Stand-alone Photovoltaic System Research Articles

Design of Type 2 Fuzzy Logic Controller Based Inverter for Isolated PV System

In this article, a Type 2 fuzzy logic controller (T2FLC) is implemented in the PV system to improve the magnitude and frequency as well as the transient time response of the photovoltaic (PV) system. T2FLC is capable to handle more uncertainty because of the PV characteristic variable with atmospheric temperature and irradiation of the sun. Simple and most widely used Perturb & Observation (P& O) based MPPT technique has been implemented to extract maximum power to generate the desired switching pulse for DC-DC converter in the proposed standalone PV system. Deployed T2FLC based inverter in the proposed standalone PV system with different loads can improve the response of the system and reduce the oscillations as well as noise. The performance of the system validates over with proportional-integral (PI) and T1FLC controller. The proposed T2FLC algorithm deployed in a standalone three-phase PV system shows performance better than the other two controllers and simulate in MATLAB/SIMULINK environment.

A novel storage system for cooling stand-alone photovoltaic installations

Stand-alone photovoltaic systems usually use batteries to adjust energy yield to energy demand. An alternative energy storage system for stand-alone photovoltaic installations is proposed for three cooling applications: air conditioning, food preservation and freezing. A thermally insulated storage tank with ammonia in saturated mixture phase is integrated into the vapour-compression cooling cycle. A thermodynamic model and an economic assessment based on typical costs and cost sensitivity are included to assess the proposed system performance in comparison with a conventional stand-alone photovoltaic system with a vapour-compression cycle. Results show that the proposed storage strategy is an affordable option, especially in hot climates and for food preservation and freezing applications.

Optimum Design of a Standalone Solar Photovoltaic System Based on Novel Integration of Iterative-PESA-II and AHP-VIKOR Methods

Solar energy is considered one of the most important renewable energy resources, and can be used to power a stand-alone photovoltaic (SAPV) system for supplying electricity in a remote area. However, inconstancy and unpredictable amounts of solar radiation are considered major obstacles in designing SAPV systems. Therefore, an accurate sizing method is necessary to apply in order to find an optimal configuration and fulfil the required load demand. In this study, a novel hybrid sizing approach was developed on the basis of techno-economic objectives to optimally size the SAPV system. The proposed hybrid method consisted of an intuitive method to estimate initial numbers of PV modules and storage battery, an iterative approach to accurately generate a set of wide ranges of optimal configurations, and a Pareto envelope-based selection algorithm (PESA-II) to reduce large configuration by efficacy obtaining a set of Pareto front (PF) solutions. Subsequently, the optimal configurations were ranked by using an integrated analytic hierarchy process (AHP) and vlsekeriterijumskaoptimizacija i kompromisonoresenje (VIKOR). The techno-economic objectives were loss of load probability, life cycle cost, and levelized cost of energy. The performance analysis results demonstrated that the lead–acid battery was reliable and more cost-effective than the other types of storage battery.

Mapping RO-Water Desalination System Powered by Standalone PV System for the Optimum Pressure and Energy Saving

Brackish water desalination is widely used to supply fresh water; reverse osmosis (RO) desalination units are considered as the most widespread technology used for this purpose due to the advantage of low power consumption. On the other hand, renewable energy resource integration into the power systems is an important trend, which serves energy supply especially in rural areas and non-stable power supply places. RO units powered from Photovoltaic (PV) systems are considered one of the reliable solutions in places where both water and energy demands are issues to be improved. In this research, the idea of storing energy in water salinity is introduced and discussed to reduce conventional battery storage banks. This concept depends on changing the pressure of the RO unit based on solar profiles to get high distilled water at high solar radiation times (high pressure applied) and low distilled water at low radiation times (low pressure values). Then, the produced water is mixed to get an acceptable salinity in the produced water. This research was applied on a small-scale RO testing unit with a pressure that changed from 40 to 60 bar, and, as a result, the water conductivity changed from 1.7 to 1.1 mS/cm. This was the base line to investigate the possibility of curtailing the battery storage system of the selected plant. Following the variable pressure scenarios, energy storage capacity was reduced by a factor of 20%.

Assessment of the Viability of Standalone Photovoltaic Systems for Rural Households in Kathiani, Machakos County, Kenya

Assessment of the Viability of Standalone Photovoltaic Systems for Rural Households in Kathiani, Machakos County, Kenya

Optimal Sizing of Standalone Photovoltaic System Using Improved Performance Model and Optimization Algorithm

A standalone photovoltaic system mainly consists of photovoltaic panels and battery bank. The use of such systems is restricted mainly due to their high initial costs. This problem is alleviated by optimal sizing as it results in reliable and cost-effective systems. However, optimal sizing is a complex task. Artificial intelligence (AI) has been shown to be effective in PV system sizing. This paper presents an AI-based standalone PV system sizing method. Differential evolution multi-objective optimization is used to find the optimal balance between system’s reliability and cost. Two objective functions are minimized, the loss of load probability and the life cycle cost. A numerical algorithm is used as a benchmark for the proposed method’s speed and accuracy. Results indicate that the AI algorithm can be successfully used in standalone PV systems sizing. The proposed method was roughly 27 times faster than the numerical method. Due to AI algorithm’s random nature, the proposed method resulted in the exact optimal solution in 6 out of 12 runs. Near-optimal solutions were found in the other six runs. Nevertheless, the nearly optimal solutions did not introduce major departure from optimal system performance, indicating that the results of the proposed method are practically optimal at worst.

A hybrid solar chimney/photovoltaic thermal system for direct electric power production and water distillation

In this work, modifications are made on the conventional solar chimney system in order to improve its economic viability. The two main modifications are the addition of a photovoltaic (PV) system to increase the system total electricity production, and the installation of water pool to cool the PV panels as well as to allow the system to generate freshwater. A mathematical model is developed to test the feasibility of both the conventional and modified systems. It is found that the total system utilization factor for the conventional system is 0.51%, while the utilization factor for the modified system is 4.37%. Parametric analysis is conducted to determine the variables that lead to the best utilization factor. The best results are achieved when the submerged PV panels are closer to the chimney. Furthermore, the performance of the system is tested, taking into account the weather data of a location in the country of Jordan. The results showed that the proposed system produces 45.35% more electricity annually than a standalone PV system installed in the same location. Moreover, the sensitivity analysis conducted shows that the chimney height is the most significant variable influences the system utilization factor. That is, the higher the chimney, the higher the utilization factor. Finally, the economic analysis concludes that the cost of freshwater produced by the system is 1.60 US$ per cubic meter, which is 46.3% cheaper than what is produced using other similar systems. Also, the economic indices of the proposed system show an improvement from that for the conventional solar chimney.

Application of artificial neural network in sizing a stand-alone photovoltaic system: a review

<span>Artificial Neural Network (ANN) techniques are becoming useful in the current era due to the vast development of the current computer technologies. ANN has been used in various fields especially in the field of science and technology. One of the advantage that makes ANN so interesting is the ANN’s ability to learn the input and output relationship even though the relationship is non-linear. In addition, ANN is also useful for modelling, optimization, prediction, forecasting, and controlling systems. The main objective of this paper is to present a review of the ANN techniques for sizing a stand-alone photovoltaic (PV) system. The review in this paper shows the potential of ANN as a design tool for a stand-alone PV. In addition, ANN is very useful to improve the sizing process of the stand-alone PV system. The sizing process is of paramount importance to a stand-alone PV system in order to make sure the system can generate ample electrical energy to supply the load demand.</span>

A Combined Three-Port LLC Structure for Adaptive Power Flow Adjustment of PV Systems

This article proposes a scheme to achieve improved efficiencies for a standalone photovoltaic (PV) system. Specifically, a combined three-port LLC structure is utilized to adaptively regulate the power sharing between the PV and the energy storage battery. This is fulfilled by adjusting the equivalent resonant conditions of two phase-controlled resonant tanks through a shared resonant capacitor. Thus, the overall efficiency is improved by simultaneously reducing the power conversion stages and optimizing LLC converters with fixed-frequency operation. Because an extra power flow path is added to discharge the battery, the nonisolated converter used for battery charging does not need to be bidirectional. Also, since each resonant tank can share part of the load, the new circuit does not add any extra costs of power components. In addition to detailed theoretical analysis, experimental results verify the effectiveness of the proposed concept.

Detection of cleaning interventions on photovoltaic modules with machine learning

Soiling losses are a major concern for remote power systems that rely on photovoltaic energy. Power loss analysis is efficient for the monitoring of large power plants and for developing an optimal cleaning schedule, but it is not adapted for remote monitoring of standalone photovoltaic systems that are used in rural and poor regions. Indeed, this technique relies on a costly and dirt sensitive irradiance sensor. This paper investigates the possibility of a low-cost monitoring of cleaning interventions on photovoltaic modules during daytime. We believe that it can be helpful to know whether the soiling is regularly removed or not, and to decide if it is necessary to carry out additional cleaning operations. The problem is formulated as a classification task to automatically identify the occurrence of a cleaning intervention using a time window of temperature, voltage and current measurements of a photovoltaic array. We investigate machine learning tools based on Logistic Regression, Support Vector Machines, Artificial Neural Networks and Random Forest to achieve such classification task. In addition, we study the influence of the temporal resolution of the signals and the feature extraction on the classification performance. The experiments are conducted on a real dataset and show promising results with classification accuracy of up to 95%. Based on the results, three implementation strategies addressing different practical needs are proposed. The results may be particularly useful for non-governmental organizations, governments and energy service companies to improve the maintenance level of their photovoltaic facilities.

Design and Control of Standalone PV System without ESD Usage for Enhanced Energy Utilization

Background: A Standalone Photovoltaic (PV) based system has practical constraints like the need for Energy Storage Devices (ESD) in order to ensure 24 hours availability of electricity and optimized usage of available PV power. Implementation of hybrid renewable energy based system depends upon geographical location and thus availability of a specific energy resource. Also, ESDs are costly to maintain and thus limited optimized usage of ESD is suggested in the literature. Methods: In this paper, a new concept of a PV system integrated with pumped storage is presented for electrification/implementation in rural areas. Proposed system operates at Maximum Power Point Tracking (MPPT) without de-rating the PV capacity or any need of ESD. The control philosophy is simple, robust and ensures two modes of operation for pumped storage i.e. motoring mode and generating mode; depending upon the PV power being generated, load demand and available water level in lower and upper reservoir. Result: The effectiveness of the proposed system and control architecture is verified through MATLAB/Simulink simulation. For various modes of operation, the proposed system is able to maintain DC bus voltage, AC 3-phase voltage, the frequency at approximately constant desired values. Conclusion: However, to operate the PV system at night with heavy loads, additional ESD may be required for better response and stability.

Robust design of type-2 fuzzy logic-based maximum power point tracking for photovoltaics

Photovoltaic (PV) power generation is uncertain and intermittent due to varying insolation and temperature. The Maximum Power Point Tracking (MPPT) algorithm implemented in a DC/DC converter ensures maximum PV power generation for a given insolation and temperature. This paper proposes a novel method to achieve this optimization under uncertainty: (1) An Interval Type-2 Fuzzy Logic System (IT2FLS) is used to tune the duty cycle of a DC/DC converter. The control gains and IT2 membership functions are tuned optimally using approximate gradient-descent algorithm. The so-called footprint of uncertainty (FOU) in the IT2 membership functions ensures that the IT2FLS is more powerful than traditional FLS in dealing with noise and uncertainty. (2) Taguchi’s orthogonal scenarios are used to evaluate the PV power generations by considering different meteorological conditions. Signal-to-noise ratios (SNR) obtained from Taguchi’s experiments are then analyzed by average effect of all control factor levels and main effect of each control factor to achieve the robust design of control gains and IT2 fuzzy membership functions. The proposed method is implemented using a DSP Chip-in-the-Loop (DIL) simulation through a real-time simulator OPAL-RT (OP5600) and TI DSP Chip (eZdsp TMS320F28335). A standalone PV system with a boost converter and load is used to demonstrate the practical applicability of the proposed method.

An MPPT controller model for a standalone PV system

ABSTRACT Designing an efficient photovoltaic (PV) system is a complex task that involves modelling and simulation of all of its subsystems. The simulation results are usually obtained by performing behavioural simulations, which is useful when simulating at the system level, though it is not possible to implement models of real electronic components due to an absence of adequate libraries. In this manuscript we will focus on a simulation of electronic circuits performing maximum power point tracking control (MPPT), which is one of the standalone PV subsystems, using circuit-level model. Here we will introduce some modifications to perturb and observe method in order to facilitate circuit-level simulation, and present a SPICE circuit implementing that MPPT algorithm. The importance of the contribution comes from the fact that the SPICE implementation of the algorithm is circuit (technology) independent.

Multiple scenarios multi-objective salp swarm optimization for sizing of standalone photovoltaic system

The paper presents a new multiple scenario multi-objective salp swarm optimization (MS-MOSS) algorithm to optimally size a standalone PV system. An accurate estimation of the number of PV modules and storage battery is crucial as it affects the system reliability and cost. Three scenarios have been presented focusing on Pareto optimal solutions by minimizing two conflicting objectives. Loss of load probability (LLP) and life-cycle cost (LLC) are considered to obtain the Pareto front. The iterative method is employed for validation of the superiority results of the proposed MS-MOSS algorithm. The results show that the scenarios are able to find Pareto optimal configuration at a high level of accuracy and at a very low cost. The proposed three scenarios are faster than iterative approach approximately by 158, 194.2, and 141.6 times, respectively. The third scenario outperforms other scenarios in terms of coverage and convergence of the distribution of solution to the Pareto front. As a conclusion, The MS-MOSS algorithm is found to be very effective in sizing of SAPV system.

Accurate Sizing of Residential Stand-Alone Photovoltaic Systems Considering System Reliability

In rural areas or in isolated communities in developing countries it is increasingly common to install micro-renewable sources, such as photovoltaic (PV) systems, by residential consumers without access to the utility distribution network. The reliability of the supply provided by these stand-alone generators is a key issue when designing the PV system. The proper system sizing for a minimum level of reliability avoids unacceptable continuity of supply (undersized system) and unnecessary costs (oversized system). This paper presents a method for the accurate sizing of stand-alone photovoltaic (SAPV) residential generation systems for a pre-established reliability level. The proposed method is based on the application of a sequential random Monte Carlo simulation to the system model. Uncertainties of solar radiation, energy demand, and component failures are simultaneously considered. The results of the case study facilitate the sizing of the main energy elements (solar panels and battery) depending on the required level of reliability, taking into account the uncertainties that affect this type of facility. The analysis carried out demonstrates that deterministic designs of SAPV systems based on average demand and radiation values or the average number of consecutive cloudy days can lead to inadequate levels of continuity of supply.

Nonlinear Control for Positive Output Super Lift Luo Converter in Stand Alone Photovoltaic System

This paper proposes a stand-alone photovoltaic (PV) system based on a DC-DC positive output super lift Luo (POSLL) converter. A conventional sliding mode control, a sliding mode controller using a simple sign function and a linear controller using proportional integrator (PI) are used for the control of the PV panel voltage and POSLL converter inductor current and these methods are compared together. The POSLL converter is a DC-DC converter with higher voltage gain compared to other conventional DC-DC converters, and has a good voltage regulation with a simple structure. The stability and accessibility of the proposed nonlinear controls are investigated widely. The internal dynamics of the proposed closed-loop control systems are also investiged. A practical implementation of the system on a hardware setup is performed using a low cost Discovery real time digital control platform. The experimental and simulation results demonstrate the validity of the proposed control schemes over a stand-alone real photovoltaic system.

Sizing verification of a 4kWp retrofitted grid-connected photovoltaic system: a case study in Shah Alam, Malaysia

Electricity are commonly generated from several types of energy resources such as fossil and nuclear energy. However, due to emission of carbon dioxide from both sources, renewable energy is introduced to provide a clean and secure sustainable energy. One of the potential renewable energy application is Photovoltaic (PV) system; namely grid-connected photovoltaic (GCPV) system and stand-alone photovoltaic (SAPV) system. In this study, a mathematical approach of SEDA’s GCPV sizing model is implemented to size a 4kWp of a retrofitted GCPV system by the method claimed to be the best practice mathematical design model under tropical climate Malaysia. The outcome of the sizing approach will then be evaluated with HelioScope software, one of commercial simulation tools available in current market. The final result obtained from both methods shows that the final PV array configuration is 1 x 12 (parallel x series) which is in agreement to the actual installed system.

Improvement in Performance of Series Z-Source Inverter with an Application as Solar PV Fed Water Pump

For a stand-alone solar pump, Z-source inverter (ZSI) is being preferred because of its single-stage power conversion capability with buck-boost ability. As compared to traditional ZSI, series Z-source inverter (SZSI) reduces the voltage stress on capacitor and inrush current of the inductor significantly. In this paper, modes of operation of the SZSI for an induction motor load are explained. When an induction motor runs at a low power factor, an additional mode exists. In this mode, high-magnitude pulses appear on the DC link voltage if the decoupling capacitor is not used with an unidirectional source like solar photovoltaic (PV). In addition, an improved modulation technique is proposed to improve the performance of SZSI. This paper presents a performance of SZSI with solar photovoltaic as a source and an induction motor coupled with the centrifugal pump as a load. Simulation results show the performance of the proposed scheme. Experimental and simulation results demonstrate the validity of analysis. Therefore, SZSI is a promising topology for the solar PV stand-alone system.

A Novel Fault Classification Approach for Photovoltaic Systems

Photovoltaic (PV) energy has become one of the main sources of renewable energy and is currently the fastest-growing energy technology. As PV energy continues to grow in importance, the investigation of the faults and degradation of PV systems is crucial for better stability and performance of electrical systems. In this work, a fault classification algorithm is proposed to achieve accurate and early failure detection in PV systems. The analysis is carried out considering the feature extraction capabilities of the wavelet transform and classification attributes of radial basis function networks (RBFNs). In order to improve the performance of the proposed classifier, the dynamic fusion of kernels is performed. The performance of the proposed technique is tested on a 1 kW single-phase stand-alone PV system, which depicted a 100% training efficiency under 13 s and 97% testing efficiency under 0.2 s, which is better than the techniques in the literature. The obtained results indicate that the developed method can effectively detect faults with low misclassification.

Reliability evaluation of stand-alone hybrid photovoltaic energy system for rural healthcare centre

This paper presents two methods for evaluation of reliability indices of stand-alone hybrid photovoltaic (PV) energy system. Markov model and frequency-duration (F-D) reliability techniques have been used for evaluation of reliability indices. Hybrid energy system is design and evaluated reliability indices for its configurations (Diesel only, PV/Battery and PV/Diesel/Battery). The system reliability is based on the system failure rate, interruption duration, unavailability, loss of load probability (LOLP), expected energy not supplied (EENS) mean downtime (MDT) indices, which are computed and compared different energy generation system configurations. This paper also presented hybrid energy system reliability analysis is based on monthly solar radiation and load demand data. It is observed that hybrid energy system failure rate, interruption duration, system unavailability, EENS, MDT and LOLP are least as compared to other configuration. The results show that hybrid PV/Battery/Diesel system is more efficient and reliable system as compared to other configurations. This research work will be useful for policymakers and system designers to determine optimal system in remote areas before installation.