Photovoltaic Generation System Research Articles

Optimization and comparative analysis for a stand-alone hybrid model of PV, wind turbine, and natural gas generator system in remote area – A case study in Belu

This paper proposes a hybrid model of photovoltaic (PV) and wind power generation based on the off-grid system for the rural area. The off-grid system is considered more suitable to be applied in the remote area since it has a lack of access to the closest grid network. Belu (9°10.5‘N and 124°59.4'E), Indonesia, is chosen particularly as the model due to its high potential resources of renewable energy. The data on wind and solar resources are obtained from Meteonorm. The system schematic consists of the wind turbine, photovoltaic (PV), battery, converter and electrical load. A small-size natural gas generator is used as the back-up. The data is processed by using HOMER Optimizer based on the derivative-free algorithm. The total Net Present Cost (NPC) and the Levelized Cost of Energy (LCOE) for the optimized system configuration are $95,828 and $0.106, respectively. The performance of the system is represented by the percentage value of the excess electricity and unmet electric load which are 13% and 0.39%, respectively. The carbon dioxide produced is only 10,070 kg/year. In general, the optimized system is much better compared to the generator-only system based on the economical, electrical, and environmental aspects.

Fault diagnosis of photovoltaic array based on SE-ResNet

In recent decades, fault diagnosis of photovoltaic (PV) arrays has become more and more important for the power generation of PV systems. Many traditional artificial intelligence methods have been successfully applied to use fault data samples to build fault diagnosis models, but most rely on manual feature extraction or expert knowledge to build diagnosis models, which is inefficient and may ignore some potentially useful features. Therefore, this paper proposes an SE-ResNet PV array fault diagnosis algorithm based on Residual Network (ResNet) and Squeeze-and-Excitation Network (SENet), and uses Bayesian Optimization (BO) optimize the parameters. In order to verify the effectiveness of the proposed fault diagnosis algorithm, a comprehensive fault experiment was carried out on the PV platform. Experimental results show that the model has achieved high overall performance in terms of accuracy, generalization performance, reliability and training efficiency, and has high practicability.

Countrywide PV hosting capacity and energy storage requirements for distribution networks: The case of Switzerland

Distributed photovoltaic (PV) generation is typically connected to power distribution grids, which are not designed to host a large amount of production if it is significantly larger than their nominal electricity demand. Given the prominent role of PV in energy transition pathways, modeling the existing power distribution infrastructure’s constraints and limitations is key for its reliable techno-economical analysis and expansion.As countrywide models of the distribution grids are, in general, not available, this paper first tackles the problem of estimating medium voltage (MV) distribution grids starting from publicly available datasets. It then proposes a method to estimate the PV generation hosting capacity of such grids and extend it through energy storage systems.As a final contribution and ultimate objective, this paper proposes a method to derive cost-optimal plans for countrywide deployment of PV generation and energy storage systems considering the MV power distribution infrastructure’s technical limitations. The distributed PV generation potential is modeled with high-spatially resolved capacity factors. Results are discussed using Switzerland as a case study.

Impact of optimal integration of renewable energy sources and electric vehicles in practical distribution feeder with uncertain load demand

Distributed energy resources (DERs) are a better option for fulfillment of load demand near the load centers. Optimal location and rating of DERs plays a vital role in the enhancement of distribution system performance in terms of power loss reduction, voltage profile enhancement, environmental friendliness, increasing reliability, and postponement of system upgrading. This paper addresses the Gbest-guided artificial bee colony (GABC) optimization technique for the optimal integration of renewable energy sources (RESs) and electric vehicles (EVs) in distribution feeder to improve the power loss reduction, voltage level, cost reduction, and emissions reduction under load demand uncertainty. In this work, mathematical models of RESs, that is, wind turbine generation system (WTGS) and photovoltaic generation system (PVGS), are employed to determine the generated output power. The foremost aim of this research work is simultaneous abatement of total active power loss, entire cost, and emissions generation; therefore a multiobjective-based fitness function is formed. Moreover, the impact of charging/discharging behavior of EVs on the distribution grid has also been considered in this study. The proposed methodology is applied on two test systems: (a) 28-bus practical rural distribution network located at Kakdwip zone in the province of West Bengal, India, and (b) standard 69-bus distribution feeders. Finally, from the achieved numerical outcomes, it is analyzed that, GABC algorithm generates better outcomes as compared to other optimization techniques. This indicates the viability and effectiveness of the proposed methodology.

Performance analysis and evaluation of 10 kWp solar photovoltaic array for remote islands of Andaman and Nicobar

The Andaman and Nicobar island, an union territory of India, is a group of islands located in the Indian Ocean where 93.63% of total power is generated by the diesel generators for which solar photovoltaic (PV) generation system is a viable alternative to meet the load demand of the islands. The proposed paper presents the solar PV resource assessment, performance analysis, and evaluation of normalized performance indices obtained from 10 kWp solar PV array considered at the climatic conditions of five islands of Andaman and Nicobar, mainly Smith, Middle Andaman, Baratang, Car Nicobar and Katchal. The yearly mean normalized performance indices like array yield (Yarr), reference yield (Yref), final yield (Yfin), performance ratio (PR), array capture loss (Lcap), system loss (Lsys) and capacity factor (CF) have been evaluated. The variation of ambient temperature (Tamb) and cell temperature (Tcell) have also been presented. The obtained results show yearly mean capacity factor and performance ratio are in the range of (13.73–14.61)% and (64.70–64.93)%, respectively. The yearly mean array yield, reference yield, final yield, array capture loss and system loss are (3.66–3.90) h/d, (5.08–5.43) h/d, (3.30–3.51) h/d, (1.42–1.53) h/d and (0.37–0.39) h/d, respectively.

Study on simulation of wind load characteristics for photovoltaic generation systems

Photovoltaic generation systems can automatically track the angle of sunlight. The system consists of four photovoltaic (PV) panels which can adjust pitch angle and azimuth angle according to the sunlight. The variation of the wind coefficient and wind load characteristics of the PV panels with the pitch angle and azimuth angle is obtained through the wind tunnel simulation based on FLUENT to determine the flow characteristics around the PV panels.

Photovoltaic Generation Integration with Radial Feeders Using GA and GIS

The electric power generated from different electricity sources are not used efficiently by end users in the world. This is due to the loss of power supplied in the case of electricity transmission and distribution to residential, commercial, and industrial loads. Even if the loss of power in the power system cannot be avoided 100%, it should be reduced to the minimum optimal value. The loss of power in the radial feeders can be minimized using an optimally allocated photovoltaic (PV) generation system by considering the information of geography, solar irradiance of the site, and space availability, which should not have shadow from large buildings and trees. The PV generation system eliminates the problem of power demand by enhancing the capacity of the power network as well as by reducing the depletion and consumption of fossil fuel resources. To reduce power loss and improve system loading capacity for demand response, the integration and finding the optimal place of photovoltaic generation take high concern from power system operators and technicians. The optimal allocation of PV has been done using the Genetic Algorithm (GA) for optimization of a multiobjective function with different constraints. The main objective of this paper is to minimize the power loss of the radial distribution networks by maintaining the phase voltage of the load in balance and improving the drop in voltage along the phase. So, GA is used to determine the best location and capacity of PV generation that can reduce the loss of power in the system. The IEEE-33 bus system is used to test the proposed method. Generally, using the GA and GIS methods results in a high accuracy for optimal placement of PV generation in the IEEE-33 bus radial feeder and enables to reduce the loss of power during transmission and distribution by maintaining the power quality for consumers.

Predictive Duty Cycle of Maximum Power Point Tracking Based on Artificial Neural Network and Bootstrap Method for Hybrid Photovoltaic/ Wind Turbine System Considering Limitation Voltage of Grid

In this paper, we propose a new control-based the neural network and bootstrap method to get the predictive duty cycle for the maximum power point of hybrid Photovoltaic (PV) and Wind Turbine generator system (WTG) connected to 380 V grid. The neural network is designed to be controller by learning the data control of multi-input DC/ DC converter. The artificial neural network (ANN) needs many data for training then the ANN can give the predictive duty cycle to multi input DC/ DC converter. To get much data, we can use the bootstrap method to generate data from the real data. From Photovoltaic characteristic, we can get 344 real data after the data are made by bootstrap method we can get 8000 data. The 8000 data of PV can be used for training artificial neural network (ANN) of PV system. From wind turbine characteristic we can get 348 real data after the data are made by bootstrap method we can get 6000 data. The 6000 data of WT can be used for training artificial neural network of WT system. This new control has two responsibilities, are to shift the voltage of PV and WTG to optimum condition and to maintain the stability of grid system. From the simulation results those can be seen that the power of hybrid PV / WTG system using MPPT controller is in maximum power and has constant voltage and constant frequency of grid system.

Design and Installation of 500-kW Floating Photovoltaic Structures Using High-Durability Steel

Countries around the world are expanding their investment in the new and renewable energy industry for strengthening energy security, improving air pollution, responding to climate change, and tackling energy poverty. In Korea, with the nuclear phase-out declaration in 2017, the government has announced a policy to expand the ratio of new and renewable energy from 4.7% to 20% by 2030. This study examines a floating photovoltaic power generation system, which is a new and renewable energy source. A structure composed of high-durability steel with excellent corrosion resistance and durability was designed for constructing and installing a 500-kW-class floating photovoltaic power generation structure. In addition, the safety of the structure was verified through finite element analysis. By reviewing the safety of the structure with respect to the wave height, the behavior of the structure was confirmed through the design wave height formula proposed in the domestic standard. The verification result confirms that the stress is within the allowable design limit. Moreover, the energy production of the floating photovoltaic generation system was measured and compared with that of a terrestrial photovoltaic generation system, and that of the former was shown to be 10% higher than that of the latter.

Neutral-Point Voltage Oscillation Mitigation Scheme for Transformerless Three-Level PV Inverter in LVRT Operation With Selective Space Vector Modulation

In transformerless photovoltaic (PV) generation system, the neutral-point (NP) voltage balancing and the ground current reduction of three-level inverter are carefully regulated using a space vector modulation (SVM) scheme. Nevertheless, in low-voltage ride-through (LVRT) operation, the simultaneous reduction of NP voltage oscillation and common-mode voltage (CMV) has not been researched yet. To overcome these issues, a selective SVM (SSVM) strategy is proposed in this article. First, the NP voltage oscillation of three-level inverter in LVRT operation is analyzed in detail, which reveals that the NP voltage is affected by phase currents and duty cycles. Based on the location of output voltage and the direction of grid currents, the correct small vectors are selected under different power factor angles. Then, the small vector force (SVF) including the grid currents and duty cycle on NP voltage is proposed for the first time. According to the value of SVF, the optimal small vector having the most effective impact on NP voltage among the correct vectors and switching sequence is determined. With the proposed method, the NP voltage oscillation and CMV are reduced simultaneously in LVRT operation. Finally, the effectiveness of the proposed method is verified with experimental results.

A simplified and fast computing photovoltaic model for string simulation under partial shading condition

The photovoltaic (PV) model allows the current–voltage characteristic curves of the PV module to be represented in the simulation, which is important in the development of the PV generation system. Nevertheless, the current single PV model is not able to receive multiple irradiance and temperature input to simulate the partial shading condition. The conventional PV model with the partial shading capability requires several PV models that are connected with a bypass diode in parallel to each PV model. As a result, the computation time becomes high and the adaptability of this model is low since it requires a circuit simulation software. This paper presents an adjuster that allows a standard PV model to have partial shading capability. The proposed PV model is only applicable for the series configuration only. The single diode model with a series resistance is used to design the PV model in MATLAB/Simulink and the results have been compared and analysed with the conventional PV model. From the results, it has shown that the proposed PV model is able to be executed up to 46 times faster in computation time compared to the conventional PV model while maintaining the maximum power point error below 4%.

Assessment of Dynamic Economic and Emission Dispatch Problem using WOA in Networked Grids with Photovoltaic Power Injection

Since decades, the main aim for the researchers is to get reliable and inexpensive electricity out of available resources. Till now, different economic dispatch methods have been developed to meet the challenges of continuous and sustainable electricity production at optimized cost. Due to the increase of public awareness on environmental protection, the utilities have forced to use renewable energy sources to modify the operation strategies to reduce the pollution and atmospheric emissions produced due to power plants. This paper represents the allocation of dynamic economic emission dispatch (DEED) problem involving thermal and photovoltaic (PV) generation system as hybrid dynamic economic emission dispatch (HDEED) to meet the minimization of both the cost of fuel and emission simultaneously. Whale optimization algorithm (WOA) is used to minimize the total cost of operation and emission levels while dispatching power to committed generation units considering all operational constraints. To show the efficiency, the proposed technique is applied to solve the dynamic economic emission dispatch problem on 5- and 10-unit test systems. The technique is also used to solve the HDEED problem on IEEE 30-bus 6-unit and IEEE 57-bus 7-unit test system with and without renewable generation. The results obtained after injection of photovoltaic power into existing power systems show the effectiveness of the proposed techniques to reduce the cost of operation and emission levels.

A Development of an Evaluation Method of the Locational Value of Distributed Batteries as a Voltage Control Device in a Distribution System with Large Penetration of Photovoltaic Generation Systems

A Development of an Evaluation Method of the Locational Value of Distributed Batteries as a Voltage Control Device in a Distribution System with Large Penetration of Photovoltaic Generation Systems

Simulation-Based Coyote Optimization Algorithm to Determine Gains of PI Controller for Enhancing the Performance of Solar PV Water-Pumping System

In this study, a simulation-based coyote optimization algorithm (COA) to identify the gains of PI to ameliorate the water-pumping system performance fed from the photovoltaic system is presented. The aim is to develop a stand-alone water-pumping system powered by solar energy, i.e., without the need of electric power from the utility grid. The voltage of the DC bus was adopted as a good candidate to guarantee the extraction of the maximum power under partial shading conditions. In such a system, two proportional-integral (PI) controllers, at least, are necessary. The adjustment of (Proportional-Integral) controllers are always carried out by classical and tiresome trials and errors techniques which becomes a hard task and time-consuming. In order to overcome this problem, an optimization problem was reformulated and modeled under functional time-domain constraints, aiming at tuning these decision variables. For achieving the desired operational characteristics of the PV water-pumping system for both rotor speed and DC-link voltage, simultaneously, the proposed COA algorithm is adopted. It is carried out through resolving a multiobjective optimization problem employing the weighted-sum technique. Inspired on the Canis latrans species, the COA algorithm is successfully investigated to resolve such a problem by taking into account some constraints in terms of time-domain performance as well as producing the maximum power from the photovoltaic generation system. To assess the efficiency of the suggested COA method, the classical Ziegler–Nichols and trial–error tuning methods for the DC-link voltage and rotor speed dynamics, were compared. The main outcomes ensured the effectiveness and superiority of the COA algorithm. Compared to the other reported techniques, it is superior in terms of convergence rapidity and solution qualities.

Grid-Connected PV Generation System—Components and Challenges: A Review

Renewable energy (RE) has become a focal point of interest as an alternative source of energy to the traditional fossil fuel and other energy sources due to the fact that it is more environmentally friendly, abundant and economically feasible. Many countries aggressively promote feed-in tariff schemes and solar photovoltaic (PV) systems have become one of the fastest growing RE sources that can be integrated into the grid distribution network. This paper reviews the recent development of grid-connected PV (GPV) generation systems comprising of several sub-components such as PV modules, DC-DC converter, maximum power point tracking (MPPT) technique, and an inverter. In addition, various grid synchronization and islanding detection methods are elaborated. The future key challenges to build a smart and efficient GPV generation system were also presented.

An assessment methodology on reliability of Aggregate Battery Energy Storage System considering dynamic operation

Nowadays, distributed generators in Microgrids (MG) are developed to exploit the clean and renewable energy from nature, such as solar irradiation, wind power, tidal wave, etc. Accordingly, an Aggregate Battery Energy Storage System (ABESS) is implemented to achieve the stability and reliability of MG. To be clearly decribed, the ABESS will play a main role as a power controller in supply-demand operation of MG. In order to demonstrate significance and importance of ABESS in the MG, its operation reliability will be introduced in this paper. The authors will use an analytical methodology based on Markov models to assess the operation reliability of the whole ABESS under dynamic operation cases. According to dynamic operation cases of MG with the ABESS and Photovoltaic Generation System (PVS), the failure rate of the ABESS is different. Simulations and test results are presented and discussed to prove that the operation reliability of the ABESS in the MG significantly depends on different dynamic operation along with the voltage dynamic and power loss.

Development of a Predictive Model for a Photovoltaic Module’s Surface Temperature

PV (photovoltaic) systems are receiving the spotlight in Korea due to the Renewable Energy 3020 Implementation Plan (RE3020), which has the goal of reaching 20% for the proportion of renewable energy generation by 2030. Accordingly, the actual performance evaluation of PV systems to achieve the RE3020 has become more important. PV efficiency is mainly determined by various weather conditions (e.g., solar radiation) that affect the power generation of PV systems. However, the efficiency is also affected by changes in module surface temperature. In particular, the efficiency decreases when the module surface temperature rises. That is, the actual PV efficiency falls short of the rated efficiency. The estimation of module surface temperature is critical for evaluating the actual performance of PV systems. Many studies have been conducted to calculate the surface temperature. However, most of the previous studies focused on calculations of current surface temperatures using current environment data, which means that the previous studies have limitations related to timestep. That is, there is a lack of predictive models that calculate the future surface temperatures by using the current measured data. Therefore, this study developed a predictive model using an ANN (artificial neural network) algorithm to determine the surface temperature of PV modules for a future period of time. Then, this study evaluated the actual performance (i.e., power generation) with the predicted surface temperatures.

Design and simulation of a microgrid for TIH campus

<p><span>This paper proposes a methodology for designing and operating a microgrid (MG) for the main campus of the Technical Institution Hawija. In this MG, a battery energy storage system (BESS), photovoltaic (PV) generation system, and controllable loads are included. Due to the high penetration of the PVs, over-voltage issues may occur in this MG. A novel operation strategy is considered by coordinating the BESS, PVs, and loads to prevent power outages and accomplish a secure operation of this MG. In this proposed approach, droop controllers have been implemented to provide the appropriate references for the PVs and BESS to maintain the voltage of the MG within a secure range. The generation of the PVs may be curtailed to guarantee the fidelity of the voltage. The intended simulations will be based on MATLAB/Simulink to show the efficacy of the intended design.</span></p><script type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.0/MathJax.js?config=TeX-AMS-MML_HTMLorMML&delayStartupUntil=configured"></script><script id="texAllTheThingsPageScript" type="text/javascript" src="chrome-extension://cbimabofgmfdkicghcadidpemeenbffn/js/pageScript.js"></script>

저압범위 확대에 따른 태양광발전시스템 직류배선 설계방법

저압범위 확대에 따른 태양광발전시스템 직류배선 설계방법

Common‐ground non‐isolated high‐gain DC/DC converter for low powerdistributed generation photovoltaic systems

A high step-up/high-efficiency converter is one of the essential requirements of a low power grid-connected photovoltaic system that provides the maximum power point tracking ability and injects the low voltage extracted power to AC or DC distribution network. This study presents a common-ground non-isolated high-gain DC/DC converter whit a naturally wide range of soft-switching conditions. The proposed converter has two resonant loops, and a new simple structure consists of an active switch, three diodes, two inductors and two capacitors, work in two useful operation modes. In the optimum operation mode (OOM), the switch turns on/off in zero current switching (ZCS)/zero voltage switching condition, and at the sub-OOM, the switch turns on in ZCS condition and turns off in hard switching condition. The mathematical analysis and MATLAB/SIMULINK simulation results are described in detail. Also, a prototype 100 W converter is built and tested to validate the simulation analysis on a 100 W photovoltaic panel.