Standalone Solar Photovoltaic System Research Articles

Solar Powered Electric Vehicle Charging Station With Integrated Battery Storage System

ABSTRACTThe shift towards electrical vehicles (EVs) can be an important alternative to internal combustion engines for sustainable energy solutions. However, increased EV adoption will increase the charging demand, and there will be a load on the grid electricity. Integrating solar photovoltaic systems with EV charging infrastructure will not only support environmental goals, but also ensure a more resilient and self‐sufficient energy system. A standalone PV system is a good option to reduce the stress on the grid for charging EVs. This present work pivots on the design and performance assessment of a solar photovoltaic system customized for an electric vehicle charging station in Bangalore, India. For this purpose, we have used the PVsyst software to design and optimize a standalone PV system with battery energy storage for EV charging stations. The result shows that 51.1 kWp PV system will be sufficient to meet the energy demand of the charging station by producing 98 313 kWh array energy. The proposed system showed a good average performance ratio of 68.90%. This study shows that the integration of standalone solar photovoltaic systems with EV charging stations is crucial in India and other countries to alleviate grid stress and promote sustainable energy use. This approach not only supports the transition to cleaner transportation but also enhances energy security and reduces dependency on fossil fuels.

Maximizing off-grid solar photovoltaic system efficiency through cutting-edge performance optimization technique for incremental conductance algorithm

The maximum power point tracking (MPPT) algorithms are required to deliver the optimal energy from solar photovoltaic cells/array (PV) under numerous weather conditions. Therefore, MPPT circuits driven by defined rules called algorithms are designed. These algorithms range from simple to complex in design and implementation and are selected based on the scenarios of the surroundings. However, the incremental conductance (InC) MPPT algorithm is one of the market's most simple, easy to implement, and demanding algorithms. The drawback associated with the InC algorithm is its tracking speed. To overcome this weakness various researchers have made multiple improvements. Although the performance became better but was not satisfied. Further, the improvements introduce steady-state oscillations of the operating point around the MPP. So, the user needs to pick and choose based on demand. Keeping the target in focus, we have introduced a couple of modifications in the structure of INC. that remain fruitful. The proposed structure named the augmented InC algorithm has shown marvelous improvement in tracking speed and steady-state oscillations. The results have been compared with the conventional InC algorithm, where the proposed augmented InC algorithm has outperformed the conventional InC algorithm in tracking speed and steady-state oscillations. We have used the MATLAB script to code the conventional InC algorithm and proposed augmented InC algorithms based on their designed flowchart. Both algorithms have been applied to the standalone solar photovoltaic system composed of a solar photovoltaic array, DC/DC boost converter, illumination and temperature inputs, MPPT algorithm, and a DC load. The model is designed in Simulink/MATLAB.

Battery-less uncertainty-based control of a stand-alone PV-electrolyzer system

Solar photovoltaic (PV) energy is variable. The output power can change considerably in a matter of minutes, imposing challenges on the control of systems connected downstream. The power from these systems can be smoothed using electric storage, potentially increasing the system cost. An alternative is to deliberately curtail the power before it starts to change. This strategy relies on ultra-short-term forecasting to determine the curtailment point. Unfortunately, forecasting is prone to errors and high uncertainty even in the very short-term, leading to control errors. We propose an active power curtailment control strategy for a stand-alone solar photovoltaic system powering an electrolyzer. Our work’s novelty relies on the controller’s ability to deal with large forecasting errors and high uncertainty, combining artificial intelligence for predicting the power ramps and fuzzy logic to account for imperfect prediction. We validated our approach using a hardware emulator of the photovoltaic system, power converter and electrolyzer. Under clear sky conditions, the curtailment results in unnecessary energy loss, while under variable irradiance, the controller successfully smooths the power ramps within 10% of the PV system’s nominal power. Although our approach was designed for a stand-alone system, its concept can be directly applied to grid-connected systems as well.

A high gain Z-source boost DC–DC converter with common ground for solar PV applications

This paper proposes a high-gain dc–dc converter with common ground utilizing a Z-source network for low voltage solar photovoltaic (PV) applications. This converter features a common ground and a high output–input voltage conversion factor at a low duty cycle. These converters find their most common application in grid-tied or stand-alone solar photovoltaic systems, particularly those with low output voltages that must be increased to the required level. The presented converter operating duty ratio is within 0–0.5 and maintains similar voltage stress on Z-network components since it employs the conventional Z-source configuration. The presented converter provides a common ground between source and load, unlike conventional Z-network converter. A type-2 closed-loop voltage controller and state–space average model evaluate the converter’s dynamic behavior for reliable and steady performance. A laboratory hardware prototype of 250 Watts is built and low gate signals are generated by using a ARM cortex M4 Microcontroller (STM32F407VGT6). The experimental results confirm that the proposed converter, with a gain of 10.46 and a power of 250 Watts, has a maximum efficiency of around 93%. The experimental results validates the effectiveness of the proposed converter under both constant and shifts in amounts of solar irradiation.

Simulation based study of Maximum Power Point Tracking and Frequency Regulation for Stand-alone Solar Photovoltaic Systems

The main objective of this paper is to develop a simulation model of stand-alone solar photovoltaic (PV) system based on mathematical models. A maximum power point tracking (MPPT) algorithm based on incremental conductance method is applied to extract the maximum power from solar PV energy conversion system. A DC/DC boost converter allows the MPPT to control the intermediate voltage. To regulate to voltage at load side a voltage source converter (VSC) based controller is applied to generate the pulse signal for three-phase inverter. The frequency regulation controller is developed based on conventional phase locked loop (PLL) system along with resistive dumping loads. A simulation model based on mathematical model Matlab®/Simulink®/SimPower® is constructed interface. Results using from simulation are stated to demonstrate the behaviour of stand alone solar PV energy conversion system.

Technical and economic analyses of PV battery systems considering two different tariff policies

Installing batteries in solar photovoltaic (PV) houses is becoming commonplace and different tariff policies give residents more options to lower their energy bills. This paper develops two rule-based control strategies to operate solar PV battery systems under fixed flat or time-of-use tariff policies, aiming to increase PV self-consumption and self-sufficiency. The battery modelling considers the charging and discharging efficiencies and the battery energy efficiency. The payback period for solar PV battery systems under the two tariff policies is also analysed considering various economic factors such as the capital cost of solar PV systems, the capital and maintenance costs of the batteries, the annual discount rate and the increases or decreases in the retail prices of grid electricity and the feed-in tariff. The analyses are conducted using actual PV energy and smart meter data from a real case study house in Geelong, Australia. Results indicate that when battery capacity is increased, PV self-consumption and self-sufficiency grow under both tariff policies, but this trend is limited by constrained PV generation due to seasonal conditions. Additionally, increasing solar PV system size for fixed battery capacity increases PV self-sufficiency, but decreases PV self-consumption. Results of economic analysis demonstrate that the payback period for a standalone solar PV system increases as its capacity grows. Moreover, the payback period for PV batteries can be slightly shorter or even longer than using solar PV systems alone under both tariff policies, which is economically unattractive. Considering the benefits that batteries can bring to residents and electricity networks, local governments need to be more proactive in providing financial subsidies for residents to install batteries.

Maximum Power Point Tracking Controller Algorithm Based on the Artificial Neural Network for a Standalone PV Solar System

This paper presents an optimization technique based on Artificial Neural Networks (ANN). This technique aims to extract the maximum power from a standalone solar photovoltaic (SPV) system with good precision, speed and robustness. A comparative study is carried out with the Maximum Power Point Tracking (MPPT) control algorithms based on Perturbation and Observation (P&O) and Incremental Conductance (InC) to justify the performance of the proposed method. By a study of speed and precision, the simulation results show the effectiveness of the neural technique by a response time (Rt), Root Means Square Error (RMSE) and Means Absolute Error (MAE) of 26.75 ms and 0.4109 respectively. With no overshoot, the proposed method ensures an efficiency of 98.527 % compared to the classic techniques (P&O and InC) which respectively give 93.989 % and 89.894 %. In addition to these performances, the method based on the ANN retains better robustness than the P&O and InC with regard to meteorological variations by a good follow-up of the reference power.

Design methodology and implementation of stand-alone solar photovoltaic power system for daily energy consumption of 9.16 kWh

This stand-alone solar photovoltaic power system was designed to power a daily energy consumption of 9.16 kWh reliably, by means of photovoltaic only. The design involves different components whose capacities depend on 9.16 kWh daily energy consumption and 1-day autonomy, including several factors that determine the choice of selection. After implementation, the system was put to the test for two days to ascertain the design validity and check if it would be able to sustain the daily load demand for 24 h without failure. The results reveal that the design methodology employed for the stand-alone system in this study is accurate and reliable because the system was able to power the load interminably for 34 h, with a resulting 0.6% DoD at the end of the test. This was due to the complete energy balance that the design methodology offers. Day 1 shows that the overall PV array power was 208% higher than the daytime load power and 61.2% higher than the overall daily load power. While Day-2 shows the overall PV array power to be 130% higher than the daytime load power and 56.3% higher than the overall daily load power, The energy balance between PV array, battery, and load size was completely and sufficiently achieved on both days, as the highest depth of discharge recorded during the test was 48.7%. The study reveals that through a complete energy balance between PV, battery, and load size, a standalone PV system can reliably sustain daily energy demand. It aims to design a stand-alone PV system capable of reliably sustaining daily energy demand without the need for long days of autonomy, so as to help prevent failures in solar PV projects that come as a result of inappropriate sizing, planning, and a lack of technical know-how.

Solar irrigation in sub-Saharan Africa: economic feasibility and development potential

Irrespective of water resource abundance, agriculture in sub-Saharan Africa (SSA) is predominantly rainfed. Along with fertilization, irrigation could support smallholder farmers with stabilizing crop yields, increasing incomes, and achieving food security. A key barrier to irrigation uptake is inadequate rural electricity supply for pumping and distributing water, besides other infrastructure deficits. Here we devise a spatially explicit integrated modelling framework to show that over one third of unmet crop water requirements of 19 major crops in smallholder cropland of SSA could be supplied with standalone solar photovoltaic (PV) irrigation systems that can be paid back by farmers within 20 years. This accounts for 60 km3 yr−1 of blue irrigation water requirements distributed over 55 million ha of currently rainfed harvested area (about 40% of the total). Crucially, we identify 10 million ha with a profit potential >$100 ha−1 yr−1. To finance such distributed small-scale infrastructure deployment and operation, we estimate an average discounted investment requirement of $3 billion yr−1, generating potential profits of over $5 billion yr−1 from increased yields to the smallholder farmers, as well as significant food security and energy access co-benefits. We demonstrate the critical importance of business models and investment incentives, crop prices, and PV & battery costs in shaping the economic feasibility and profitability of solar irrigation. Yet, we find that without strong land and water resources management infrastructure and governance, a widespread deployment of solar pumps may drive an unsustainable exploitation of water sources and reduce environmental flows. Our analysis supports public and private stakeholders seeking to target investments along the water–energy–food–economy–sustainable development nexus.

An intelligent converter and controller for electric vehicle drives utilizing grid and stand-alone solar photovoltaic power generation systems

In this study, a battery energy management system for electric vehicle (EV) applications is proposed with a standalone photovoltaic (PV) source and controlled based on the availability of grid, PV source, load consumption, and energy stored in the battery. This paper proposes a single-ended primary-inductance converter (SEPIC) DC-DC converter for charging the battery through the utility and PV source that provides good load regulation. The bidirectional nature of the proposed DC-DC converter provides the charging and discharging of the EV battery in the succeeding modes of operation, i) grid-tied charging, ii) PV-tied charging, iii) discharging to the load in the absence of utility and PV source, and iv) regenerative braking. An improved perturb and observe-based maximum power point tracking (MPPT) algorithm is proposed to track the maximum power from the PV source. In addition, to handle the four modes of operation, a dedicated controller is also proposed. Firstly, the proposed system is validated using MATLAB/Simulink software by considering different operating conditions, and the performance is compared with the traditional MPPT algorithms. Finally, the effectiveness of the suggested system is validated through an experimental prototype. The result proved the superiority of the converter and controller over the traditional systems.<div align="center"> </div>

Real-time implementation of sliding mode controller for standalone microgrid systems for voltage and frequency stabilization

This paper presents for stabilizing the output voltage and frequency of the hybrid source microgrid system (HSMG) and standalone solar photovoltaic microgrid system (SAPV), under varying source and loading conditions. An HSMG system consists of a solar, wind and battery system incorporated with a solar boost converter, wind rectifier/boost converter and bidirectional converter, respectively. These different dc level outputs are applied to the multiple input dc–dc converter for obtaining the constant dc level and then converted into three-phase power with suitable inverters. The source-side converters are designed to obtain the maximum output irrespective of the input conditions with PI controllers. The multiple input dc–dc converter controls the dc link voltage with the well-designed proportional, proportional integral, proportional integral derivative controller. The three-phase inverter is premeditated to obtain the constant voltage and frequency even under varying load patterns. The tuning of the PID controller is incorporated with Ziegler Nichols’s technique to reduce the frequency deviation and steady-state error. A SAPV microgrid system is developed with a high-capacity solar system incorporated with two-stage power conversion. Stage 1 and 2 are constant dc/constant ac obtained using suitable converters incorporated with an adaptive controller. The sliding mode controller (SMC) is an adaptive controller that performs better in dynamic operations. In this work, SMC maximizes the solar output and stabilizes the DC voltage using an appropriate PWM pulse to the boost converters. Also, the output voltage and frequency are maintained constant during the different operating situations. All simulations are carried out in MATLAB. PID and SMC controllers are implemented to the HSMG and SAPV microgrid systems in the OPAL-RT environment to validate the results in real-time applications respectively. The different operating conditions are tested for both the systems and the results prove that the chosen controllers are more suitable for these applications.

Effect of cloud transits in a stand-alone solar photovoltaic water pumping system

This paper discusses the effects of cloud transit on a stand-alone direct solar photovoltaic water pumping system for irrigation and farms. In this way, its impact is studied, applying a possible classification based on its incidence and effects on the system. For this, the information provided by the data loggers of different photovoltaic installations has been analyzed and in turn compared with the data obtained in the reference installation. In addition, the Matlab-Simulink simulation model used is described. Different simulations have been developed to verify the basic characteristics of the proposed system. In this way, it is possible to check the advantages and drawbacks of the direct water pumping in irrigation applications. At the same time, the system parameters can be easily modified to meet the requirements of different water flow capacities. Also, the water hammer effect and the cavitation phenomenon in the water pump are described. Finally, the simulation results obtained as well as their conclusions are presented.

Modeling of a stand-alone solar photovoltaic water pumping system for irrigation

Solar photovoltaic water pumping systems have been research topics in recent decades. The purpose was to develop much more profitable and efficient systems to meet the needs of pumping water for livestock and irrigation. This paper describes the design of a stand-alone photovoltaic water pumping system. A Boost converter is used to apply the Maximum Power Point Tracking (MPPT) algorithm. Similarly, a three-phase voltage source converter (VSC) is used to supply the asynchronous motor. The installation must provide a continuous water flow during the irrigation interval. It has been verified that in adverse weather conditions (cloud transits or partly cloudy) it is necessary to incorporate a decentralized-hybrid energy storage system (based on batteries or ultracapacitors), or excessively oversize the standalone photovoltaic system, to supply the water pump. The model has been simulated in Matlab-Simulink. In this way, different simulations have been developed to verify the basic characteristics of the proposed system. The results of the simulated model and the conclusions obtained are also presented in this paper.

Integrated battery management system employing multi-port DC/DC converter for standalone solar photovoltaic system

ABSTRACT The standalone solar photovoltaic (PV) systems employing multiport converters utilize battery as buffers to handle excess or deficit solar PV power. However, a review of literature has shown that often no battery management unit in the control schemes of multi-port converters used in such hybrid systems and also there is an abnormality in the levels of battery voltage. The battery management unit systems are essential to maintain battery at safe operating limits of current and voltage. This paper proposes one such unit for a standalone solar PV system make use of a single inductor, dual input/output DC-DC converter along with the developed time sharing control scheme. It consists of a battery management unit scheme that implements the standard three-stage charging process. The battery management unit is integrated into a dynamic power management scheme for a standalone solar PV system which consists of combined voltage control and MPPT control. Further, the reduction in solar power of around 50% makes the voltage controller to adjust its duty ratio by almost 50% of its previous value to maintain the constant load power. The built in experimental setup in the laboratory validates the working of the proposed battery management system.

Optimal coordinated energy management strategy for standalone solar photovoltaic system with hybrid energy storage

Energy storage devices and renewable resources, especially rooftop photovoltaic (PV), are vital to the operation of standalone systems. In this study, an energy management strategy (EMS) for battery energy storage systems (BESS), PV, and supercapacitors (SC) is presented. The proposed control strategy is designed to optimize the BESS flow rate, discharge, and charge cycles of the energy system using the Meta-heuristic Jaya algorithm by properly coordinating SC and PV. SC is employed in HESS to fulfill the transient energy mismatches and reduce the transitory high charge/discharge current rate impacts on BESS using EMS. The proposed controller also has the benefit of keeping the battery's SoC within limitations for a long period. To extend the life of BESS, the EMS is aimed at minimizing deep charging and discharging by reducing PV generation, particularly under light load (no-load) situations and when battery and SC's SoC≥SoCmax or charging. Similarly, the optional load shedding is employed when battery and SC's SoC≤SoCmin to avoid deep discharge. The proposed EMS is validated in both simulation environment and hardware-prototype under different perturbations and operating conditions. The charge and discharge rate performance of BESS and SC under different charge and discharge time durations, i.e., 1 s, 2 s, and 3 s, were evaluated in both simulation and hardware, and compared to conventional charge and discharge methods for HESS, whose charge and discharge time durations are nearly 0.3 s to 0.4 s. As a result, battery stress is significantly reduced. Furthermore, the economic analysis of the complete system is carried out. In this, it is observed that standalone PV and HESS systems with the proposed EMS are cost-effective and economical compared with PV and BESS systems when operated for a long horizon beyond 6 years.

Development of Amphibious Mobile Solar Power Generator with Ultra Water Filtration System for Disaster Relief

During severe flood and natural disaster scenarios, electricity power becomes an essential and critical element to ensure the operation of medical services, equipment and communication systems as the power stations will most likely be shut down. Delivering power source and potable water to disaster areas becomes a major obstacle during severe flooding following the rise of water level causing road transportation becomes inaccessible. Therefore, an amphibian trailer equipped with a hybrid solar photovoltaic (PV) and an ultra-water filtration system is a good solution as it can be deployed or towed to the disaster areas by either a boat or a pickup truck. The amphibian trailer is equipped with a hybrid standalone solar PV system with battery storage and a generator set that can supply approximately 25 kWh of electric power per day. An ultra-water filtration system is also installed on the trailer, and it is powered by the hybrid solar PV system. Aluminium is used to construct the chassis of the trailer to ensure that the trailer is lightweight, strong, durable, and anti-corrosion. The wheeled trailer is integrated with a fiberglass floatable pontoon to allow it to operate on land and water. More importantly, the amphibious trailer can be relocated easily based on the situation and needs. This paper describes comprehensively the design and development process of the solar amphibious trailer.

ANFIS MPPT with power management strategy to harvest reliable power from standalone PV systems to residential loads

<span lang="EN-US">In recent decades, the matching between the growing energy demand and generation is becoming the challenging task to the researcher’s leads for the development of standalone solar photo voltaic (SSPV) power system. The SSPV system is more suited for electrification of essential loads uses DC power as it offers high efficiency. This work aims to model and simulate SSPV with lead acid battery is used as a DC source. The proposed series shunt charge controller with power management strategy (PMS)is designed and modeled to control the power flow among SSPV, battery and the load. adaptive neuro fuzzy inference system (ANFIS) controller effectively regulates the output voltage by controlling duty ratio of the suitable converter for driving a DC load. A PMS is developed for selecting the operating mode of SSCC by sensing and regulating the battery voltage within 11.6-12.95 V. Here, the 250 Wp panel has been employed to charge a 12 V, 34 AH battery. The practicability of SSPVB system is verified under various loaded conditions using MATLAB/Simulink for a period of 24 hours. A simulation result proves that this SSPV Battery system is capable to electrify the essential loads in rural and isolated areas and also reduce the dependency of grid power.</span>

Management of Electric Energy in Stand-alone Off-grid Solar PV System

The stand-alone solar photovoltaic system has different kinds like on-grid and off-grid. This paper deals with the analysis, design and control of electric energy with different load profiles in off-grid stand-alone solar photovoltaic systems. The management of electric energy varies according to various load profiles. In here, the loads are considered as only DC loads. This paper shows three different dc load profiles. The goal of the management is to show and control the loads according to the load profiles and observe the outputs in MATLAB/Simulink. The simulation of the system has been developed in MATLAB/Simulink. Here, a simple stand-alone solar photovoltaic model has been used which carries PV module, charge controller, management strategy, battery, loads and a monitoring box to monitor the load profiles. This work introduces the procedure of how to control with different load profiles and what are the outputs. Finally, experimental results and related figures are shown to verify the effectiveness of the proposed energy management strategy.

ENHANCE EFFICIENCY OF SOLAR ENERGY CONVERSION SYSTEM USING ANFIS WITH ISOLATED MODE

This paper shows performance investigation on enhance efficiency of standalone solar energy conversion system using ANFIS based MPPT controller. Now a days many researches are going in the field of renewable energy technologies to bridge the gap between supply and demand. Due to the Intermittent nature of renewable sources, operating standalone operation of them is highly unreliable causes interruption in power supply to the load. A solar photovoltaic system with MPPT based on Adaptive-Network-Based Fuzzy Inference System (ANFIS) is used for stable operation and to meet the supply with the load demand. The application of ANFIS based MPPT technique requires detailed study and analysis of the Solar Photovoltaic (SPV) system. Adaptive-Network-Based Fuzzy Inference System based MPPT technique is used along with Solar PV system as they can provide fast and accurate response to various environmental conditions. The Levenberg-Marquardt algorithm is used to train the neural network for MPPT in the photovoltaic system. This developed control strategy is able to control the devices and various power interface circuitry used therein. The main aim of this paper is to ensure a maximum power output coordinating appropriate control strategy with sources & compare the performance analysis of the ANFIS based MPPT with conventional incremental conductance based MPPT for the SPV system. The simulation studies have been carried out to find out the SPV system performance with different input conditions such as typical solar radiation and temperature. The Simulation test results show variable power generation and verifies that the performance of the integrated system with this control strategy is effective for the real-time installation. The simulation results shows that the performance of this developed control strategy for receiving maximum power output from the standalone SPV system is farfetched. Simulation test results show variable power generation and verify the performance of the integrated system with control strategy is overall effective for real-time installation. The developed system is essential in an isolated region where an existing grid is unable to supply secure power generation and system is beneficial with smartly feed ultimate power generation sources.

Techno-economic comparison of standalone solar PV and hybrid power systems for remote outdoor telecommunication sites in northern Ghana

Telecommunication services have continued to evolve to meet the ever-changing bandwidth demand requirements. The electricity grid network of Ghana is faced with challenges, including low voltages, a lack of quick fault response teams, and the proximity to specific locations. Using diesel generators to address the shortfall in grid supply is expensive and has implications for greenhouse gas emissions. This study evaluated the technical and economic benefits of using a standalone solar photovoltaic (PV) system, hybrid (Solar PV/diesel), conventional diesel generators (DG), and grid extension to power an off-grid outdoor telecommunication site. Power solutions configurations were simulated using hybrid optimization of multiple electric renewables (HOMER). The study found the optimum design to be a standalone solar PV/battery system with 56.3 kW solar PV array and Sixty (60) pieces of 12 V SAGM batteries of 135 Ah. The optimum design had a net present cost (NPC) of US$ 88,176.00 and a cost of energy (COE) of US$ 0.321/kWh. The COE and the NPC of the optimum system were approximately 50% less than the design with DG only, which could significantly impact service tariff and improve access to digital connectivity. The COE from the solar PV/battery system is not competitive with the grid power supply (COE = US$0.12). However, considering the electric distance limit or breakeven distance of 4.51km for grid extension, the solar PV/battery is preferred. Therefore, the stakeholders in providing power solutions to off-grid locations should consider solar PV technology.