current of grid-tied inverter can meet the active and reactive power requirements of power grid as much as possible without overing the limit. In this way, the maximized support for the voltage recovery of power grid which contains zero voltage ride through is realized. In the non-standard environment, the proposed control strategy is proven to be effective by the simulation results. Compared with traditional LVRT strategy, the proposed strategy in this paper not only realizes the safe and reliable operation, but also improves the economy of photovoltaic power generation system, without any add additional equipment.