Solar Photovoltaic Generation System Research Articles

A Particle Swarm Optimization–Adaptive Weighted Delay Velocity-Based Fast-Converging Maximum Power Point Tracking Algorithm for Solar PV Generation System

Photovoltaic (PV) arrays have a considerably lower output when exposed to partial shadowing (PS). Whilst adding bypass diodes to the output reduces PS’s impact, this adjustment causes many output power peaks. Because of their tendency to converge to local maxima, traditional algorithms like perturb and observe and hill-climbing should not be used to track the optimal peak. The tracking of the optimal peak is achieved by employing a range of artificial intelligence methodologies, such as utilizing an artificial neural network and implementing control based on fuzzy logic principles. These algorithms perform satisfactorily under PS conditions but their training method necessitates a sizable quantity of data which result in placing an unnecessary demand on CPU memory. In order to achieve maximum power point tracking (MPPT) with fast convergence, minimal power fluctuations, and excellent stability, this paper introduces a novel optimization algorithm named PSO-AWDV (particle swarm optimization–adaptive weighted delay velocity). This algorithm employs a stochastic search approach, which involves the random exploration of the search space, to accomplish these goals. The efficacy of the proposed algorithm is demonstrated by conducting experiments on a series-connected configuration of four modules, under different levels of solar radiation. The algorithm successfully gets rid of the problems brought on by current traditional and AI-based methods. The PSO-AWDV algorithm stands out for its simplicity and reduced computational complexity when compared to traditional PSO and its variant PSO-VC, while excelling in locating the maximum power point (MPP) even in intricate shading scenarios, encompassing partial shading conditions and notable insolation fluctuations. Furthermore, its tracking efficiency surpasses that of both conventional PSO and PSO-VC. To further validate our results, we conducted a real-time hardware-in-the-loop (HIL) emulation, which confirmed the superiority of the PSO-AWDV algorithm over traditional and AI-based methods. Overall, the proposed algorithm offers a practical solution to the challenges of MPPT under PS conditions, with promising outcomes for real-world PV applications.

YSA ve Bukalemun Optimizasyon Algoritmalarına Dayalı DER'lerde Tekno Ekonomik için Pratik Radyal Dağıtım Besleyicisi

Distributed energy resources (DERs) are a better choice to meet load demand close to load centers. Optimal DER placement and DER ratings lead to power loss reduction, voltage profile improvement, environmental friendliness, dependability, and postponement of system changes. This study uses artificial neural networks and the Chameleon Optimization Algorithm to analyze the best integration of renewable energy sources and electric vehicles in distribution feeders to reduce power loss, regulate voltage levels, and decrease the cost and emissions under unpredictable load demand. In this study, the generated output power of the models is compared to solar photovoltaic generation systems and wind turbine generation systems. As a result, a fitness function with several objectives has been developed to reduce total active power loss while also reducing total cost and emissions generation. The study took into account the influence of EV charging/discharging behavior on the distribution system. The 28-bus rural distribution network in feeders is used to test the suggested methodology. Final analysis of the numerical results showed that the Artificial Neural Network and Chameleon Optimization Algorithms outperformed in terms of power loss (440.94 kw) and average purchase of real power (2224 kw), but these parameters do not favor the other optimization algorithms. This showed that the proposed strategy is both viable and effective.

A state of the art a hybrid intelligent strategies of maximum power point tracking: a systematic contemporary

Renewable energy sources are among the best substitute sources to fossil fuel due to it is very suitable for mitigating global warming; solar energy is considered the main causes of renewable energy, and solar photovoltaic (PV) generation systems have gained importance worldwide due to several characteristics, including cheap maintenance, low noise, and low fuel costs. However, one of the most difficult challenges facing solar energy systems is changing weather circumstances. The robust control approach stabilizes the PV system's output and maximizes harvested energy. In this study, several maximum power point tracking (MPPT) performances have been presented. Among them, artificial intelligence (AI) based on MPPT methods demonstrates the ability to capture the MPP point. There are several ways to apply AI to MPPT, and this paper presented various intelligent MPPT methods in detail with their benefits and drawbacks and comparison among them to select which technique is suitable and can be used to change weather conditions with<strong> </strong>horse optimization method (HOM) plus neural artificial system (NAS).

Net green energy potential of solar photovoltaic and wind energy generation systems

“Green energy” is the energy that can be produced while sustaining ecosystem services. Maintenance of the services provided by the ecosystem requires energy, termed the ecosystem maintenance energy (ESME). Including ESME costs in energy accounting enables assessment of an energy plant's ability to produce energy over and above inputs and EMSE costs over the lifetime of the plant. In this work, an assessment of the potential of two renewable energy plants wind and solar photovoltaic to produce “green energy” is undertaken, those were chosen due to their likely dominance of the future energy market. The assessment is done using a methodology that unifies environmental impact assessment, ESME and energy accounting into a single metric termed the green energy return on investment (EROIg). The paper also extends ESME calculation by incorporating ecosystem impacts that were previously unaccounted-for such as: biodiversity loss; delayed ecosystem maintenance; carbon capture by photosynthesis; ozone depletion and formation and ionizing radiation. The solar and wind energy plants considered were sized to produce an equivalent amount of annual energy and were placed at a theoretical location where the capacity factor (CF) is equivalent to the average global utility scale CF for each resource. The study found that onshore wind energy has a greater potential in generating green energy with an EROIg of 17.19. Removal of impacts related to biodiversity loss, which is included here for the first time, is found to play a critical role in plant assessment from both biodiversity and CO2 capture by photosynthesis perspective. Plants needing and providing biodiversity offsets are shown to provide an overall 18%–25% improvement in EROIg. This improvement is triggered by the corresponding CO2 capture by photosynthesis. Some design options were evaluated to determine the sensitivity of the resulting EROIg to the plant design and to the temporal element of the investigation. Those include the addition of battery storage and the delay in action on ecosystem maintenance from a 20-year to a 100-year time horizon which were found to reduce the resultant EROIg by >40% and >87% respectively.

The European Solar Communication—Will It Pave the Road to Achieve 1 TW of Photovoltaic System Capacity in the European Union by 2030?

The urgency of a clean energy transition in the European Union is now not only driven by concerns about climate change, but also by using local renewable energy resources to reduce the dependency on foreign energy imports. Solar photovoltaic electricity generation is acknowledged as one of the pillars of this transition and various policy measures were implemented over the last two years to not only accelerate the deployment of solar photovoltaic electricity generation systems, but also to rebuild a competitive solar value chain in Europe to hedge against solar photovoltaic component supply chain disruptions. However, the current political ambitions still do not pay sufficient attention to the importance of solar photovoltaics as a major contributor to the necessary future renewable energy supply. According to the market trend between 2017 and 2022, the currently average EU installed capacity of 474.55 Wp/capita will not reach the necessary 2246 Wp/capita or 1 TWp target by 2030. At the moment, only seven member states have an installed capacity per capita higher than the average EU value.

Analyzing the Impact of Electricity Rates on the Feasibility of Solar PV and Energy Storage Systems in Commercial Buildings: Financial vs. Resilience Perspective

The use of solar photovoltaic (PV) generation and battery energy storage (BES) systems in commercial buildings has been increasing significantly in recent years. Most of these systems, however, are designed to solely minimize the investment and operation costs. With the increasing concerns about high-impact low-probability (HILP) events, such as natural disasters, and their impact on power system resilience, there is a substantial need to integrate outage risks in power system infrastructure planning problems. This paper examines the impact of various electricity rates on the feasibility of PV and BES systems in commercial buildings for financial and resilience purposes. Simulation studies are conducted using the Renewable Energy Integration & Optimization (REopt) decision support software to optimize the size of solar PV and BES systems for both financial and resilience purposes, considering different combinations of geographic locations, load profiles, electricity rates, and outage durations. The feasibility assessment is conducted by analyzing and comparing the net present value (NPV) for each combination of parameters.

Cooperative Use of IMD and GPT in a 3-Phase Ungrounded Distribution System Linked to a Transformerless Photovoltaic Power Generation Facility

Distributed generations, using solar photovoltaic (PV) generation systems, are generally connected to ungrounded distribution systems to ensure operational continuity and avoid electro-chemical corrosions. The ungrounded power distribution system possesses an advantage of continuous operation regardless of primary fault occurrence due to a small fault current. Conversely, a subsequent secondary fault can induce a large fault current representing that of other electrical grounding types, resulting in inevitable power shutdowns. As preventative methods, both insulation status monitoring and primary failure detection have become of high importance. This paper presents a method enabling the cooperative use of IMD (Insulation Monitoring Device) and GPT (Ground Potential Transformer) in an ungrounded distribution system connected with a transformerless inverter. Moreover, factors leading to errors during IMD insulation monitoring, CLR (Current Limit Resistor) burnout of a GPT, and malfunctions of related protection devices are presented. Furthermore, a method for selecting the inductor and capacitor in consideration of the operating characteristics of IMD and GPT is discussed. The proposed cooperative operation method enables the accurate measurement of insulation resistance using IMD, while concurrently reducing the constitutively induced zero-sequence voltage in the CLR of a GPT to prevent CLR burnouts and malfunctions of connected protection devices. Hence, the method is anticipated to contribute to the stable operation of alternating current (AC) and Direct Current (DC) combined systems connected with transformerless inverters.

Snapshot of Photovoltaics − May 2023

In 2022 the cumulative installed photovoltaic electricity generation capacity increased to over 1 TW, 10 years after it reached the 100 GW level in 2012. In 2022, overall investment in renewable energy has increased by 16% to USD 499 billion compared to USD 953 billion for fossil fuels, which saw an increase of 6%. Investments in solar photovoltaics accounted for USD 301.5 billion or 60% of the renewable energy investments. The annual installations of solar photovoltaic electricity generation systems increased by about 40% to over 230 GWp in 2022. Compared to 2021, the number of countries which installed 1 GWp/year or more has increased by almost 80% to 32. Despite the increase in hardware costs for solar photovoltaic systems and battery storage, both markets had a strong growth, driven by the soaring energy prices in 2022. The increase of the levelised costs for solar photovoltaic electricity was well below the increase of electricity generated with fossil fuels. The electrification of heating, transport and industry will create additional demand for renewable electricity, including solar, if we want to stay on track for not more than 1.5 °C global temperature increase.

Optimal Energy Management System Applied to a Building Involving Solar Renewable Systems, Electrical Vehicles, and Storage Systems

This paper proposes an energy management system to achieve an optimal power flow that minimizes the total economic cost associated with the monthly energy consumption of a five-apartment residential building. The test has considered that each apartment has one electric vehicle, and the building has an energy storage system in the lower plant and a solar photovoltaic generation system on the rooftop. The aim is to provide residential users with guidelines on the times of the day to charge their electric vehicles and the amount of energy to charge each hour in a lower monthly energy bill. The optimization problem regarding economic cost minimization is solved using a particle swarm optimization algorithm. Thus, three cases defined as the consumption of residential users at different day hours are employed to test the method proposed. Simulation results show that the algorithm reduces the energy bill of a typical residential user up to 20.08% compared to a user whose patterns of electric vehicle chargers are not optimized. Additionally, the comparison of the results obtained for the three types of residential users has allowed the establishment of the ideal residential user that guarantees the lowest energy bill possible.

Analysis and optimizes of hybrid wind and solar photovoltaic generation system for off-grid small village

As an effective means of providing power to remote and off-grid areas of developing countries, where rural electrification problems are most common, hybrid renewable energy systems are considered. HOMER simulated and configured wind turbine, photovoltaic, battery bank, and converter for the electricity demand of the Mander rural community, which has 37 families with household sizes of 7 members, as a remote village in Northern Iraq in this article. The hypothesis project was also evaluated using the parameters Net Present Value and Simple Payback Period. Daily energy consumption of 173,120 kWh and peak electricity consumption of 32,14 kW were measured for the outcome of the selected site. The proposed system produced 68,458 kWh/yr (13.7 percent) by the wind turbine, PV created 432,354 kWh/yr. (86.3 percent), and 265 operating batteries with a total operating cost (TOC) and costs of energy (COE) of $9,195 and 0.365 $/kWh, respectively. This survey emphasized the role of solar photovoltaic and wind turbine as hybrid renewable energy systems HRESs in the sustainable supply of electricity in rural areas of northern Iraq.

Design and Implementation of a Flexible Photovoltaic Emulator Using a GaN-Based Synchronous Buck Converter.

In order to efficiently facilitate various research works related to power converter design and testing for solar photovoltaic (PV) generation systems, it is a great merit to use advanced power-converter-based and digitally controlled PV emulators in place of actual PV modules to reduce the space, cost, and time to obtain the required scenarios of solar irradiances for various functional tests. This paper presents a flexible PV emulator based on gallium nitride (GaN), a wide-bandgap (WBG) semiconductor, and a based synchronous buck converter and controlled with a digital signal processor (DSP). With the help of GaN-based switching devices, the proposed emulator can accurately mimic the dynamic voltage-current characteristics of any PV module under normal irradiance and partial shading conditions. With the proposed PV emulator, it is possible to closely emulate any PV module characteristic both theoretically, based on manufacturer’s datasheets, and experimentally, based on measured data from practical PV modules. A curve fitting algorithm is used to handle the real-time generation of control signals for the digital controller. Both simulation with computer software and implementation on 1 kW GaN-based experimental hardware using Texas Instruments DSP as the controller have been carried out. Results show that the proposed emulator achieves efficiency as high as 99.05% and exhibits multifaceted application features in tracking various PV voltage and current parameters, demonstrating the feasibility and excellent performance of the proposed PV emulator.

Development and real time implementation of intelligent holistic power control for stand alone solar photovoltaic generation system

This paper focusses on real-time implementation of an intelligent Holistic Power-Control system which is suitable for uniform, dynamic-irradiance and shaded-conditions for a stand-alone solar-PV system. The model consists of two intelligent Maximum Power Point Tracking(MPPT) control algorithms under different environmental conditions and a novel shading-detection mechanism. A fuzzy logic MPPT system with rule-base developed from real-time solar panel have been implemented. A partial shading detection mechanism based on power loss generated from solar PV array without any sensors is incorporated in the real-time platform. A fuzzy-logic Sweep-Inclusion algorithm is proposed to reach global maximum power point with fast tracking-time under partially-shaded conditions. To test the performance, real-time PV-system with data acquisition using LabVIEW is developed. The standalone solar-PV system is benefitted by the proposed-method by its less tracking-time and more efficiency, accurate partial shading detection through modified power loss scheme and Fuzzy Logic Sweep-Inclusion algorithm for identifying the global-MPPT point.

Life Cycle Costing Analysis of Solar Photo Voltaic Generation System in Indian Scenario

ABSTRACT This paper aims at the application of Life-Cycle-Costing (LCC) analysis of sustainable renewable energy like solar photo voltaic generation system in India to find out its viability and techno-economic feasibility. Life-Cycle-Costinganalysis is employed to evaluate the long term benefit of the huge investments in India’s ambitious plan of setting up nearly 100 GW installed solar power capacity by December 2022. For renewable energy systems, this methodology shows the cost-effectiveness of being used as an alternative source compared to conventional power generations. Case studies of six solar power plants in India in the state of Karnataka, Gujarat, Andhra Pradesh, Tamil Nadu, New Delhi and Rajasthan were considered to find out the economic viability of the feasibility of the solar power plants in India. It has been observed that in an emerging economy like India, the feasibility and economic viability of solar power plants are quite high. The cash flow analysis for all six cases confirms that project payback depends on initial investment and rate of Power–Purchase-Agreement (PPA). It has been observed that the payback period is generally less than eight years. Thereby the techno-economic feasibility of the solar power plant projects in India is quite high.

A Framework for the Resilience of LV Electrical Networks with Photovoltaic Power Injection

Context: Electrical distribution networks have undergone several changes in the last decade. Some changes include incorporating distributed energy sources, such as solar photovoltaic (PV) generation systems. It could modify the performance of the electrical network and leads to new challenges such as evaluating the impacts of the PV integration, the response to electrical and climatic disturbances, and the planning and restructuring of networks. Electrical network behavior versus PV integration could be evaluated by quantifying the variation in operation and including network resilience.
 Objective: Propose a reference framework to evaluate the resilience of LV electrical networks with PV power injection.
 Methodology: This paper addresses the framework for evaluating the performance of a low voltage (LV) electrical network in the face of the integration of PVs. It collects research related to evaluating the resilience of electrical networks on severe climate changes, natural disasters, and typical maneuvers. Then, it proposes a guideline to evaluate the performance of LV electrical networks with the integration of PV generation sources and includes resilience. For this, the determination of resilience evaluation indices is proposed. The indices are obtained from a normalized transformation of the measurable electrical parameters of the networks. The parameters are those that present the most affected by PV integration or are significant in the performance of the networks. Finally, it presents the evaluation of a proposed resilience index for a university building LV network as a case study.
 Results: The resilience assessment proposal is applied to a case study. When evaluating the resilience of the voltage at the common coupling point of the PV, an index of 0.84 is obtained, equivalent to 59.8 hours of overvoltage.
 Conclusions: It is possible to improve the resilience of the BT network through management strategies. In the case study, a 29% reduction in overvoltage hours was obtained by applying a curtailment strategy to the PV system.
 Financing: ECOS-Nord, Minciencias and Universidad Industrial de Santander.

Characterization of photovoltaic solar energy systems in a Colombian region

Objective: To establish a baseline about the solar photovoltaic energy systems installed in the department of Caldas, Colombia. Methodology: The solar photovoltaic installations were identified from secondary sources of information, followed by field visits to collect information on the characteristics of these systems. An evaluation instrument was designed consisting of 6 categories which was subsequently evaluated by expert peers. It was applied accompanied by interviews with owners of the identified systems. Results: 41 solar photovoltaic systems were identified and installed in 11 municipalities of Caldas. Data was collected from 28 installations with different characteristics. 50% of the solar photovoltaic systems are in the Central-South region of Caldas. 71% of the systems are mainly installed in the urban area; 64% correspond to small-scale isolated solar photovoltaic energy generation systems, with a maximum power of less than 600W. These installations have become a viable energy alternative for the region and are being used especially for lighting and the operation of household appliances in residences, hotels, restaurants, and educational institutions. Conclusions: Although regulations on solar energy installations had not been established, these systems have already been implemented in the department in a successful, but moderate, manner.

Technical Performance and Economic Feasibility Simulation of 200kWP Rooftop Solar Photovoltaic On grid on Industrial Estate Factory Building with Helioscope Software

Renewable energy resources are currently being developed in Indonesia. The government is also targeting renewable energy mix of 23% to be achieved in 2025. Solar Photovoltaic Generation System is one of a form of renewable energy that is currently being developed in Indonesia. Several industrial estates in Indonesia are filled with factories with fairly large buildings and have great potential for the development of Rooftop Solar Photovoltaic with the advantage of reducing land investment costs and of course without reducing the functionality of factory operational. The purpose of this research is to simulate the technical and economic performance of Solar Photovoltaic on grid 200kWP installed on the roof of a factory building using Helioscope software in an industrial estate area in West Java. The simulation results show that the average value for Global Horizontal Irradiance (GHI) is 138.2 kWh/m2, Electrical Energy Production is 21,977 kWh, and the Performance Ratio (PR) in one year is 78.06. Meanwhile, the total annual Electrical Energy Production is 263,723.6 kWh. The total investment value of the Rooftop Solar Photovoltaic on Grid system in this factory building is Rp. 2,457,850,800. Based on the economic feasibility study made, it can be concluded that the Rooftop Solar Photovoltaic on Grid system with a power of 200 kWP in the factory building is economically feasible as long as the interest rate is less than 12.71% (Internal Rate of Return/ IRR).

On the Optimal Tilt Angle and Orientation of an On-Site Solar Photovoltaic Energy Generation System for Sabah’s Rural Electrification

An ongoing project to implement a mini standalone solar photovoltaic (PV) generation system of 2.5 kWp capacity at the eco-tourism centre of Liogu Ku Silou-Silou (EPLISSI), Sabah, was initiated in 2019. Since the solar panel support (ground mounting) used in this project will be erected separately, the main goals of this study are to estimate the optimum tilt angle, βopt, and orientation for the solar PV modules. To achieve these goals, the Liu and Jordan isotropic diffuse radiation model was used (1960). Another three isotropic diffuse sky radiation models (Koronakis model, Badescu model, and Tian model) were applied to estimate the optimum tilt angle with the orientation kept facing due south. For verification purposes, the PV power output data obtained from an online PV simulator known as Global Solar Atlas or GSA 2.3 was used and compared to the results of the four isotropic models. The results suggest that the Tian model is more suitable for approximating insolation, as it was proven to have the lowest difference among all models and is in close agreement with the result of the optimum tilt angle provided by GSA 2.3. However, the outcomes demonstrated from the isotropic models propose an error up to 30% (in the range of 31% to 32%) as compared to GSA 2.3.

Active–passive combined energy-efficient retrofit of rural residence with non-benchmarked construction: A case study in Shandong province, China

Unlike standard-restricted and well-equipped urban residential buildings, a large portion of rural buildings sacrifice indoor comfort and energy efficiency to reduce the initial investment. Therefore, cost-effective retrofit strategies for rural buildings are urgently needed to better living conditions and create higher energy efficiency. This study developed a framework to choose the optimal economical retrofitting strategies for existing rural buildings by taking both active and passive approaches into consideration. The building retrofitting measurements were a combination of thermal performance improvement for external walls and a solar photovoltaic generation system for the rooftop. With the case of a rural dwelling in Shandong province, this study first assessed the thermal transmittance of the external walls and collected geometry and operational schedules to create a building model for the later energy simulation. Environmental monitoring was also conducted for two months – in February for winter and August for summer – to obtain actual indoor temperatures, which were used to calibrate the energy model within a 10% error rate. In total, 17 retrofitting plans were then set up and analyzed in this study. The results showed that when applying the cost-optimal retrofit plan, there is the great potential to reduce energy use by 20.5% and to balance the annual building energy consumption with a payback period of 10.7 years. Finally, the proposed framework was proven to be accurate and feasible and was expected to be widely used in the improvement of living conditions in Chinese rural areas.

An MPPT method using hybrid radial movement optimization with teaching-learning based optimization under fluctuating atmospheric conditions

Due to its clean and abundant availability, solar energy is popular as a source to generate electricity. Solar photovoltaic (PV) technology converts sunlight incident on the solar PV panel or array directly into non-linear DC electricity. However, the non-linear nature of the solar panels’ power needs to be tracked for its efficient utilization. The problem of non-linearity becomes more prominent when the solar PV array is shaded, even leading to high power losses and concentrated heating in some areas (hotspot condition) of the PV array. Bypass diodes used to eliminate the shading effect cause multiple peaks of power on the power versus voltage (P-V) curve and make the tracking problem quite complex. Conventional algorithms to track the optimal power point cannot search the complete P-V curve and often become trapped in local optima. More recently, metaheuristic algorithms have been employed for maximum power point tracking. Being stochastic, these algorithms explore the complete search area, thereby eliminating any chance of becoming trapped stuck in local optima. This paper proposes a hybridized version of two metaheuristic algorithms, Radial Movement Optimization and teaching-learning based optimization (RMOTLBO). The algorithm has been discussed in detail and applied to multiple shading patterns in a solar PV generation system. It successfully tracks the maximum power point (MPP) in a lesser amount of time and lesser fluctuations.

Multi-objective Pareto based Optimal Placement and Sizing of Solar PV and Wind Generation System

Appropriate placement and sizing of distributed generation is required for reducing power loss and improvement in voltage profile of power system. Solar photovoltaic (PV) and wind energy are two prominent sources of distributed generation. In this paper, the authors propose a novel method to analyze the optimal placement and sizing of the solar PV and wind generation system in a radial distribution system. A multi objective function is selected for optimal siting and sizing. A 33-bus distribution system has been considered for testing the developed algorithm. Optimal location is obtained by placing DG source at each bus and satisfying objective function. Jaya algorithm is implemented for optimal sizing of PV and wind system. Also the system has been analyzed by placing the solar PV and Wind generation system independently and then simultaneously.